Jaspar_enrichment

Last updated: 2025-05-06

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Knit directory: ATAC_learning/

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Untracked files:
    Untracked:  analysis/Diagnosis-tmm.Rmd
    Untracked:  analysis/Expressed_RNA_associations.Rmd
    Untracked:  analysis/LFC_corr.Rmd
    Untracked:  analysis/QC_on_reads.Rmd
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    Untracked:  output/cormotif_probability_all_6_list.csv
    Untracked:  setup.RData

Unstaged changes:
    Modified:   ATAC_learning.Rproj
    Modified:   analysis/Jaspar_motif.Rmd
    Modified:   analysis/final_four_analysis.Rmd

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/Jaspar_motif_ff.Rmd) and HTML (docs/Jaspar_motif_ff.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
Rmd	ce8f202	reneeisnowhere	2025-05-06	update webpage
html	8520f12	E. Renee Matthews	2025-01-27	Build site.
Rmd	b8446aa	E. Renee Matthews	2025-01-27	adjust ESR open axis
html	aa0769e	E. Renee Matthews	2025-01-02	Build site.
Rmd	68ded3e	E. Renee Matthews	2025-01-02	new data
html	1c68be2	reneeisnowhere	2024-12-23	Build site.
Rmd	46d4487	reneeisnowhere	2024-12-23	updates to motif table
Rmd	2698702	reneeisnowhere	2024-11-14	more commits
html	b5b2c0f	reneeisnowhere	2024-10-18	Build site.
Rmd	73ac3ff	reneeisnowhere	2024-10-18	Adding zbtb14 for EAR_open
html	5bf51a6	reneeisnowhere	2024-10-18	Build site.
Rmd	ac14581	reneeisnowhere	2024-10-18	updates to plotting
html	b7543b3	reneeisnowhere	2024-10-14	Build site.
Rmd	51ccf8f	reneeisnowhere	2024-10-14	updates to motif sets
html	f9c15bd	reneeisnowhere	2024-10-12	Build site.
Rmd	5609d59	reneeisnowhere	2024-10-12	updates
html	d8eef0e	reneeisnowhere	2024-10-09	Build site.
Rmd	12a7203	reneeisnowhere	2024-10-09	updates to motif position plots!
html	14551f7	reneeisnowhere	2024-09-26	Build site.
Rmd	6cdc685	reneeisnowhere	2024-09-26	updates with 4 sets of peaks

packages

library(tidyverse)
library(cowplot)
library(kableExtra)
library(broom)
library(RColorBrewer)
library(ChIPseeker)
library("TxDb.Hsapiens.UCSC.hg38.knownGene")
library("org.Hs.eg.db")
library(rtracklayer)
library(edgeR)
library(ggfortify)
library(limma)
library(readr)
library(BiocGenerics)
library(gridExtra)
library(VennDiagram)
library(scales)
library(Cormotif)
library(BiocParallel)
library(ggpubr)
library(devtools)
library(JASPAR2022)
library(TFBSTools)
library(MotifDb)
library(BSgenome.Hsapiens.UCSC.hg38)
library(data.table)
library(universalmotif)
library(ggseqlogo)
library(motifmatchr)
library(gridExtra)

Data loading

# 
# lala <- read_delim("C:/Users/renee/ATAC_folder/ATAC_meme_data/200bp/EAR_open_200xstreme/xstreme.tsv",
#     delim = "\t", escape_double = FALSE,
#     trim_ws = TRUE)

# saveRDS(xstreme_EAR_openSVA,"data/Final_four_data/xstreme/xstreme_EAR_openSVA.RDS")



# saveRDS(xstreme_EAR_close200,"data/Final_four_data/xstreme/xstreme_EAR_close200.RDS")
# saveRDS(xstreme_EAR_open200,"data/Final_four_data/xstreme/xstreme_EAR_open200.RDS")
# saveRDS(xstreme_ESR_open200,"data/Final_four_data/xstreme/xstreme_ESR_open200.RDS")
# saveRDS(xstreme_ESR_close200,"data/Final_four_data/xstreme/xstreme_ESR_close200.RDS")
# saveRDS(ESR_OC_xstreme,"data/Final_four_data/xstreme/ESR_OC_xstreme.RDS")
# saveRDS(ESR_C_xstreme,"data/Final_four_data/xstreme/ESR_OC_xstreme.RDS")
# saveRDS(xstreme_ESR_clop200,"data/Final_four_data/xstreme/xstreme_ESR_clop200.RDS")
# saveRDS(xstreme_LR_close200,"data/Final_four_data/xstreme/xstreme_LR_close200.RDS")
# saveRDS(xstreme_LR_open200,"data/Final_four_data/xstreme/xstreme_LR_open200.RDS")
# saveRDS(LR_open_10h_xstreme,"data/Final_four_data/xstreme/LR_open_10h_xstreme.RDS")
# saveRDS(xstreme_ESR_opcl200,"data/Final_four_data/xstreme/xstreme_ESR_opcl200.RDS")


EAR_close_xstreme <-
  readRDS("data/Final_four_data/xstreme/EAR_close_xstreme.RDS")%>%
  slice_head(n = length(.$ID)-3)
EAR_open_xstreme <- 
  readRDS("data/Final_four_data/xstreme/EAR_open_xstreme.RDS")%>%
  slice_head(n = length(.$ID)-3)
ESR_open_xstreme <- 
  readRDS("data/Final_four_data/xstreme/ESR_open_xstreme.RDS")%>%
  slice_head(n = length(.$ID)-3)
ESR_close_xstreme <- 
  readRDS("data/Final_four_data/xstreme/ESR_close_xstreme.RDS")%>%
  slice_head(n = length(.$ID)-3)
ESR_OC_xstreme <- 
  readRDS("data/Final_four_data/xstreme/ESR_OC_xstreme.RDS")%>%
  slice_head(n = length(.$ID)-3)
ESR_opcl_xstreme <- 
  readRDS("data/Final_four_data/xstreme/xstreme_ESR_opcl200.RDS")%>%
  slice_head(n = length(.$ID)-3)
ESR_clop_xstreme <- 
  readRDS("data/Final_four_data/xstreme/xstreme_ESR_clop200.RDS")%>%
  slice_head(n = length(.$ID)-3)


LR_close_xstreme <-
  readRDS("data/Final_four_data/xstreme/LR_close_xstreme.RDS")%>%
  slice_head(n = length(.$ID)-3)
LR_open_xstreme <-
  readRDS("data/Final_four_data/xstreme/LR_open_10h_xstreme.RDS")%>%
  slice_head(n = length(.$ID)-3)
LR_open_10h_xstreme <-
  readRDS("data/Final_four_data/xstreme/LR_open_10h_xstreme.RDS")%>%
  slice_head(n = length(.$ID)-3)

EAR_close_200xstreme <-
  readRDS("data/Final_four_data/xstreme/xstreme_EAR_close200.RDS")%>%
  slice_head(n = length(.$ID)-3)
EAR_open_200xstreme <- 
  readRDS("data/Final_four_data/xstreme/xstreme_EAR_open200.RDS")%>%
  slice_head(n = length(.$ID)-3)
ESR_open_200xstreme <- 
  readRDS("data/Final_four_data/xstreme/xstreme_ESR_open200.RDS")%>%
  slice_head(n = length(.$ID)-3)

ESR_close_200xstreme <- 
  readRDS("data/Final_four_data/xstreme/xstreme_ESR_close200.RDS")%>%
  slice_head(n = length(.$ID)-3)
ESR_OC_xstreme <-
  readRDS("data/Final_four_data/xstreme/xstreme_LR_open200.RDS")%>%
  slice_head(n = length(.$ID)-3)
LR_close_200xstreme <-
  readRDS("data/Final_four_data/xstreme/xstreme_LR_close200.RDS")%>%
  slice_head(n = length(.$ID)-3)
LR_open_200xstreme <-
  readRDS("data/Final_four_data/xstreme/xstreme_LR_open200.RDS")%>%
  slice_head(n = length(.$ID)-3)
#### full sequence sea out
sea_EAR_open <- readRDS("data/Final_four_data/xstreme/sea_EAR_open.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_EAR_close <- readRDS("data/Final_four_data/xstreme/sea_EAR_close.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_ESR_close <- readRDS("data/Final_four_data/xstreme/sea_ESR_close.RDS")
sea_ESR_open <- readRDS("data/Final_four_data/xstreme/sea_ESR_open.RDS")#%>%
  # slice_head(n = length(.$ID)-3)
 
sea_ESR_OC <- readRDS("data/Final_four_data/xstreme/sea_ESR_OC.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_LR_open <- readRDS("data/Final_four_data/xstreme/sea_LR_open_10h.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_LR_close <- readRDS("data/Final_four_data/xstreme/sea_LR_close.RDS")%>%
  slice_head(n = length(.$ID)-3)

sea_LR_open <- readRDS("data/Final_four_data/xstreme/sea_LR_open_10h.RDS")%>%
  slice_head(n = length(.$ID)-3)


### sea out 200 bp sequences
# sea_ESR_clop200 <- read_delim("~/ATAC_meme_data/200bp/ESR_D_200xstreme/sea_out/sea.tsv",
#     delim = "\t", escape_double = FALSE,
#     trim_ws = TRUE)
# saveRDS(sea_ESR_clop200,"data/Final_four_data/xstreme/sea_ESR_clop_200.RDS")

### sea part2!

sea_EAR_open_200 <- readRDS("data/Final_four_data/xstreme/sea_EAR_open_200.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_EAR_close_200 <- readRDS("data/Final_four_data/xstreme/sea_EAR_close_200.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_ESR_close_200 <- readRDS("data/Final_four_data/xstreme/sea_ESR_close_200.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_ESR_open_200 <- readRDS("data/Final_four_data/xstreme/sea_ESR_open_200.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_ESR_opcl_200 <- readRDS("data/Final_four_data/xstreme/sea_ESR_opcl_200.RDS")%>%
  slice_head(n = length(.$ID)-3)

sea_ESR_clop_200 <- readRDS("data/Final_four_data/xstreme/sea_ESR_clop_200.RDS")%>%
  slice_head(n = length(.$ID)-3)

sea_LR_open_200 <- readRDS("data/Final_four_data/xstreme/sea_LR_open_200.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_LR_close_200 <- readRDS("data/Final_four_data/xstreme/sea_LR_close_200.RDS")%>%
  slice_head(n = length(.$ID)-3)


### sea part2!  This is for missing merged data in sea_disc_out 
# sea_ESR_clop_p2 <- read_delim("~/ATAC_meme_data/200bp/ESR_D_200xstreme/sea_disc_out/sea.tsv",
#     delim = "\t", escape_double = FALSE,
#     trim_ws = TRUE)
# saveRDS(sea_ESR_clop_p2,"data/Final_four_data/xstreme/sea_ESR_clop_200_p2.RDS")


sea_EAR_open_200_p2 <- readRDS("data/Final_four_data/xstreme/sea_EAR_open_200_p2.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_EAR_close_200_p2 <- readRDS("data/Final_four_data/xstreme/sea_EAR_close_200_p2.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_ESR_close_200_p2 <- readRDS("data/Final_four_data/xstreme/sea_ESR_close_200_p2.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_ESR_open_200_p2 <- readRDS("data/Final_four_data/xstreme/sea_ESR_open_200_p2.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_ESR_opcl_200_p2 <- readRDS("data/Final_four_data/xstreme/sea_ESR_opcl_200_p2.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_ESR_clop_200_p2 <- readRDS("data/Final_four_data/xstreme/sea_ESR_clop_200_p2.RDS")%>%
  slice_head(n = length(.$ID)-3)

sea_LR_open_200_p2 <- readRDS("data/Final_four_data/xstreme/sea_LR_open_200_p2.RDS")%>%
  slice_head(n = length(.$ID)-3)
sea_LR_close_200_p2 <- readRDS("data/Final_four_data/xstreme/sea_LR_close_200_p2.RDS")%>%
  slice_head(n = length(.$ID)-3)




peakAnnoList_ff_8motif <- readRDS("data/Final_four_data/peakAnnoList_ff_8motif.RDS")
# saveRDS(ESR_D,"data/Final_four_data/ESR_D.RDS") 
toplistall_RNA <- readRDS("data/other_papers/toplistall_RNA.RDS")
###Because of how I applied the DEG system in RNA-seq analysis, the lFC is opposite of the 
###counts.   I did trt-veh instead of veh-trt.  therefore I need to multiply lfc by -1 to get t
###the right correlation.

toplistall_RNA <- toplistall_RNA %>%
  mutate(logFC = logFC*(-1))

RNA_expresed_genes <- toplistall_RNA %>%
  # dplyr::filter(adj.P.Val <0.05) %>%
   mutate(expression = if_else(logFC<0,"down","up")) %>%
  dplyr::select(ENTREZID,SYMBOL,expression) %>%
  # dplyr::select(ENTREZID,SYMBOL) %>%
  unique(.)
RNA_expresed_genes_DE <- toplistall_RNA %>%
  dplyr::filter(adj.P.Val <0.05) %>%
  mutate(expression = if_else(logFC<0,"down","up")) %>%
  dplyr::select(ENTREZID,SYMBOL,expression) %>%
  unique(.)

Enrichment all peaks to NR peaks

EAR lists

# EAR_open_xstreme%>% 
#   dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
#   arrange(.,EVALUE) %>% 
#   dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
#   kable(., caption = "Enriched motifs in EAR open v NR") %>%
#   kable_paper("striped", full_width = TRUE) %>%
#   kable_styling(full_width = FALSE, font_size = 16) %>%
#   scroll_box(height = "500px")

EAR_open_200xstreme%>% 
  dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
  arrange(.,EVALUE) %>% 
  dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
  kable(., caption = "Enriched motifs 200 bp in EAR open v NR") %>%
  kable_paper("striped", full_width = TRUE) %>%
  kable_styling(full_width = FALSE, font_size = 16) %>%
  scroll_box(height = "500px")

Enriched motifs 200 bp in EAR open v NR
RANK	SIM_MOTIF	ALT_ID	ID	SEA_PVALUE	EVALUE
5	MA1650.1	ZBTB14	MA1650.1	2.42e-39	2.07e-36
7	MA0506.2	Nrf1	MA0506.2	2.82e-38	2.41e-35
114	MA1125.1 (ZNF384)	MEME-1	TTWTTTTTTTWTTTT	0.901	1.1e-31
9	MA1713.1	ZNF610	MA1713.1	2.55e-30	2.18e-27
12	MA0131.2	HINFP	MA0131.2	2.26e-24	1.93e-21
13	MA1122.1	TFDP1	MA1122.1	7.68e-24	6.56e-21
14	MA1721.1	ZNF93	MA1721.1	8.56e-24	7.31e-21
15	MA0865.2	E2F8	MA0865.2	1.39e-23	1.19e-20
16	MA1513.1	KLF15	MA1513.1	4.24e-23	3.62e-20
18	MA0024.3	E2F1	MA0024.3	3.59e-21	3.06e-18
19	MA0527.1	ZBTB33	MA0527.1	1.62e-19	1.38e-16
20	MA0162.4	EGR1	MA0162.4	1.45e-18	1.24e-15
21	MA0814.2	TFAP2C	MA0814.2	2.46e-18	2.1e-15
22	MA0748.2	YY2	MA0748.2	9.82e-18	8.38e-15
24	MA0632.2	TCFL5	MA0632.2	1.3e-16	1.11e-13
25	MA0864.2	E2F2	MA0864.2	2.29e-16	1.96e-13
26	MA0810.1	TFAP2A	MA0810.1	3.28e-16	2.8e-13
27	MA0823.1	HEY1	MA0823.1	6.39e-16	5.46e-13
28	MA0732.1	EGR3	MA0732.1	9.97e-16	8.51e-13
29	MA0470.2	E2F4	MA0470.2	2.35e-15	2.01e-12
30	MA0472.2	EGR2	MA0472.2	3.21e-15	2.74e-12
32	MA0759.2	ELK3	MA0759.2	9.84e-15	8.4e-12
33	MA1106.1	HIF1A	MA1106.1	5.52e-14	4.71e-11
34	MA0764.3	ETV4	MA0764.3	1.78e-13	1.52e-10
35	MA0028.2	ELK1	MA0028.2	1.96e-13	1.67e-10
36	MA0006.1	Ahr::Arnt	MA0006.1	2.04e-13	1.74e-10
37	MA0615.1	Gmeb1	MA0615.1	4.9e-13	4.18e-10
38	MA0524.2	TFAP2C	MA0524.2	6.16e-13	5.26e-10
39	MA0765.3	ETV5	MA0765.3	1.11e-12	9.5e-10
40	MA1966.1	TFAP4::ETV1	MA1966.1	1.33e-12	1.14e-09
41	MA1560.1	SOHLH2	MA1560.1	1.82e-12	1.56e-09
42	MA0821.2	HES5	MA0821.2	3.19e-12	2.72e-09
43	MA0811.1	TFAP2B	MA0811.1	3.25e-12	2.78e-09
44	MA0156.3	FEV	MA0156.3	5.77e-12	4.92e-09
45	MA1545.1	OVOL2	MA1545.1	8.77e-12	7.49e-09
46	MA1727.1	ZNF417	MA1727.1	1.44e-11	1.23e-08
2	MA1713.1 (ZNF610)	MEME-3	SCSGSSGCGGSSSCG	2.72e-45	1.4e-08
47	MA1099.2	HES1	MA1099.2	1.96e-11	1.67e-08
48	MA0098.3	ETS1	MA0098.3	3.74e-11	3.2e-08
49	MA1569.1	TFAP2E	MA1569.1	3.77e-11	3.22e-08
50	MA1961.1	PATZ1	MA1961.1	4.01e-11	3.42e-08
51	MA0733.1	EGR4	MA0733.1	4.47e-11	3.82e-08
52	MA1102.2	CTCFL	MA1102.2	4.7e-11	4.02e-08
53	MA0475.2	FLI1	MA0475.2	4.93e-11	4.21e-08
104	MA1107.2 (KLF9)	MEME-2	TGTGTGTGTGTGTGT	1.73e-05	5.4e-08
54	MA0259.1	ARNT::HIF1A	MA0259.1	7.69e-11	6.57e-08
55	MA1684.1	Foxn1	MA1684.1	1.26e-10	1.08e-07
56	MA1596.1	ZNF460	MA1596.1	1.86e-10	1.59e-07
57	MA0750.2	ZBTB7A	MA0750.2	1.89e-10	1.61e-07
58	MA0695.1	ZBTB7C	MA0695.1	2.2e-10	1.88e-07
59	MA0872.1	TFAP2A	MA0872.1	5.76e-10	4.92e-07
60	MA1971.1	ZBED2	MA1971.1	8.84e-10	7.55e-07
61	MA0645.1	ETV6	MA0645.1	1.16e-09	9.93e-07
62	MA0763.1	ETV3	MA0763.1	2.04e-09	1.74e-06
63	MA1522.1	MAZ	MA1522.1	2.04e-09	1.75e-06
64	MA1976.1	ZNF320	MA1976.1	2.62e-09	2.24e-06
65	MA0649.1	HEY2	MA0649.1	3.65e-09	3.12e-06
66	MA1583.1	ZFP57	MA1583.1	3.8e-09	3.25e-06
1	MA1961.1 (PATZ1)	STREME-1	1-CGCCSCCGCCSCSSS	1.61e-45	7.11e-06
67	MA1648.1	TCF12	MA1648.1	8.42e-09	7.19e-06
68	MA1484.1	ETS2	MA1484.1	8.6e-09	7.35e-06
69	MA0076.2	ELK4	MA0076.2	1.23e-08	1.05e-05
70	MA0736.1	GLIS2	MA0736.1	2.43e-08	2.07e-05
71	MA0616.2	HES2	MA0616.2	3.05e-08	2.6e-05
72	MA0830.2	TCF4	MA0830.2	3.41e-08	2.91e-05
73	MA1719.1	ZNF816	MA1719.1	4.41e-08	3.77e-05
31	MA0076.2 (ELK4)	STREME-2	2-CCGGAAGCCG	4.32e-15	3.79e-05
74	MA0104.4	MYCN	MA0104.4	5.34e-08	4.56e-05
75	MA1548.1	PLAGL2	MA1548.1	5.69e-08	4.86e-05
76	MA1708.1	ETV7	MA1708.1	1.4e-07	0.000119
77	MA0516.3	SP2	MA0516.3	1.52e-07	0.00013
78	MA0471.2	E2F6	MA0471.2	3.05e-07	0.00026
79	MA1653.1	ZNF148	MA1653.1	3.47e-07	0.000296
80	MA1533.1	NR1I2	MA1533.1	4.19e-07	0.000358
81	MA0067.2	PAX2	MA0067.2	5.58e-07	0.000477
82	MA1990.1	Gli1	MA1990.1	5.77e-07	0.000493
83	MA1651.1	ZFP42	MA1651.1	5.84e-07	0.000499
84	MA1929.1	CTCF	MA1929.1	5.88e-07	0.000502
85	MA1973.1	ZKSCAN3	MA1973.1	9.46e-07	0.000808
4	MA0506.2 (Nrf1)	STREME-3	3-GCGCCGGCGC	4.1e-41	0.00117
86	MA0147.3	MYC	MA0147.3	1.48e-06	0.00126
87	MA1931.1	ELK1::HOXA1	MA1931.1	1.7e-06	0.00145
88	MA0004.1	Arnt	MA0004.1	1.87e-06	0.00159
89	MA1474.1	CREB3L4	MA1474.1	1.97e-06	0.00168
90	MA1712.1	ZNF454	MA1712.1	2.15e-06	0.00184
91	MA1941.1	ETV2::FIGLA	MA1941.1	2.58e-06	0.00221
92	MA0812.1	TFAP2B	MA0812.1	3.06e-06	0.00262
93	MA1515.1	KLF2	MA1515.1	4.6e-06	0.00393
94	MA0146.2	Zfx	MA0146.2	5.83e-06	0.00498
95	MA1934.1	ERF::FIGLA	MA1934.1	7.25e-06	0.00619
96	MA0145.2	Tfcp2l1	MA0145.2	8.61e-06	0.00736
8	MA0865.2 (E2F8)	STREME-4	4-CGGGAG	1.32e-33	0.0074
97	MA0734.3	Gli2	MA0734.3	8.9e-06	0.0076
10	MA1650.1 (ZBTB14)	STREME-5	5-CGCGCAG	1.88e-28	0.00805
98	MA0862.1	GMEB2	MA0862.1	9.62e-06	0.00822
99	MA0646.1	GCM1	MA0646.1	9.89e-06	0.00845
100	MA0863.1	MTF1	MA0863.1	1.01e-05	0.00863
101	MA1716.1	ZNF76	MA1716.1	1.07e-05	0.0091
102	MA1711.1	ZNF343	MA1711.1	1.2e-05	0.0102
103	MA1464.1	ARNT2	MA1464.1	1.6e-05	0.0136
105	MA1584.1	ZIC5	MA1584.1	1.74e-05	0.0148
106	MA0522.3	TCF3	MA0522.3	2.04e-05	0.0174
23	MA1938.1 (ERF::NHLH1)	STREME-6	6-CGGCAGC	1.38e-17	0.0177
107	MA0694.1	ZBTB7B	MA0694.1	2.12e-05	0.0181
108	MA1635.1	BHLHE22	MA1635.1	2.96e-05	0.0253
109	MA1564.1	SP9	MA1564.1	3.46e-05	0.0295
110	MA0751.1	ZIC4	MA0751.1	3.52e-05	0.0301
111	MA1578.1	VEZF1	MA1578.1	3.55e-05	0.0303
112	MA0597.2	THAP1	MA0597.2	5.11e-05	0.0436
113	MA0760.1	ERF	MA0760.1	5.46e-05	0.0466
3	7-CTCSGGCCGG	STREME-7	7-CTCSGGCCGG	1.35e-43	0.053
11	8-HCSSSGD	STREME-8	8-HCSSSGD	8.08e-25	0.0688
6	MA1713.1 (ZNF610)	STREME-9	9-GCGGCC	7.98e-39	0.0821
17	10-YGSACGW	STREME-10	10-YGSACGW	1.02e-21	4.94

# EAR_close_xstreme %>% 
#   dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
#   arrange(.,EVALUE) %>% 
#   # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
#   # dplyr::filter(., EVALUE<0.05) %>% 
#   dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
#   kable(., caption = "Enriched motifs in EAR close") %>%
#   kable_paper("striped", full_width = TRUE) %>%
#   kable_styling(full_width = FALSE, font_size = 16) %>%
#   scroll_box(height = "500px")
EAR_close_200xstreme %>% 
  dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
  arrange(.,EVALUE) %>% 
  # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  # dplyr::filter(., EVALUE<0.05) %>% 
  dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
  kable(., caption = "Enriched motifs in EAR close 200bp") %>%
  kable_paper("striped", full_width = TRUE) %>%
  kable_styling(full_width = FALSE, font_size = 16) %>%
  scroll_box(height = "500px")

Enriched motifs in EAR close 200bp
RANK	SIM_MOTIF	ALT_ID	ID	SEA_PVALUE	EVALUE
1	MA1988.1	Atf3	MA1988.1	5.76e-79	4.97e-76
2	MA0099.3	FOS::JUN	MA0099.3	7.68e-78	6.63e-75
3	MA1130.1	FOSL2::JUN	MA1130.1	2.59e-76	2.24e-73
4	MA1634.1	BATF	MA1634.1	1.33e-75	1.15e-72
5	MA0478.1	FOSL2	MA0478.1	6.12e-74	5.27e-71
6	MA0476.1	FOS	MA0476.1	8.67e-73	7.48e-70
7	MA0462.2	BATF::JUN	MA0462.2	2.17e-71	1.87e-68
8	MA1928.1	BNC2	MA1928.1	4.56e-71	3.93e-68
9	MA1633.2	BACH1	MA1633.2	4.39e-68	3.78e-65
10	MA1137.1	FOSL1::JUNB	MA1137.1	1.32e-67	1.14e-64
11	MA0655.1	JDP2	MA0655.1	3.48e-64	3e-61
12	MA1138.1	FOSL2::JUNB	MA1138.1	4.11e-63	3.54e-60
13	MA1134.1	FOS::JUNB	MA1134.1	3.79e-62	3.27e-59
345	MA1125.1 (ZNF384)	MEME-1	AAAAAAAAAAAAAAW	0.000107	5.2e-59
14	MA0841.1	NFE2	MA0841.1	1.35e-61	1.16e-58
15	MA1135.1	FOSB::JUNB	MA1135.1	5.79e-61	4.99e-58
16	MA1144.1	FOSL2::JUND	MA1144.1	6.98e-60	6.02e-57
18	MA1101.2	BACH2	MA1101.2	2.66e-58	2.29e-55
19	MA1141.1	FOS::JUND	MA1141.1	9.51e-58	8.2e-55
21	MA1128.1	FOSL1::JUN	MA1128.1	1.2e-55	1.03e-52
22	MA0766.2	GATA5	MA0766.2	1.05e-52	9.06e-50
23	MA0501.1	MAF::NFE2	MA0501.1	1.17e-52	1.01e-49
24	MA0835.2	BATF3	MA0835.2	2.69e-52	2.32e-49
348	MA1596.1 (ZNF460)	MEME-2	GGGAGGVDGRGGHDG	0.103	3e-47
26	MA1142.1	FOSL1::JUND	MA1142.1	2.07e-48	1.78e-45
27	MA0491.2	JUND	MA0491.2	9.76e-48	8.41e-45
28	MA0489.2	Jun	MA0489.2	3.48e-46	3e-43
29	MA0676.1	Nr2e1	MA0676.1	5.04e-46	4.35e-43
30	MA0477.2	FOSL1	MA0477.2	1.82e-45	1.57e-42
31	MA0490.2	JUNB	MA0490.2	1.6e-44	1.38e-41
32	MA0150.2	Nfe2l2	MA0150.2	2.85e-44	2.46e-41
33	MA0790.1	POU4F1	MA0790.1	2.93e-43	2.53e-40
34	MA0089.2	MAFG::NFE2L1	MA0089.2	1.08e-42	9.35e-40
35	MA1132.1	JUN::JUNB	MA1132.1	9.99e-41	8.61e-38
36	MA0496.3	MAFK	MA0496.3	3.04e-40	2.62e-37
38	MA0032.2	FOXC1	MA0032.2	5.27e-38	4.54e-35
39	MA0726.1	VSX2	MA0726.1	8.15e-38	7.02e-35
40	MA0792.1	POU5F1B	MA0792.1	1.1e-37	9.49e-35
41	MA0789.1	POU3F4	MA0789.1	2.5e-37	2.16e-34
43	MA0845.1	FOXB1	MA0845.1	4.79e-37	4.13e-34
44	MA0084.1	SRY	MA0084.1	9.84e-37	8.48e-34
45	MA0886.1	EMX2	MA0886.1	5.13e-36	4.43e-33
46	MA1104.2	GATA6	MA1104.2	7.95e-36	6.85e-33
47	MA0899.1	HOXA10	MA0899.1	1.31e-35	1.13e-32
48	MA0035.4	GATA1	MA0035.4	4.34e-35	3.74e-32
49	MA0793.1	POU6F2	MA0793.1	7.99e-35	6.89e-32
50	MA0791.1	POU4F3	MA0791.1	9.91e-35	8.54e-32
51	MA0037.4	Gata3	MA0037.4	2.98e-34	2.57e-31
52	MA1963.1	SATB1	MA1963.1	1.22e-33	1.05e-30
53	MA0675.1	NKX6-2	MA0675.1	1.38e-33	1.19e-30
54	MA0902.2	HOXB2	MA0902.2	1.71e-33	1.47e-30
55	MA0725.1	VSX1	MA0725.1	1.86e-33	1.61e-30
56	MA0704.1	Lhx4	MA0704.1	4.57e-33	3.94e-30
57	MA1639.1	MEIS1	MA1639.1	6.17e-33	5.31e-30
58	MA1481.1	DRGX	MA1481.1	1.85e-32	1.59e-29
59	MA0681.2	PHOX2B	MA0681.2	7.7e-32	6.64e-29
60	MA1530.1	NKX6-3	MA1530.1	8.12e-32	7e-29
61	MA0846.1	FOXC2	MA0846.1	8.18e-32	7.05e-29
62	MA0901.2	HOXB13	MA0901.2	1.29e-31	1.11e-28
63	MA0716.1	PRRX1	MA0716.1	2.6e-31	2.24e-28
64	MA0498.2	MEIS1	MA0498.2	2.72e-31	2.34e-28
65	MA0680.2	Pax7	MA0680.2	6.48e-31	5.59e-28
66	MA0630.1	SHOX	MA0630.1	7.29e-31	6.29e-28
67	MA1563.2	SOX18	MA1563.2	7.48e-31	6.45e-28
68	MA1113.2	PBX2	MA1113.2	7.85e-31	6.76e-28
69	MA0720.1	Shox2	MA0720.1	1.86e-30	1.6e-27
70	MA0723.2	VAX2	MA0723.2	2.38e-30	2.06e-27
71	MA1640.1	MEIS2	MA1640.1	2.81e-30	2.42e-27
72	MA0027.2	EN1	MA0027.2	7.06e-30	6.09e-27
73	MA0707.2	MNX1	MA0707.2	7.48e-30	6.45e-27
74	MA0627.2	POU2F3	MA0627.2	1.31e-29	1.13e-26
75	MA0052.4	MEF2A	MA0052.4	1.72e-29	1.49e-26
76	MA0601.1	Arid3b	MA0601.1	2.64e-29	2.27e-26
77	MA0788.1	POU3F3	MA0788.1	4e-29	3.45e-26
78	MA1480.1	DPRX	MA1480.1	4.03e-29	3.47e-26
79	MA0713.1	PHOX2A	MA0713.1	6.93e-29	5.98e-26
80	MA0724.1	VENTX	MA0724.1	1.05e-28	9.07e-26
81	MA1549.1	POU6F1	MA1549.1	1.1e-28	9.49e-26
82	MA0036.3	GATA2	MA0036.3	1.39e-28	1.19e-25
83	MA0650.3	Hoxa13	MA0650.3	2.09e-28	1.8e-25
84	MA1970.1	TRPS1	MA1970.1	4.14e-28	3.57e-25
85	MA0722.1	VAX1	MA0722.1	4.97e-28	4.28e-25
86	MA0785.1	POU2F1	MA0785.1	6.68e-28	5.75e-25
87	MA1471.1	BARX2	MA1471.1	7.28e-28	6.28e-25
88	MA1476.2	Dlx5	MA1476.2	9.51e-28	8.2e-25
89	MA1487.2	FOXE1	MA1487.2	1.59e-27	1.37e-24
90	MA0890.1	GBX2	MA0890.1	1.68e-27	1.45e-24
91	MA0482.2	GATA4	MA0482.2	2.26e-27	1.95e-24
92	MA0666.2	MSX1	MA0666.2	2.67e-27	2.3e-24
93	MA1502.1	HOXB8	MA1502.1	3.08e-27	2.66e-24
94	MA0708.2	MSX2	MA0708.2	5.31e-27	4.58e-24
95	MA0495.3	MAFF	MA0495.3	5.64e-27	4.86e-24
96	MA0879.2	DLX1	MA0879.2	5.67e-27	4.88e-24
98	MA0125.1	Nobox	MA0125.1	9.96e-27	8.59e-24
99	MA0654.1	ISX	MA0654.1	1.79e-26	1.54e-23
100	MA0523.1	TCF7L2	MA0523.1	2.11e-26	1.82e-23
101	MA1152.1	SOX15	MA1152.1	2.89e-26	2.49e-23
102	MA0782.2	PKNOX1	MA0782.2	3.31e-26	2.85e-23
103	MA0881.1	Dlx4	MA0881.1	4.17e-26	3.6e-23
104	MA0644.2	ESX1	MA0644.2	8.15e-26	7.03e-23
105	MA0628.1	POU6F1	MA0628.1	8.69e-26	7.49e-23
106	MA1978.1	ZNF354A	MA1978.1	1.72e-25	1.48e-22
107	MA0140.2	GATA1::TAL1	MA0140.2	1.79e-25	1.55e-22
108	MA0868.2	SOX8	MA0868.2	2.23e-25	1.92e-22
109	MA1495.1	HOXA1	MA1495.1	2.26e-25	1.95e-22
110	MA0876.1	BSX	MA0876.1	2.36e-25	2.04e-22
111	MA0025.2	NFIL3	MA0025.2	2.47e-25	2.13e-22
112	MA0709.1	Msx3	MA0709.1	3.02e-25	2.6e-22
113	MA1607.1	Foxl2	MA1607.1	3.65e-25	3.15e-22
114	MA0041.2	FOXD3	MA0041.2	4.29e-25	3.7e-22
115	MA0679.2	ONECUT1	MA0679.2	4.31e-25	3.72e-22
116	MA0885.2	Dlx2	MA0885.2	6.01e-25	5.18e-22
117	MA0842.2	NRL	MA0842.2	6.82e-25	5.88e-22
118	MA0031.1	FOXD1	MA0031.1	7.32e-25	6.31e-22
119	MA0721.1	UNCX	MA0721.1	8.02e-25	6.91e-22
120	MA0880.1	Dlx3	MA0880.1	8.28e-25	7.14e-22
121	MA0875.1	BARX1	MA0875.1	8.42e-25	7.26e-22
122	MA0710.1	NOTO	MA0710.1	1.01e-24	8.66e-22
123	MA0882.1	DLX6	MA0882.1	1.07e-24	9.18e-22
124	MA0705.1	Lhx8	MA0705.1	1.12e-24	9.67e-22
125	MA1606.1	Foxf1	MA1606.1	1.51e-24	1.3e-21
126	MA0602.1	Arid5a	MA0602.1	1.59e-24	1.37e-21
127	MA0909.3	Hoxd13	MA0909.3	1.88e-24	1.62e-21
128	MA0142.1	Pou5f1::Sox2	MA0142.1	2.79e-24	2.41e-21
325	MA1973.1 (ZKSCAN3)	MEME-3	TGTYGCCCAGGCTGG	9.74e-06	2.8e-21
129	MA1519.1	LHX5	MA1519.1	3.88e-24	3.34e-21
130	MA0047.3	FOXA2	MA0047.3	5.88e-24	5.07e-21
131	MA0700.2	LHX2	MA0700.2	6.7e-24	5.77e-21
132	MA0648.1	GSC	MA0648.1	8.84e-24	7.62e-21
133	MA0481.3	FOXP1	MA0481.3	1.18e-23	1.02e-20
134	MA0682.2	PITX1	MA0682.2	1.63e-23	1.41e-20
135	MA0889.1	GBX1	MA0889.1	2.45e-23	2.11e-20
136	MA0910.2	HOXD8	MA0910.2	3.37e-23	2.9e-20
137	MA0903.1	HOXB3	MA0903.1	3.84e-23	3.31e-20
138	MA0635.1	BARHL2	MA0635.1	4.66e-23	4.01e-20
139	MA0674.1	NKX6-1	MA0674.1	5.88e-23	5.07e-20
140	MA0634.1	ALX3	MA0634.1	6.61e-23	5.7e-20
142	MA0787.1	POU3F2	MA0787.1	1.29e-22	1.11e-19
143	MA0658.1	LHX6	MA0658.1	1.34e-22	1.16e-19
144	MA0706.1	MEOX2	MA0706.1	1.77e-22	1.52e-19
145	MA0497.1	MEF2C	MA0497.1	3.03e-22	2.61e-19
346	MA0682.2 (PITX1)	MEME-4	WGCTGGGATTACAGG	0.000961	4.2e-19
146	MA0042.2	FOXI1	MA0042.2	5.8e-22	5e-19
147	MA0077.1	SOX9	MA0077.1	7.04e-22	6.07e-19
148	MA0612.2	EMX1	MA0612.2	1.33e-21	1.15e-18
149	MA1115.1	POU5F1	MA1115.1	1.67e-21	1.44e-18
151	MA0465.2	CDX2	MA0465.2	2.63e-21	2.27e-18
153	MA1603.1	Dmrt1	MA1603.1	3.18e-21	2.74e-18
154	MA0148.4	FOXA1	MA0148.4	3.72e-21	3.21e-18
155	MA0786.1	POU3F1	MA0786.1	4.04e-21	3.48e-18
156	MA1636.1	CEBPG	MA1636.1	4.56e-21	3.93e-18
157	MA0718.1	RAX	MA0718.1	9.15e-21	7.88e-18
158	MA0848.1	FOXO4	MA0848.1	9.71e-21	8.37e-18
159	MA0033.2	FOXL1	MA0033.2	1.54e-20	1.33e-17
160	MA0904.2	HOXB5	MA0904.2	1.87e-20	1.61e-17
161	MA1657.1	ZNF652	MA1657.1	3.73e-20	3.21e-17
162	MA0144.2	STAT3	MA0144.2	4.25e-20	3.66e-17
163	MA0018.4	CREB1	MA0018.4	5.76e-20	4.97e-17
164	MA0908.1	HOXD11	MA0908.1	6.06e-20	5.22e-17
165	MA0775.1	MEIS3	MA0775.1	8.53e-20	7.35e-17
166	MA0905.1	HOXC10	MA0905.1	2.07e-19	1.78e-16
167	MA1103.2	FOXK2	MA1103.2	2.2e-19	1.9e-16
168	MA0887.1	EVX1	MA0887.1	2.46e-19	2.12e-16
169	MA0070.1	PBX1	MA0070.1	2.94e-19	2.54e-16
170	MA0914.1	ISL2	MA0914.1	3.28e-19	2.83e-16
171	MA0143.4	SOX2	MA0143.4	3.51e-19	3.02e-16
172	MA0847.3	FOXD2	MA0847.3	3.54e-19	3.05e-16
173	MA1114.1	PBX3	MA1114.1	5.69e-19	4.91e-16
174	MA1498.2	HOXA7	MA1498.2	7.11e-19	6.13e-16
175	MA0717.1	RAX2	MA0717.1	8.84e-19	7.62e-16
176	MA1505.1	HOXC8	MA1505.1	1.03e-18	8.87e-16
177	MA0662.1	MIXL1	MA0662.1	1.18e-18	1.01e-15
178	MA0894.1	HESX1	MA0894.1	1.66e-18	1.43e-15
179	MA0117.2	Mafb	MA0117.2	2e-18	1.72e-15
180	MA0442.2	SOX10	MA0442.2	2.13e-18	1.83e-15
181	MA0892.1	GSX1	MA0892.1	4.25e-18	3.66e-15
182	MA0701.2	LHX9	MA0701.2	5.01e-18	4.32e-15
183	MA1120.1	SOX13	MA1120.1	5.15e-18	4.44e-15
184	MA0492.1	JUND	MA0492.1	5.25e-18	4.53e-15
185	MA1632.1	ATF2	MA1632.1	6.18e-18	5.33e-15
186	MA0068.2	PAX4	MA0068.2	9.35e-18	8.06e-15
187	MA1960.1	MGA::EVX1	MA1960.1	1.16e-17	9.98e-15
188	MA0891.1	GSC2	MA0891.1	2.01e-17	1.74e-14
189	MA1683.1	FOXA3	MA1683.1	2.18e-17	1.88e-14
190	MA0774.1	MEIS2	MA0774.1	3.03e-17	2.61e-14
191	MA0699.1	LBX2	MA0699.1	3.12e-17	2.69e-14
192	MA0642.2	EN2	MA0642.2	4.21e-17	3.63e-14
193	MA0151.1	Arid3a	MA0151.1	6.05e-17	5.21e-14
194	MA0124.2	Nkx3-1	MA0124.2	1.15e-16	9.92e-14
195	MA0895.1	HMBOX1	MA0895.1	1.21e-16	1.04e-13
196	MA1463.1	ARGFX	MA1463.1	1.49e-16	1.28e-13
197	MA0488.1	JUN	MA0488.1	2.37e-16	2.04e-13
198	MA0108.2	TBP	MA0108.2	3.04e-16	2.62e-13
199	MA0122.3	Nkx3-2	MA0122.3	3.06e-16	2.64e-13
200	MA1497.1	HOXA6	MA1497.1	3.61e-16	3.11e-13
201	MA0769.2	TCF7	MA0769.2	6.71e-16	5.78e-13
202	MA0797.1	TGIF2	MA0797.1	1.61e-15	1.39e-12
203	MA0102.4	CEBPA	MA0102.4	1.61e-15	1.39e-12
205	MA0711.1	OTX1	MA0711.1	4.57e-15	3.94e-12
206	MA0829.2	SREBF1	MA0829.2	5.73e-15	4.94e-12
207	MA1720.1	ZNF85	MA1720.1	6.66e-15	5.74e-12
208	MA1489.1	FOXN3	MA1489.1	6.73e-15	5.8e-12
209	MA0157.3	Foxo3	MA0157.3	6.91e-15	5.96e-12
210	MA0851.1	Foxj3	MA0851.1	1.39e-14	1.2e-11
211	MA0712.2	OTX2	MA0712.2	1.53e-14	1.32e-11
212	MA1499.1	HOXB4	MA1499.1	1.63e-14	1.4e-11
213	MA0913.2	HOXD9	MA0913.2	1.98e-14	1.7e-11
214	MA0833.2	ATF4	MA0833.2	2.18e-14	1.88e-11
215	MA0661.1	MEOX1	MA0661.1	4.08e-14	3.52e-11
216	MA0912.2	HOXD3	MA0912.2	4.79e-14	4.13e-11
217	MA0063.2	NKX2-5	MA0063.2	6.56e-14	5.65e-11
218	MA1124.1	ZNF24	MA1124.1	7.57e-14	6.52e-11
219	MA0596.1	SREBF2	MA0596.1	8.72e-14	7.52e-11
220	MA0659.3	Mafg	MA0659.3	9.98e-14	8.6e-11
221	MA0911.1	Hoxa11	MA0911.1	1.04e-13	8.98e-11
222	MA0029.1	Mecom	MA0029.1	1.24e-13	1.06e-10
223	MA0900.2	HOXA2	MA0900.2	1.75e-13	1.51e-10
224	MA0611.2	Dux	MA0611.2	1.99e-13	1.71e-10
225	MA1504.1	HOXC4	MA1504.1	2.59e-13	2.24e-10
226	MA1518.2	Lhx1	MA1518.2	2.78e-13	2.4e-10
227	MA1110.2	Nr1H4	MA1110.2	2.78e-13	2.4e-10
228	MA0867.2	SOX4	MA0867.2	4.35e-13	3.75e-10
229	MA0805.1	TBX1	MA0805.1	4.68e-13	4.03e-10
230	MA1623.1	Stat2	MA1623.1	9.21e-13	7.94e-10
231	MA0888.1	EVX2	MA0888.1	9.28e-13	8e-10
232	MA0483.1	Gfi1B	MA0483.1	9.97e-13	8.59e-10
233	MA1608.1	Isl1	MA1608.1	1.13e-12	9.73e-10
234	MA0050.3	Irf1	MA0050.3	1.25e-12	1.08e-09
235	MA1479.1	DMRTC2	MA1479.1	1.29e-12	1.11e-09
236	MA0613.1	FOXG1	MA0613.1	1.68e-12	1.45e-09
237	MA0768.2	Lef1	MA0768.2	1.82e-12	1.57e-09
238	MA0715.1	PROP1	MA0715.1	2.14e-12	1.84e-09
240	MA0898.1	Hmx3	MA0898.1	4.47e-12	3.85e-09
241	MA0153.2	HNF1B	MA0153.2	5.13e-12	4.42e-09
242	MA0624.2	Nfatc1	MA0624.2	5.18e-12	4.46e-09
243	MA0714.1	PITX3	MA0714.1	5.24e-12	4.52e-09
244	MA1991.1	Hnf1A	MA1991.1	8.04e-12	6.93e-09
245	MA1593.1	ZNF317	MA1593.1	1.29e-11	1.11e-08
246	MA0095.3	Yy1	MA0095.3	1.36e-11	1.17e-08
248	MA1571.1	TGIF2LX	MA1571.1	1.62e-11	1.39e-08
249	MA0606.2	Nfat5	MA0606.2	1.65e-11	1.42e-08
250	MA0691.1	TFAP4	MA0691.1	1.69e-11	1.46e-08
251	MA0480.2	Foxo1	MA0480.2	1.97e-11	1.69e-08
252	MA1501.1	HOXB7	MA1501.1	2.13e-11	1.83e-08
253	MA0850.1	FOXP3	MA0850.1	2.71e-11	2.34e-08
254	MA0078.2	Sox17	MA0078.2	2.8e-11	2.41e-08
255	MA1131.1	FOSL2::JUN	MA1131.1	3.55e-11	3.06e-08
256	MA1496.1	HOXA4	MA1496.1	4.5e-11	3.88e-08
257	MA1643.1	NFIB	MA1643.1	8.77e-11	7.56e-08
258	MA1127.1	FOSB::JUN	MA1127.1	9.42e-11	8.12e-08
259	MA0755.1	CUX2	MA0755.1	9.63e-11	8.31e-08
260	MA0090.3	TEAD1	MA0090.3	9.65e-11	8.32e-08
261	MA0803.1	TBX15	MA0803.1	1.06e-10	9.1e-08
262	MA0119.1	NFIC::TLX1	MA0119.1	1.08e-10	9.31e-08
20	MA1928.1 (BNC2)	STREME-1	1-VTGASTCAB	2.84e-56	9.51e-08
263	MA0071.1	RORA	MA0071.1	1.17e-10	1.01e-07
17	MA0037.4 (Gata3)	STREME-2	2-CAGATAA	1.53e-59	1.46e-07
264	MA1500.1	HOXB6	MA1500.1	2.15e-10	1.86e-07
265	MA0017.2	NR2F1	MA0017.2	2.25e-10	1.94e-07
266	MA1527.1	NFIC	MA1527.1	2.63e-10	2.27e-07
267	MA1139.1	FOSL2::JUNB	MA1139.1	3.28e-10	2.83e-07
268	MA0046.2	HNF1A	MA0046.2	3.88e-10	3.34e-07
269	MA0618.1	LBX1	MA0618.1	4.19e-10	3.62e-07
270	MA0893.2	GSX2	MA0893.2	7.14e-10	6.15e-07
271	MA0614.1	Foxj2	MA0614.1	1.01e-09	8.75e-07
272	MA0631.1	Six3	MA0631.1	1.3e-09	1.12e-06
37	MA1991.1 (Hnf1A)	STREME-3	3-ATCAAA	3.24e-38	1.27e-06
273	MA0591.1	Bach1::Mafk	MA0591.1	1.48e-09	1.27e-06
274	MA1119.1	SIX2	MA1119.1	2.16e-09	1.86e-06
275	MA1112.2	NR4A1	MA1112.2	2.33e-09	2.01e-06
276	MA1105.2	GRHL2	MA1105.2	2.47e-09	2.13e-06
278	MA1528.1	NFIX	MA1528.1	4.03e-09	3.47e-06
279	MA1118.1	SIX1	MA1118.1	7.73e-09	6.66e-06
280	MA0896.1	Hmx1	MA0896.1	9.92e-09	8.55e-06
281	MA0689.1	TBX20	MA0689.1	2.06e-08	1.78e-05
282	MA0093.3	USF1	MA0093.3	4.41e-08	3.8e-05
283	MA1111.1	NR2F2	MA1111.1	4.74e-08	4.08e-05
284	MA0152.2	Nfatc2	MA0152.2	5.3e-08	4.57e-05
285	MA0849.1	FOXO6	MA0849.1	5.75e-08	4.95e-05
286	MA0673.1	NKX2-8	MA0673.1	5.96e-08	5.13e-05
287	MA0468.1	DUX4	MA0468.1	6.85e-08	5.9e-05
288	MA1145.1	FOSL2::JUND	MA1145.1	6.91e-08	5.96e-05
289	MA1143.1	FOSL1::JUND	MA1143.1	7.09e-08	6.11e-05
290	MA0877.3	BARHL1	MA0877.3	1.04e-07	8.95e-05
291	MA0836.2	CEBPD	MA0836.2	1.25e-07	0.000108
292	MA0854.1	Alx1	MA0854.1	1.38e-07	0.000119
294	MA1709.1	ZIM3	MA1709.1	1.6e-07	0.000138
295	MA1562.1	SOX14	MA1562.1	1.61e-07	0.000139
296	MA0038.2	GFI1	MA0038.2	1.75e-07	0.000151
297	MA1126.1	FOS::JUN	MA1126.1	2.52e-07	0.000218
298	MA1567.2	Tbx6	MA1567.2	3.97e-07	0.000342
299	MA0807.1	TBX5	MA0807.1	4.91e-07	0.000423
300	MA0629.1	Rhox11	MA0629.1	5.44e-07	0.000469
301	MA1707.1	DMRTA1	MA1707.1	6.38e-07	0.00055
239	4-CAGTGAGCTG	STREME-4	4-CAGTGAGCTG	2.31e-12	0.000572
302	MA0853.1	Alx4	MA0853.1	7.61e-07	0.000656
303	MA1644.1	NFYC	MA1644.1	8.44e-07	0.000728
304	MA1478.1	DMRTA2	MA1478.1	9.72e-07	0.000837
314	MA1627.1 (Wt1)	MEME-5	CCCCWCCCCCMMNCC	4.21e-06	0.00089
305	MA0883.1	Dmbx1	MA0883.1	1.11e-06	0.000957
306	MA0783.1	PKNOX2	MA0783.1	1.13e-06	0.000978
307	MA0087.2	Sox5	MA0087.2	1.15e-06	0.000992
308	MA0831.3	TFE3	MA0831.3	1.38e-06	0.00119
25	MA0498.2 (MEIS1)	STREME-5	5-CTGWCAG	2.54e-51	0.00153
309	MA0809.2	TEAD4	MA0809.2	2.22e-06	0.00191
310	MA0698.1	ZBTB18	MA0698.1	2.59e-06	0.00223
311	MA2003.1	NKX2-4	MA2003.1	2.6e-06	0.00224
312	MA0595.1	SREBF1	MA0595.1	2.66e-06	0.00229
313	MA0092.1	Hand1::Tcf3	MA0092.1	2.83e-06	0.00244
315	MA0693.3	Vdr	MA0693.3	4.56e-06	0.00393
316	MA0620.3	MITF	MA0620.3	4.87e-06	0.0042
317	MA1150.1	RORB	MA1150.1	5.78e-06	0.00498
141	6-AGAAAA	STREME-6	6-AGAAAA	1.07e-22	0.00522
318	MA1618.1	Ptf1a	MA1618.1	6.12e-06	0.00528
319	MA0780.1	PAX3	MA0780.1	6.23e-06	0.00537
204	MA1627.1 (Wt1)	STREME-7	7-CCTCCCCCA	1.89e-15	0.00542
320	MA0141.3	ESRRB	MA0141.3	6.98e-06	0.00602
321	MA0840.1	Creb5	MA0840.1	7.46e-06	0.00643
322	MA0684.2	RUNX3	MA0684.2	8.09e-06	0.00697
323	MA1962.1	POU2F1::SOX2	MA1962.1	8.72e-06	0.00751
324	MA0852.2	FOXK1	MA0852.2	9.22e-06	0.00795
326	MA0672.1	NKX2-3	MA0672.1	1.06e-05	0.00911
277	8-TRATYA	STREME-8	8-TRATYA	2.97e-09	0.00982
328	MA1974.1	ZNF211	MA1974.1	1.3e-05	0.0112
329	MA0514.2	Sox3	MA0514.2	1.31e-05	0.0113
330	MA0610.1	DMRT3	MA0610.1	1.36e-05	0.0118
331	MA0599.1	KLF5	MA0599.1	1.49e-05	0.0128
332	MA1507.1	HOXD4	MA1507.1	1.55e-05	0.0134
333	MA0806.1	TBX4	MA0806.1	1.69e-05	0.0145
334	MA0467.2	Crx	MA0467.2	2.18e-05	0.0188
335	MA0656.1	JDP2	MA0656.1	2.21e-05	0.019
336	MA0132.2	PDX1	MA0132.2	2.26e-05	0.0195
337	MA0796.1	TGIF1	MA0796.1	2.78e-05	0.0239
338	MA0623.2	NEUROG1	MA0623.2	3e-05	0.0259
339	MA1980.1	ZNF418	MA1980.1	3.21e-05	0.0277
327	MA1125.1 (ZNF384)	MEME-6	YCTGTCTCAAAAMAA	1.28e-05	0.029
340	MA0688.1	TBX2	MA0688.1	3.43e-05	0.0295
341	MA1645.1	NKX2-2	MA1645.1	3.51e-05	0.0303
247	9-AATGTA	STREME-9	9-AATGTA	1.54e-11	0.0319
293	MA0592.3 (ESRRA)	STREME-10	10-AGGTCA	1.43e-07	0.0319
347	MA1715.1 (ZNF707)	STREME-11	11-GCCCAGCTCCTGA	0.0711	0.0335
42	MA1633.2 (BACH1)	STREME-12	12-AGTCAT	3.45e-37	0.037
342	MA1570.1	TFAP4	MA1570.1	4.71e-05	0.0406
343	MA0802.1	TBR1	MA0802.1	4.76e-05	0.0411
344	MA1503.1	HOXB9	MA1503.1	5.28e-05	0.0455
97	MA1632.1 (ATF2)	STREME-13	13-ATGAGGTR	6.8e-27	0.0712
152	14-AAGATG	STREME-14	14-AAGATG	2.71e-21	0.0738
150	MA1657.1 (ZNF652)	STREME-15	15-AGAGTT	2.54e-21	0.128

ESR lists

# ESR_open_xstreme %>% 
#  dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
#    arrange(.,EVALUE) %>% 
#    dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
#   # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
#   # dplyr::filter(., EVALUE<0.05) %>% 
#   dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
#   kable(., caption = "Enriched motifs in ESR open") %>%
#   kable_paper("striped", full_width = TRUE) %>%
#   kable_styling(full_width = FALSE, font_size = 16) %>%
#   scroll_box(height = "800px")

ESR_open_200xstreme %>% 
 dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
   arrange(.,EVALUE) %>% 
   dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
  # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  # dplyr::filter(., EVALUE<0.05) %>% 
  dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
  kable(., caption = "Enriched motifs in ESR open, 200bp") %>%
  kable_paper("striped", full_width = TRUE) %>%
  kable_styling(full_width = FALSE, font_size = 16) %>%
  scroll_box(height = "800px")

Enriched motifs in ESR open, 200bp
RANK	SIM_MOTIF	ALT_ID	ID	SEA_PVALUE	EVALUE
16	MA0490.2	JUNB	MA0490.2	3.44e-109	3e-106
3	GTGTGTGTGTGTGTG	MEME-1	GTGTGTGTGTGTGTG	4.65e-124	5e-101
18	MA0491.2	JUND	MA0491.2	1.66e-100	1.45e-97
19	MA1128.1	FOSL1::JUN	MA1128.1	2.7e-100	2.36e-97
20	MA0099.3	FOS::JUN	MA0099.3	1.43e-99	1.25e-96
22	MA0477.2	FOSL1	MA0477.2	3.12e-98	2.73e-95
23	MA1144.1	FOSL2::JUND	MA1144.1	7.01e-98	6.13e-95
24	MA0655.1	JDP2	MA0655.1	1.4e-95	1.22e-92
25	MA1138.1	FOSL2::JUNB	MA1138.1	1.5e-95	1.31e-92
26	MA1142.1	FOSL1::JUND	MA1142.1	2.53e-94	2.21e-91
27	MA1135.1	FOSB::JUNB	MA1135.1	1.2e-92	1.05e-89
29	MA1137.1	FOSL1::JUNB	MA1137.1	1.57e-89	1.37e-86
30	MA1988.1	Atf3	MA1988.1	7.68e-88	6.71e-85
32	MA1141.1	FOS::JUND	MA1141.1	1.73e-86	1.51e-83
34	MA0476.1	FOS	MA0476.1	1.87e-85	1.63e-82
35	MA1633.2	BACH1	MA1633.2	1.23e-84	1.08e-81
36	MA1130.1	FOSL2::JUN	MA1130.1	6.65e-82	5.81e-79
37	MA0841.1	NFE2	MA0841.1	4.39e-81	3.84e-78
38	MA0835.2	BATF3	MA0835.2	4.69e-79	4.1e-76
39	MA1134.1	FOS::JUNB	MA1134.1	9.62e-79	8.41e-76
40	MA1101.2	BACH2	MA1101.2	2e-74	1.75e-71
41	MA1132.1	JUN::JUNB	MA1132.1	7.45e-73	6.51e-70
42	MA1634.1	BATF	MA1634.1	8.57e-68	7.5e-65
43	MA0489.2	Jun	MA0489.2	3.62e-67	3.16e-64
44	MA1155.1	ZSCAN4	MA1155.1	2e-66	1.75e-63
45	MA0861.1	TP73	MA0861.1	8.68e-66	7.58e-63
46	MA0106.3	TP53	MA0106.3	1.28e-65	1.12e-62
47	MA0462.2	BATF::JUN	MA0462.2	1.39e-65	1.22e-62
48	MA0478.1	FOSL2	MA0478.1	3.93e-64	3.43e-61
126	MA1125.1 (ZNF384)	MEME-2	WWTTTTTKTWTTTTT	0.00125	5.3e-48
17	TGTGTRTGTGT	MEME-3	TGTGTRTGTGT	2.04e-106	4.2e-44
50	MA0073.1	RREB1	MA0073.1	5.61e-42	4.9e-39
51	MA0525.2	TP63	MA0525.2	8.72e-39	7.62e-36
88	MA1547.2 (PITX2)	MEME-4	AAAGTGCTGGGATTA	2.62e-08	1.9e-34
53	MA1108.2	MXI1	MA1108.2	4.61e-35	4.03e-32
55	MA1928.1	BNC2	MA1928.1	3.12e-34	2.73e-31
56	MA0006.1	Ahr::Arnt	MA0006.1	7.06e-34	6.17e-31
95	MA1596.1 (ZNF460)	MEME-6	GGGAGGCYGAGGYRG	1.34e-07	2.5e-27
127	MA1973.1 (ZKSCAN3)	MEME-10	TGTTGCCCAGGCTGG	0.00163	3.9e-24
125	GAGACRGRGTYTCRC	MEME-11	GAGACRGRGTYTCRC	0.000286	2.3e-23
57	MA0089.2	MAFG::NFE2L1	MA0089.2	2.88e-24	2.52e-21
58	MA0819.2	CLOCK	MA0819.2	1.17e-22	1.02e-19
59	MA0623.2	NEUROG1	MA0623.2	1.8e-21	1.57e-18
60	MA1974.1	ZNF211	MA1974.1	2.95e-21	2.58e-18
61	MA0259.1	ARNT::HIF1A	MA0259.1	2e-20	1.75e-17
12	MA1107.2 (KLF9)	MEME-7	GTRTGTGTGTG	1.21e-115	3.1e-17
62	MA1718.1	ZNF8	MA1718.1	1.09e-19	9.49e-17
63	MA0501.1	MAF::NFE2	MA0501.1	1.7e-18	1.49e-15
64	MA0626.1	Npas2	MA0626.1	2.84e-18	2.48e-15
9	TGTGTGTRTGTGTGT	MEME-13	TGTGTGTRTGTGTGT	2.59e-117	8e-15
2	TGTGTGYRTGTGTG	MEME-8	TGTGTGYRTGTGTG	1.63e-128	4e-14
28	MA1107.2 (KLF9)	MEME-9	TGTGTGTGTGTRTG	1.7e-92	6.6e-14
7	MA1107.2 (KLF9)	STREME-1	1-CACACACACACAC	1.04e-118	3.08e-13
33	2-CACACACACATRCAC	STREME-2	2-CACACACACATRCAC	4.87e-86	1.19e-12
66	MA0496.3	MAFK	MA0496.3	7.51e-15	6.56e-12
67	MA0678.1	OLIG2	MA0678.1	1.13e-14	9.86e-12
11	MA1107.2 (KLF9)	STREME-3	3-CACACACACACAD	6.75e-116	1.19e-10
68	MA0058.3	MAX	MA0058.3	1.53e-13	1.33e-10
21	4-CACACAYGCAC	STREME-4	4-CACACAYGCAC	2.38e-98	2.83e-10
10	MA1107.2 (KLF9)	MEME-5	ACACABACAYACA	5.94e-117	5e-10
4	MA1155.1 (ZSCAN4)	MEME-17	TGTGTRTGTGTGTG	1.09e-119	7.8e-10
8	MA1990.1 (Gli1)	STREME-5	5-CACACACCACACACA	3.91e-118	7.98e-10
69	MA1107.2	KLF9	MA1107.2	1.03e-12	9.03e-10
70	MA0622.1	Mlxip	MA0622.1	1.53e-12	1.34e-09
71	MA0817.1	BHLHE23	MA0817.1	1.82e-12	1.59e-09
15	MA0491.2 (JUND)	STREME-6	6-RATGASTCATY	1.04e-110	2.26e-09
1	7-CACACATACACAC	STREME-7	7-CACACATACACAC	2.85e-143	3.25e-09
72	MA0147.3	MYC	MA0147.3	1.07e-11	9.33e-09
73	MA0849.1	FOXO6	MA0849.1	1.43e-11	1.25e-08
74	MA0818.2	BHLHE22	MA0818.2	1.58e-11	1.38e-08
76	MA1124.1	ZNF24	MA1124.1	3.75e-11	3.28e-08
77	MA0825.1	MNT	MA0825.1	4.4e-11	3.85e-08
78	MA1560.1	SOHLH2	MA1560.1	5.35e-11	4.68e-08
75	YGCCTGTARTCCCAG	MEME-15	YGCCTGTARTCCCAG	2.71e-11	9.9e-08
79	MA1493.1	HES6	MA1493.1	1.41e-10	1.23e-07
6	TGTGTGGTGTGTGTG	MEME-12	TGTGTGGTGTGTGTG	5.3e-119	1.6e-07
80	MA0059.1	MAX::MYC	MA0059.1	2.88e-10	2.52e-07
81	MA0608.1	Creb3l2	MA0608.1	4.21e-10	3.68e-07
82	MA0607.2	BHLHA15	MA0607.2	4.67e-10	4.08e-07
83	MA0150.2	Nfe2l2	MA0150.2	9.13e-10	7.98e-07
84	MA0804.1	TBX19	MA0804.1	2.58e-09	2.26e-06
13	8-CAYRCACAC	STREME-8	8-CAYRCACAC	2.99e-114	3.22e-06
85	MA0827.1	OLIG3	MA0827.1	5.24e-09	4.58e-06
86	MA1606.1	Foxf1	MA1606.1	1.85e-08	1.62e-05
87	MA1464.1	ARNT2	MA1464.1	2.12e-08	1.86e-05
89	MA0689.1	TBX20	MA0689.1	3.09e-08	2.7e-05
90	MA0826.1	OLIG1	MA0826.1	4.67e-08	4.08e-05
92	MA0004.1	Arnt	MA0004.1	5.2e-08	4.55e-05
31	MA1974.1 (ZNF211)	STREME-9	9-MCACACACCACAC	5.48e-87	5.64e-05
93	MA0162.4	EGR1	MA0162.4	7.58e-08	6.63e-05
5	GTGTGTATGTGTG	MEME-14	GTGTGTATGTGTG	2.89e-119	7.1e-05
94	MA1106.1	HIF1A	MA1106.1	8.34e-08	7.29e-05
96	MA0649.1	HEY2	MA0649.1	1.44e-07	0.000126
97	MA0871.2	TFEC	MA0871.2	1.52e-07	0.000133
98	MA1487.2	FOXE1	MA1487.2	1.59e-07	0.000139
99	MA0627.2	POU2F3	MA0627.2	1.87e-07	0.000163
100	MA0472.2	EGR2	MA0472.2	2.1e-07	0.000184
101	MA0047.3	FOXA2	MA0047.3	2.4e-07	0.00021
102	MA1990.1	Gli1	MA1990.1	3.8e-07	0.000332
104	MA1559.1	SNAI3	MA1559.1	8.67e-07	0.000758
129	TGTGTGGTGTGTGTG	MEME-16	TGTGTGGTGTGTGTG	2.72	0.00077
105	MA0823.1	HEY1	MA0823.1	1.03e-06	9e-04
14	10-ATGTGTGTG	STREME-10	10-ATGTGTGTG	7.72e-113	0.00165
106	MA1103.2	FOXK2	MA1103.2	2.06e-06	0.0018
107	MA1115.1	POU5F1	MA1115.1	2.31e-06	0.00202
108	MA0464.2	BHLHE40	MA0464.2	2.53e-06	0.00221
109	MA0616.2	HES2	MA0616.2	2.73e-06	0.00239
110	MA0836.2	CEBPD	MA0836.2	3.47e-06	0.00304
111	MA0033.2	FOXL1	MA0033.2	3.88e-06	0.00339
52	MA1108.2 (MXI1)	STREME-11	11-TACACATG	1.09e-35	0.00484
112	MA0698.1	ZBTB18	MA0698.1	6.68e-06	0.00584
113	MA1618.1	Ptf1a	MA1618.1	1.15e-05	0.0101
114	MA0461.2	Atoh1	MA0461.2	1.3e-05	0.0113
115	MA0030.1	FOXF2	MA0030.1	1.41e-05	0.0123
116	MA0847.3	FOXD2	MA0847.3	1.44e-05	0.0126
117	MA0632.2	TCFL5	MA0632.2	1.79e-05	0.0156
118	MA1491.2	GLI3	MA1491.2	1.98e-05	0.0173
119	MA0615.1	Gmeb1	MA0615.1	2.43e-05	0.0213
120	MA0845.1	FOXB1	MA0845.1	2.78e-05	0.0243
121	MA0148.4	FOXA1	MA0148.4	4.09e-05	0.0357
122	MA0009.2	TBXT	MA0009.2	4.17e-05	0.0364
123	MA0646.1	GCM1	MA0646.1	4.65e-05	0.0406
124	MA0733.1	EGR4	MA0733.1	5.68e-05	0.0496
91	12-CGAGTGATCCGCC	STREME-12	12-CGAGTGATCCGCC	4.76e-08	0.0562
54	13-ACACAGG	STREME-13	13-ACACAGG	9.1e-35	0.0565
49	14-ACACAY	STREME-14	14-ACACAY	4.01e-43	0.0572
65	MA1601.2 (ZNF75D)	STREME-15	15-GGCATGCCCACAGT	1.9e-16	4.36
128	MA0052.4 (MEF2A)	STREME-16	16-TATTTTTAGWA	0.00293	6.41
103	MA1964.1 (SMAD2)	STREME-17	17-CCCGTCTGGGAAGT	6.42e-07	17

# ESR_close_xstreme %>% 
#   dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
#   arrange(.,EVALUE) %>%
#    dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
#   # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
#   # dplyr::filter(., EVALUE<0.05) %>% 
#   kable(., caption = "Enriched motifs  ESR close") %>%
#   kable_paper("striped", full_width = TRUE) %>%
#   kable_styling(full_width = FALSE, font_size = 16) %>%
#   scroll_box(height = "800px")

ESR_close_200xstreme %>% 
  dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
  arrange(.,EVALUE) %>%
   dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
  # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  # dplyr::filter(., EVALUE<0.05) %>% 
  kable(., caption = "Enriched motifs  ESR close 200bp") %>%
  kable_paper("striped", full_width = TRUE) %>%
  kable_styling(full_width = FALSE, font_size = 16) %>%
  scroll_box(height = "800px")

Enriched motifs ESR close 200bp
RANK	SIM_MOTIF	ALT_ID	ID	SEA_PVALUE	EVALUE
48	MA1723.1 (PRDM9)	MEME-1	YCCCYMHYCCCWSCY	6.89e-56	6.6e-96
10	MA1653.1	ZNF148	MA1653.1	5.37e-97	4.67e-94
11	MA0774.1	MEIS2	MA0774.1	1.53e-96	1.33e-93
13	MA1961.1	PATZ1	MA1961.1	1.85e-89	1.6e-86
14	MA1959.1	KLF7	MA1959.1	4.84e-89	4.2e-86
15	MA1630.2	ZNF281	MA1630.2	1.63e-87	1.42e-84
16	MA0742.2	KLF12	MA0742.2	1.32e-86	1.14e-83
18	MA0493.2	KLF1	MA0493.2	4.38e-86	3.8e-83
20	MA1511.2	KLF10	MA1511.2	9.52e-85	8.26e-82
21	MA0685.2	SP4	MA0685.2	1.29e-83	1.12e-80
23	MA0599.1	KLF5	MA0599.1	7.72e-79	6.7e-76
24	MA1643.1	NFIB	MA1643.1	1.72e-78	1.49e-75
25	MA1522.1	MAZ	MA1522.1	3.2e-78	2.78e-75
26	MA0740.2	KLF14	MA0740.2	3.33e-78	2.89e-75
27	MA0753.2	ZNF740	MA0753.2	2.09e-77	1.81e-74
28	MA0079.5	SP1	MA0079.5	5.56e-77	4.83e-74
29	MA1965.1	SP5	MA1965.1	6.63e-75	5.76e-72
30	MA0741.1	KLF16	MA0741.1	4.79e-71	4.16e-68
31	MA0516.3	SP2	MA0516.3	1.55e-69	1.35e-66
32	MA0746.2	SP3	MA0746.2	6.08e-69	5.27e-66
33	MA0119.1	NFIC::TLX1	MA0119.1	3.72e-68	3.23e-65
34	MA1981.1	ZNF530	MA1981.1	4.54e-67	3.94e-64
35	MA1650.1	ZBTB14	MA1650.1	4.63e-67	4.02e-64
37	MA1527.1	NFIC	MA1527.1	3.5e-65	3.04e-62
38	MA0162.4	EGR1	MA0162.4	1.69e-64	1.47e-61
39	MA1528.1	NFIX	MA1528.1	3.94e-64	3.43e-61
40	MA1713.1	ZNF610	MA1713.1	1.51e-63	1.31e-60
41	MA1564.1	SP9	MA1564.1	5.21e-63	4.52e-60
42	MA1512.1	KLF11	MA1512.1	3.15e-61	2.73e-58
45	MA1548.1	PLAGL2	MA1548.1	1.17e-58	1.01e-55
47	MA1578.1	VEZF1	MA1578.1	2.76e-58	2.39e-55
50	MA1627.1	Wt1	MA1627.1	1.11e-54	9.64e-52
51	MA0597.2	THAP1	MA0597.2	8.31e-54	7.21e-51
52	MA1515.1	KLF2	MA1515.1	5.35e-52	4.64e-49
53	MA1102.2	CTCFL	MA1102.2	2.28e-51	1.98e-48
54	MA1615.1	Plagl1	MA1615.1	2.09e-49	1.81e-46
55	MA1514.1	KLF17	MA1514.1	2.12e-46	1.84e-43
56	MA0039.4	KLF4	MA0039.4	4.92e-46	4.27e-43
57	MA0155.1	INSM1	MA0155.1	1.28e-45	1.11e-42
58	MA0775.1	MEIS3	MA0775.1	1.89e-45	1.64e-42
59	MA1107.2	KLF9	MA1107.2	2.8e-45	2.43e-42
96	MA1723.1 (PRDM9)	MEME-2	GGSAGRRGSARGGRS	5.41e-27	3.5e-42
60	MA1976.1	ZNF320	MA1976.1	5.63e-45	4.89e-42
61	MA1599.1	ZNF682	MA1599.1	9.56e-44	8.29e-41
63	MA1986.1	ZNF692	MA1986.1	3.32e-43	2.88e-40
64	MA0810.1	TFAP2A	MA0810.1	3.79e-43	3.29e-40
65	MA0672.1	NKX2-3	MA0672.1	4.82e-41	4.18e-38
66	MA1631.1	ASCL1	MA1631.1	7.2e-40	6.25e-37
67	MA1596.1	ZNF460	MA1596.1	9.04e-40	7.84e-37
68	MA1712.1	ZNF454	MA1712.1	2.06e-39	1.79e-36
69	MA0146.2	Zfx	MA0146.2	2.86e-39	2.48e-36
70	MA1516.1	KLF3	MA1516.1	4.56e-36	3.96e-33
71	MA0739.1	Hic1	MA0739.1	6.33e-36	5.49e-33
72	MA0633.2	Twist2	MA0633.2	1.4e-35	1.21e-32
73	MA0747.1	SP8	MA0747.1	1.84e-35	1.6e-32
74	MA2003.1	NKX2-4	MA2003.1	9.66e-35	8.38e-32
75	MA1997.1	Olig2	MA1997.1	1.99e-34	1.73e-31
76	MA0131.2	HINFP	MA0131.2	9.49e-34	8.24e-31
77	MA1719.1	ZNF816	MA1719.1	4.66e-33	4.04e-30
78	MA0504.1	NR2C2	MA0504.1	2.14e-32	1.86e-29
79	MA0797.1	TGIF2	MA0797.1	3.25e-32	2.82e-29
80	MA0830.2	TCF4	MA0830.2	5.64e-32	4.9e-29
81	MA1993.1	Neurod2	MA1993.1	1.08e-31	9.35e-29
82	MA1723.1	PRDM9	MA1723.1	1.3e-31	1.13e-28
83	MA1721.1	ZNF93	MA1721.1	2.53e-31	2.19e-28
84	MA0522.3	TCF3	MA0522.3	2.9e-31	2.51e-28
85	MA0528.2	ZNF263	MA0528.2	3.11e-31	2.7e-28
86	MA0471.2	E2F6	MA0471.2	7.3e-31	6.34e-28
87	MA0498.2	MEIS1	MA0498.2	1.66e-30	1.44e-27
88	MA0524.2	TFAP2C	MA0524.2	2.38e-30	2.07e-27
89	MA1710.1	ZNF257	MA1710.1	3.01e-30	2.61e-27
90	MA0872.1	TFAP2A	MA0872.1	1.01e-29	8.79e-27
91	MA0521.2	Tcf12	MA0521.2	1.47e-29	1.27e-26
92	MA0812.1	TFAP2B	MA0812.1	1.68e-29	1.45e-26
93	MA0738.1	HIC2	MA0738.1	4.56e-29	3.96e-26
94	MA0803.1	TBX15	MA0803.1	2.34e-28	2.03e-25
95	MA0783.1	PKNOX2	MA0783.1	4.67e-28	4.06e-25
97	MA1517.1	KLF6	MA1517.1	7.85e-27	6.81e-24
98	MA0003.4	TFAP2A	MA0003.4	1.05e-26	9.13e-24
99	MA1648.1	TCF12	MA1648.1	2.4e-26	2.08e-23
100	MA0751.1	ZIC4	MA0751.1	2.41e-26	2.1e-23
101	MA0130.1	ZNF354C	MA0130.1	9.45e-26	8.2e-23
102	MA0814.2	TFAP2C	MA0814.2	1.06e-25	9.2e-23
103	MA1987.1	ZNF701	MA1987.1	3.52e-25	3.06e-22
104	MA1728.1	ZNF549	MA1728.1	7.69e-25	6.67e-22
105	MA0811.1	TFAP2B	MA0811.1	1.09e-24	9.5e-22
106	MA1635.1	BHLHE22	MA1635.1	1.32e-24	1.14e-21
107	MA1600.1	ZNF684	MA1600.1	4.37e-24	3.79e-21
108	MA0506.2	Nrf1	MA0506.2	5.32e-24	4.62e-21
109	MA0691.1	TFAP4	MA0691.1	1.34e-23	1.16e-20
110	MA1619.1	Ptf1A	MA1619.1	1.35e-23	1.17e-20
3	MA0774.1 (MEIS2)	STREME-1	1-RGCTGTCA	1.96e-124	2.27e-20
111	MA0673.1	NKX2-8	MA0673.1	3.16e-23	2.74e-20
112	MA0499.2	MYOD1	MA0499.2	3.89e-23	3.37e-20
113	MA0734.3	Gli2	MA0734.3	4.77e-23	4.14e-20
114	MA0733.1	EGR4	MA0733.1	1.2e-22	1.04e-19
115	MA0670.1	NFIA	MA0670.1	2.19e-22	1.9e-19
116	MA1979.1	ZNF416	MA1979.1	3.22e-22	2.8e-19
117	MA0796.1	TGIF1	MA0796.1	4.8e-22	4.17e-19
118	MA1656.1	ZNF449	MA1656.1	5.33e-22	4.63e-19
119	MA1982.1	ZNF574	MA1982.1	2.75e-21	2.39e-18
120	MA1641.1	MYF5	MA1641.1	4.04e-21	3.51e-18
121	MA0736.1	GLIS2	MA0736.1	6.15e-21	5.34e-18
122	MA1587.1	ZNF135	MA1587.1	1.3e-20	1.13e-17
265	MA1125.1 (ZNF384)	MEME-3	TTTTTTTTTTTTTTT	0.964	1.7e-17
123	MA0665.1	MSC	MA0665.1	3.59e-20	3.12e-17
124	MA1629.1	Zic2	MA1629.1	1.11e-19	9.63e-17
125	MA0816.1	Ascl2	MA0816.1	1.32e-19	1.14e-16
126	MA0807.1	TBX5	MA0807.1	1.32e-19	1.15e-16
127	MA1628.1	Zic1::Zic2	MA1628.1	1.74e-19	1.51e-16
128	MA0258.2	ESR2	MA0258.2	1.77e-19	1.54e-16
19	CAGCYCWG	MEME-4	CAGCYCWG	4.56e-86	4.6e-16
129	MA0815.1	TFAP2C	MA0815.1	8.29e-19	7.2e-16
130	MA0500.2	MYOG	MA0500.2	8.84e-19	7.68e-16
131	MA0671.1	NFIX	MA0671.1	9.85e-19	8.55e-16
132	MA0048.2	NHLH1	MA0048.2	1.02e-18	8.87e-16
133	MA0694.1	ZBTB7B	MA0694.1	1.03e-18	8.92e-16
134	MA1472.2	Bhlha15	MA1472.2	1.63e-18	1.41e-15
135	MA1571.1	TGIF2LX	MA1571.1	1.64e-18	1.42e-15
137	MA0145.2	Tfcp2l1	MA0145.2	4.11e-18	3.57e-15
138	MA1972.1	ZFP14	MA1972.1	5.69e-18	4.94e-15
139	MA1637.1	EBF3	MA1637.1	3.72e-17	3.23e-14
140	MA2002.1	Zfp335	MA2002.1	3.97e-17	3.44e-14
141	MA1100.2	ASCL1	MA1100.2	5.18e-17	4.5e-14
142	MA1122.1	TFDP1	MA1122.1	9.01e-17	7.82e-14
143	MA0104.4	MYCN	MA0104.4	3.47e-16	3.01e-13
144	MA0071.1	RORA	MA0071.1	3.57e-16	3.1e-13
145	MA1535.1	NR2C1	MA1535.1	3.82e-16	3.32e-13
146	MA0745.2	SNAI2	MA0745.2	8.78e-16	7.62e-13
147	MA0161.2	NFIC	MA0161.2	9.13e-16	7.93e-13
2	MA0597.2 (THAP1)	STREME-2	2-CCCTGCCA	1.3e-125	2.38e-12
148	MA1973.1	ZKSCAN3	MA1973.1	4.47e-15	3.88e-12
22	MA1548.1 (PLAGL2)	STREME-3	3-WGGGCCCW	4.52e-83	4.85e-12
149	MA1730.1	ZNF708	MA1730.1	6.01e-15	5.21e-12
150	MA0750.2	ZBTB7A	MA0750.2	6.86e-15	5.95e-12
151	MA1990.1	Gli1	MA1990.1	1.26e-14	1.09e-11
152	MA0805.1	TBX1	MA0805.1	1.67e-14	1.45e-11
153	MA1114.1	PBX3	MA1114.1	1.96e-14	1.7e-11
155	MA0766.2	GATA5	MA0766.2	4.6e-14	3.99e-11
5	MA1981.1 (ZNF530)	STREME-4	4-WGGGCCTG	3.44e-118	5.44e-11
7	MA1630.2 (ZNF281)	STREME-5	5-CCCCWCCC	1.93e-110	8.3e-11
156	MA0092.1	Hand1::Tcf3	MA0092.1	1.19e-13	1.03e-10
157	MA1985.1	ZNF669	MA1985.1	2.47e-13	2.15e-10
158	MA1567.2	Tbx6	MA1567.2	2.8e-13	2.43e-10
159	MA0649.1	HEY2	MA0649.1	3.16e-13	2.75e-10
160	MA0017.2	NR2F1	MA0017.2	4.25e-13	3.69e-10
161	MA0084.1	SRY	MA0084.1	4.54e-13	3.95e-10
162	MA0073.1	RREB1	MA0073.1	5.36e-13	4.65e-10
163	MA0626.1	Npas2	MA0626.1	6.98e-13	6.06e-10
164	MA0676.1	Nr2e1	MA0676.1	7.96e-13	6.91e-10
165	MA0472.2	EGR2	MA0472.2	8.64e-13	7.5e-10
1	MA1979.1 (ZNF416)	STREME-6	6-SAGCCCWG	2.43e-129	8.57e-10
166	MA0782.2	PKNOX1	MA0782.2	1.04e-12	9e-10
167	MA0154.4	EBF1	MA0154.4	1.51e-12	1.31e-09
168	MA0767.1	GCM2	MA0767.1	2.2e-12	1.91e-09
169	MA1604.1	Ebf2	MA1604.1	2.46e-12	2.13e-09
170	MA0163.1	PLAG1	MA0163.1	3.03e-12	2.63e-09
171	MA1109.1	NEUROD1	MA1109.1	4.52e-12	3.93e-09
172	MA1572.1	TGIF2LY	MA1572.1	6.09e-12	5.29e-09
173	MA1531.1	NR1D1	MA1531.1	1.1e-11	9.55e-09
174	MA1110.2	Nr1H4	MA1110.2	1.12e-11	9.68e-09
175	MA0697.2	Zic3	MA0697.2	1.14e-11	9.9e-09
176	MA0147.3	MYC	MA0147.3	1.55e-11	1.34e-08
177	MA0748.2	YY2	MA0748.2	1.62e-11	1.4e-08
178	MA0596.1	SREBF2	MA0596.1	2.8e-11	2.43e-08
179	MA1726.1	ZNF331	MA1726.1	6.21e-11	5.39e-08
180	MA0664.1	MLXIPL	MA0664.1	6.96e-11	6.04e-08
181	MA1153.1	Smad4	MA1153.1	9.41e-11	8.17e-08
182	MA0720.1	Shox2	MA0720.1	1.67e-10	1.45e-07
9	MA1565.1 (TBX18)	STREME-7	7-CACCTCY	4.08e-99	1.56e-07
183	MA0139.1	CTCF	MA0139.1	1.89e-10	1.64e-07
264	TGTGTGTGTGTGTGT	MEME-5	TGTGTGTGTGTGTGT	0.414	1.7e-07
184	MA0159.1	RARA::RXRA	MA0159.1	2.31e-10	2.01e-07
8	8-CWGSCWG	STREME-8	8-CWGSCWG	2.89e-99	2.08e-07
185	MA0821.2	HES5	MA0821.2	3.28e-10	2.84e-07
186	MA1570.1	TFAP4	MA1570.1	4.24e-10	3.68e-07
187	MA1731.1	ZNF768	MA1731.1	4.42e-10	3.84e-07
188	MA1108.2	MXI1	MA1108.2	5.27e-10	4.58e-07
189	MA1583.1	ZFP57	MA1583.1	6.68e-10	5.8e-07
190	MA0737.1	GLIS3	MA0737.1	1.21e-09	1.05e-06
191	MA1964.1	SMAD2	MA1964.1	1.3e-09	1.12e-06
192	MA0831.3	TFE3	MA0831.3	1.36e-09	1.18e-06
46	MA1643.1 (NFIB)	STREME-9	9-CTTGGCAC	1.56e-58	1.19e-06
62	MA1631.1 (ASCL1)	MEME-7	RGCWGCWGGGVSWGS	3.01e-43	2.1e-06
193	MA0006.1	Ahr::Arnt	MA0006.1	2.85e-09	2.47e-06
194	MA0820.1	FIGLA	MA0820.1	3.51e-09	3.05e-06
195	MA0723.2	VAX2	MA0723.2	3.52e-09	3.06e-06
196	MA0035.4	GATA1	MA0035.4	5.02e-09	4.35e-06
197	MA0674.1	NKX6-1	MA0674.1	5.41e-09	4.69e-06
199	MA0668.2	Neurod2	MA0668.2	6.49e-09	5.64e-06
200	MA0014.3	PAX5	MA0014.3	8.11e-09	7.04e-06
201	MA1727.1	ZNF417	MA1727.1	8.13e-09	7.05e-06
202	MA0806.1	TBX4	MA0806.1	8.68e-09	7.53e-06
203	MA0695.1	ZBTB7C	MA0695.1	8.81e-09	7.65e-06
204	MA0704.1	Lhx4	MA0704.1	1.18e-08	1.02e-05
205	MA0027.2	EN1	MA0027.2	1.39e-08	1.2e-05
206	MA1569.1	TFAP2E	MA1569.1	1.47e-08	1.28e-05
17	MA1630.2 (ZNF281)	MEME-6	GGGGGMDGGGC	1.8e-86	1.3e-05
207	MA1966.1	TFAP4::ETV1	MA1966.1	2.24e-08	1.94e-05
208	MA1642.1	NEUROG2	MA1642.1	2.32e-08	2.01e-05
12	MA0146.2 (Zfx)	STREME-10	10-CAGGCCW	1.7e-96	2.4e-05
209	MA0832.1	Tcf21	MA0832.1	4.18e-08	3.63e-05
210	MA0722.1	VAX1	MA0722.1	5.16e-08	4.48e-05
211	MA0730.1	RARA	MA0730.1	6.82e-08	5.92e-05
212	MA1103.2	FOXK2	MA1103.2	6.96e-08	6.05e-05
213	MA0865.2	E2F8	MA0865.2	7.82e-08	6.79e-05
214	MA0769.2	TCF7	MA0769.2	7.86e-08	6.82e-05
215	MA1574.1	THRB	MA1574.1	8.96e-08	7.77e-05
216	MA1996.1	Nr1H2	MA1996.1	1.15e-07	9.98e-05
217	MA0718.1	RAX	MA0718.1	1.2e-07	0.000104
218	MA0698.1	ZBTB18	MA0698.1	1.25e-07	0.000108
219	MA0511.2	RUNX2	MA0511.2	1.59e-07	0.000138
43	MA1994.1 (Nkx2-1)	STREME-11	11-CCACTTGAS	1.97e-60	0.00015
220	MA1558.1	SNAI1	MA1558.1	1.98e-07	0.000172
221	MA1941.1	ETV2::FIGLA	MA1941.1	2.21e-07	0.000192
222	MA0716.1	PRRX1	MA0716.1	2.77e-07	0.00024
223	MA1606.1	Foxf1	MA1606.1	2.84e-07	0.000246
224	MA0882.1	DLX6	MA0882.1	2.95e-07	0.000256
225	MA0903.1	HOXB3	MA0903.1	3.16e-07	0.000274
226	MA0885.2	Dlx2	MA0885.2	3.35e-07	0.000291
227	MA1104.2	GATA6	MA1104.2	3.6e-07	0.000312
228	MA0648.1	GSC	MA0648.1	5.25e-07	0.000456
229	MA0801.1	MGA	MA0801.1	5.84e-07	0.000507
230	MA1715.1	ZNF707	MA1715.1	7.08e-07	0.000615
231	MA0692.1	TFEB	MA0692.1	1.12e-06	0.000973
232	MA1498.2	HOXA7	MA1498.2	1.27e-06	0.0011
233	MA0595.1	SREBF1	MA0595.1	1.37e-06	0.00119
234	MA0858.1	Rarb	MA0858.1	1.46e-06	0.00127
235	MA1565.1	TBX18	MA1565.1	1.66e-06	0.00144
236	MA1652.1	ZKSCAN5	MA1652.1	2.18e-06	0.0019
237	MA1566.2	TBX3	MA1566.2	2.31e-06	0.002
238	MA0643.1	Esrrg	MA0643.1	2.7e-06	0.00234
239	MA1480.1	DPRX	MA1480.1	2.95e-06	0.00256
240	MA0808.1	TEAD3	MA0808.1	3.43e-06	0.00298
241	MA1152.1	SOX15	MA1152.1	3.83e-06	0.00332
242	MA0696.1	ZIC1	MA0696.1	4.14e-06	0.00359
243	MA0667.1	MYF6	MA0667.1	4.38e-06	0.0038
244	MA1969.1	THRA	MA1969.1	4.53e-06	0.00393
245	MA0630.1	SHOX	MA0630.1	5.81e-06	0.00505
154	12-GCTCTCTTCA	STREME-12	12-GCTCTCTTCA	2.01e-14	0.00512
246	MA0065.2	Pparg::Rxra	MA0065.2	6.01e-06	0.00521
247	MA0879.2	DLX1	MA0879.2	6.98e-06	0.00606
248	MA0899.1	HOXA10	MA0899.1	7.27e-06	0.00631
249	MA0068.2	PAX4	MA0068.2	8.03e-06	0.00697
250	MA1593.1	ZNF317	MA1593.1	1.01e-05	0.00881
4	MA0734.3 (Gli2)	STREME-13	13-CWCCCWG	3.17e-118	0.00907
251	MA1581.1	ZBTB6	MA1581.1	1.08e-05	0.00935
252	MA0116.1	Znf423	MA0116.1	1.74e-05	0.0151
253	MA0721.1	UNCX	MA0721.1	1.84e-05	0.0159
254	MA1620.1	Ptf1A	MA1620.1	2.93e-05	0.0254
198	14-GCAGACTTA	STREME-14	14-GCAGACTTA	6e-09	0.0256
49	15-CCTCTCCA	STREME-15	15-CCTCTCCA	2.89e-55	0.0259
255	MA1476.2	Dlx5	MA1476.2	3.01e-05	0.0261
256	MA0056.2	MZF1	MA0056.2	3.12e-05	0.0271
257	MA0004.1	Arnt	MA0004.1	3.25e-05	0.0282
258	MA0033.2	FOXL1	MA0033.2	3.26e-05	0.0283
259	MA0093.3	USF1	MA0093.3	3.35e-05	0.0291
260	MA0675.1	NKX6-2	MA0675.1	3.6e-05	0.0312
261	MA0149.1	EWSR1-FLI1	MA0149.1	4.06e-05	0.0353
6	MA0783.1 (PKNOX2)	STREME-16	16-STGNCAS	4.18e-113	0.0453
262	MA0650.3	Hoxa13	MA0650.3	5.44e-05	0.0472
36	MA1644.1 (NFYC)	STREME-17	17-CCCATCA	2.43e-66	0.0539
44	MA0697.2 (Zic3)	STREME-18	18-SAGSAGG	2.63e-60	0.794
136	19-GCTTATAGATAAAAC	STREME-19	19-GCTTATAGATAAAAC	2.34e-18	2.19
263	MA0069.1 (PAX6)	STREME-20	20-TACTCAAGCCTCA	0.000149	17.2

# ESR_OC_xstreme %>% 
#   dplyr::select(SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
#   arrange(.,EVALUE) %>%
#    dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
#   # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
#   # dplyr::filter(., EVALUE<0.05) %>% 
#   kable(., caption = "Enriched motifs  in ESR OC") %>%
#   kable_paper("striped", full_width = TRUE) %>%
#   kable_styling(full_width = FALSE, font_size = 16) %>%
#   scroll_box(height = "800px")

ESR_opcl_xstreme %>% 
  dplyr::select(SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
  arrange(.,EVALUE) %>%
   dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
  # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  # dplyr::filter(., EVALUE<0.05) %>% 
  kable(., caption = "Enriched motifs  in ESR opcl") %>%
  kable_paper("striped", full_width = TRUE) %>%
  kable_styling(full_width = FALSE, font_size = 16) %>%
  scroll_box(height = "800px")

Enriched motifs in ESR opcl
SIM_MOTIF	ALT_ID	ID	SEA_PVALUE	EVALUE
MA1125.1 (ZNF384)	MEME-1	AARWADAAAAAWAWW	1.73e-11	1e-13
MA1107.2 (KLF9)	MEME-2	GTGTGTRTGTGTGTG	0.075	3e-07
MA0789.1	POU3F4	MA0789.1	5.29e-08	4.48e-05
MA0787.1	POU3F2	MA0787.1	3.21e-07	0.000272
MA0063.2	NKX2-5	MA0063.2	4.29e-07	0.000363
MA0676.1	Nr2e1	MA0676.1	4.7e-07	0.000397
MA0507.2	POU2F2	MA0507.2	7.47e-06	0.00632
MA0792.1	POU5F1B	MA0792.1	8.05e-06	0.00681
MA1471.1	BARX2	MA1471.1	8.51e-06	0.0072
MA0788.1	POU3F3	MA0788.1	1.59e-05	0.0135
MA0913.2	HOXD9	MA0913.2	4.43e-05	0.0375
MA0790.1	POU4F1	MA0790.1	4.52e-05	0.0383
MA0465.2	CDX2	MA0465.2	4.76e-05	0.0403
1-AWATATWT	STREME-1	1-AWATATWT	7.55e-06	0.372
2-CCAAGCTACA	STREME-2	2-CCAAGCTACA	3.57e-10	1.38
MA1589.1 (ZNF140)	STREME-3	3-AATTCCATTCTCHMW	9.86e-13	3

ESR_clop_xstreme %>% 
  dplyr::select(SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
  arrange(.,EVALUE) %>%
   dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
  # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  # dplyr::filter(., EVALUE<0.05) %>% 
  kable(., caption = "Enriched motifs  in ESR clop") %>%
  kable_paper("striped", full_width = TRUE) %>%
  kable_styling(full_width = FALSE, font_size = 16) %>%
  scroll_box(height = "800px")

Enriched motifs in ESR clop
SIM_MOTIF	ALT_ID	ID	SEA_PVALUE	EVALUE
MA1988.1	Atf3	MA1988.1	3.21e-205	2.77e-202
MA0489.2	Jun	MA0489.2	1.54e-198	1.33e-195
MA1134.1	FOS::JUNB	MA1134.1	3.83e-198	3.31e-195
MA1138.1	FOSL2::JUNB	MA1138.1	2.87e-195	2.48e-192
MA1634.1	BATF	MA1634.1	3.04e-194	2.62e-191
MA1141.1	FOS::JUND	MA1141.1	1.69e-193	1.46e-190
MA0099.3	FOS::JUN	MA0099.3	1.96e-192	1.7e-189
MA1130.1	FOSL2::JUN	MA1130.1	1.98e-192	1.71e-189
MA0462.2	BATF::JUN	MA0462.2	3.72e-191	3.22e-188
MA0477.2	FOSL1	MA0477.2	5.43e-189	4.7e-186
MA1135.1	FOSB::JUNB	MA1135.1	7.75e-189	6.69e-186
MA0835.2	BATF3	MA0835.2	6.81e-188	5.89e-185
MA1144.1	FOSL2::JUND	MA1144.1	3.96e-187	3.42e-184
MA1633.2	BACH1	MA1633.2	1.72e-186	1.49e-183
MA1128.1	FOSL1::JUN	MA1128.1	2.58e-185	2.23e-182
MA0491.2	JUND	MA0491.2	1.82e-184	1.57e-181
MA0476.1	FOS	MA0476.1	3.82e-181	3.3e-178
MA0490.2	JUNB	MA0490.2	2.92e-180	2.52e-177
MA1137.1	FOSL1::JUNB	MA1137.1	3.75e-180	3.24e-177
MA0478.1	FOSL2	MA0478.1	8.72e-178	7.53e-175
MA0655.1	JDP2	MA0655.1	4.99e-161	4.32e-158
MA1928.1	BNC2	MA1928.1	5.57e-161	4.81e-158
MA1101.2	BACH2	MA1101.2	1.66e-160	1.44e-157
MA1142.1	FOSL1::JUND	MA1142.1	3.78e-156	3.27e-153
MA1132.1	JUN::JUNB	MA1132.1	3.59e-147	3.1e-144
MA0841.1	NFE2	MA0841.1	4.31e-123	3.73e-120
MA1134.1 (FOS::JUNB)	MEME-1	RRTGACTCAKV	1.2e-197	5.1e-112
MA0089.2	MAFG::NFE2L1	MA0089.2	1e-85	8.64e-83
MA0496.3	MAFK	MA0496.3	8.86e-78	7.66e-75
MA1125.1 (ZNF384)	MEME-2	AAAAAAAAAAAAAAA	2.07e-10	2e-74
MA0501.1	MAF::NFE2	MA0501.1	6.75e-72	5.83e-69
MA0659.3	Mafg	MA0659.3	5.69e-63	4.92e-60
MA0150.2	Nfe2l2	MA0150.2	1.78e-54	1.54e-51
MA0682.2 (PITX1)	MEME-4	WGCTGGGATTACAGG	9.38e-11	3.2e-45
AGGCTGGAGTGCAGT	MEME-3	AGGCTGGAGTGCAGT	1.14e-13	6.4e-43
MA0790.1	POU4F1	MA0790.1	4.04e-44	3.49e-41
MA0680.2	Pax7	MA0680.2	1.14e-39	9.82e-37
MA0791.1	POU4F3	MA0791.1	4.56e-39	3.94e-36
MA1596.1 (ZNF460)	MEME-5	CCTCAGCCTCCCAAR	3.4e-09	2.8e-33
MA0037.4	Gata3	MA0037.4	1.3e-35	1.13e-32
MA0681.2	PHOX2B	MA0681.2	1.23e-34	1.06e-31
MA1978.1	ZNF354A	MA1978.1	1.77e-34	1.53e-31
MA1104.2	GATA6	MA1104.2	6.8e-34	5.88e-31
MA0142.1	Pou5f1::Sox2	MA0142.1	1.2e-33	1.03e-30
MA0676.1	Nr2e1	MA0676.1	1.28e-33	1.1e-30
MA0901.2	HOXB13	MA0901.2	9.15e-33	7.91e-30
MA0723.2	VAX2	MA0723.2	1.14e-32	9.85e-30
MA1963.1	SATB1	MA1963.1	1.48e-32	1.28e-29
MA0785.1	POU2F1	MA0785.1	1.87e-32	1.62e-29
MA0787.1	POU3F2	MA0787.1	4.26e-32	3.68e-29
MA1471.1	BARX2	MA1471.1	6.56e-32	5.66e-29
MA0786.1	POU3F1	MA0786.1	8.73e-32	7.55e-29
MA0035.4	GATA1	MA0035.4	1.89e-31	1.64e-28
MA0628.1	POU6F1	MA0628.1	8.18e-31	7.07e-28
MA0792.1	POU5F1B	MA0792.1	1.05e-30	9.05e-28
MA0793.1	POU6F2	MA0793.1	2.5e-30	2.16e-27
MA0158.2	HOXA5	MA0158.2	2.62e-30	2.26e-27
MA1549.1	POU6F1	MA1549.1	2.79e-30	2.41e-27
MA0846.1	FOXC2	MA0846.1	3.36e-30	2.9e-27
MA1606.1	Foxf1	MA1606.1	3.59e-29	3.1e-26
MA0788.1	POU3F3	MA0788.1	4.08e-29	3.52e-26
MA0477.2 (FOSL1)	STREME-1	1-NNNVTGASTCABNNN	3.44e-213	3.55e-26
CTCAAGYGATCCTCC	MEME-6	CTCAAGYGATCCTCC	2.16e-10	9.3e-26
MA1970.1	TRPS1	MA1970.1	2.95e-28	2.55e-25
MA1643.1 (NFIB)	MEME-8	GCCRGGCRYGGTGGC	7.07e-06	2.7e-25
MA0910.2	HOXD8	MA0910.2	4.32e-28	3.73e-25
MA0041.2	FOXD3	MA0041.2	4.47e-28	3.86e-25
MA0052.4	MEF2A	MA0052.4	7.42e-28	6.41e-25
MA0031.1	FOXD1	MA0031.1	1.21e-27	1.05e-24
MA0602.1	Arid5a	MA0602.1	2.2e-27	1.9e-24
MA0766.2	GATA5	MA0766.2	2.38e-27	2.05e-24
MA0630.1	SHOX	MA0630.1	2.57e-27	2.22e-24
MA0153.2	HNF1B	MA0153.2	5.37e-27	4.64e-24
MA1502.1	HOXB8	MA1502.1	1.16e-26	1.01e-23
MA0707.2	MNX1	MA0707.2	1.29e-26	1.12e-23
MA0718.1	RAX	MA0718.1	1.98e-26	1.71e-23
MA1639.1	MEIS1	MA1639.1	2.07e-26	1.79e-23
MA0654.1	ISX	MA0654.1	2.17e-26	1.88e-23
MA0886.1	EMX2	MA0886.1	3.1e-26	2.68e-23
MA1487.2	FOXE1	MA1487.2	3.17e-26	2.74e-23
MA0905.1	HOXC10	MA0905.1	3.82e-26	3.3e-23
MA0148.4	FOXA1	MA0148.4	6.61e-26	5.71e-23
MA0902.2	HOXB2	MA0902.2	1.09e-25	9.46e-23
MA0713.1	PHOX2A	MA0713.1	1.18e-25	1.02e-22
MA0674.1	NKX6-1	MA0674.1	1.58e-25	1.36e-22
MA0661.1	MEOX1	MA0661.1	1.69e-25	1.46e-22
MA0465.2	CDX2	MA0465.2	1.86e-25	1.61e-22
MA0904.2	HOXB5	MA0904.2	1.9e-25	1.64e-22
MA0601.1	Arid3b	MA0601.1	2.7e-25	2.33e-22
MA0722.1	VAX1	MA0722.1	2.9e-25	2.51e-22
MA1495.1	HOXA1	MA1495.1	3.82e-25	3.3e-22
MA1152.1	SOX15	MA1152.1	4.01e-25	3.46e-22
MA0634.1	ALX3	MA0634.1	6.04e-25	5.21e-22
MA0789.1	POU3F4	MA0789.1	1.71e-24	1.48e-21
MA0658.1	LHX6	MA0658.1	2.01e-24	1.73e-21
MA1505.1	HOXC8	MA1505.1	2.47e-24	2.13e-21
MA0912.2	HOXD3	MA0912.2	3e-24	2.59e-21
MA0046.2	HNF1A	MA0046.2	3.72e-24	3.21e-21
MA0845.1	FOXB1	MA0845.1	4.99e-24	4.31e-21
MA0027.2	EN1	MA0027.2	5.32e-24	4.6e-21
MA0899.1	HOXA10	MA0899.1	6.38e-24	5.51e-21
MA0495.3	MAFF	MA0495.3	7.9e-24	6.83e-21
MA0612.2	EMX1	MA0612.2	8.69e-24	7.51e-21
MA0880.1	Dlx3	MA0880.1	9.27e-24	8.01e-21
MA0482.2	GATA4	MA0482.2	1.62e-23	1.4e-20
MA0709.1	Msx3	MA0709.1	1.81e-23	1.56e-20
MA0851.1	Foxj3	MA0851.1	3.84e-23	3.32e-20
MA0909.3	Hoxd13	MA0909.3	3.95e-23	3.41e-20
MA1143.1	FOSL1::JUND	MA1143.1	5.59e-23	4.83e-20
MA1623.1	Stat2	MA1623.1	6.05e-23	5.23e-20
MA0898.1	Hmx3	MA0898.1	6.21e-23	5.36e-20
MA0143.4	SOX2	MA0143.4	7.09e-23	6.12e-20
MA0894.1	HESX1	MA0894.1	7.95e-23	6.86e-20
MA1480.1	DPRX	MA1480.1	8.31e-23	7.18e-20
MA1124.1	ZNF24	MA1124.1	1.08e-22	9.37e-20
MA1499.1	HOXB4	MA1499.1	1.53e-22	1.32e-19
MA0833.2	ATF4	MA0833.2	1.56e-22	1.35e-19
TCTYRCTCTGTYRCC	MEME-7	TCTYRCTCTGTYRCC	1.31e-11	1.6e-19
MA0682.2	PITX1	MA0682.2	1.92e-22	1.66e-19
MA0675.1	NKX6-2	MA0675.1	3.82e-22	3.3e-19
MA1636.1	CEBPG	MA1636.1	4.45e-22	3.84e-19
MA0701.2	LHX9	MA0701.2	4.5e-22	3.88e-19
MA0720.1	Shox2	MA0720.1	4.72e-22	4.08e-19
MA0889.1	GBX1	MA0889.1	4.82e-22	4.16e-19
MA0706.1	MEOX2	MA0706.1	6.62e-22	5.72e-19
MA0036.3	GATA2	MA0036.3	7.11e-22	6.15e-19
MA0591.1	Bach1::Mafk	MA0591.1	9.03e-22	7.8e-19
MA0881.1	Dlx4	MA0881.1	9.47e-22	8.18e-19
MA0725.1	VSX1	MA0725.1	9.68e-22	8.36e-19
MA0704.1	Lhx4	MA0704.1	1.06e-21	9.18e-19
MA0908.1	HOXD11	MA0908.1	1.08e-21	9.34e-19
MA1640.1	MEIS2	MA1640.1	1.48e-21	1.28e-18
MA0047.3	FOXA2	MA0047.3	1.49e-21	1.29e-18
MA0885.2	Dlx2	MA0885.2	2.05e-21	1.78e-18
MA1657.1	ZNF652	MA1657.1	2.63e-21	2.27e-18
MA1481.1	DRGX	MA1481.1	3.09e-21	2.67e-18
MA0627.2	POU2F3	MA0627.2	3.44e-21	2.97e-18
MA0755.1	CUX2	MA0755.1	3.9e-21	3.37e-18
MA1497.1	HOXA6	MA1497.1	6.88e-21	5.95e-18
MA0890.1	GBX2	MA0890.1	7.14e-21	6.17e-18
MA0084.1	SRY	MA0084.1	1.31e-20	1.13e-17
MA0726.1	VSX2	MA0726.1	1.49e-20	1.29e-17
MA0868.2	SOX8	MA0868.2	1.49e-20	1.29e-17
MA1607.1	Foxl2	MA1607.1	1.99e-20	1.72e-17
MA0666.2	MSX1	MA0666.2	2.11e-20	1.82e-17
MA0038.2 (GFI1)	MEME-9	TCWCRGCTCACTGCA	4.89e-09	2.7e-17
MA1519.1	LHX5	MA1519.1	3.41e-20	2.94e-17
MA0611.2	Dux	MA0611.2	4.64e-20	4.01e-17
MA0132.2	PDX1	MA0132.2	1.01e-19	8.75e-17
MA0032.2	FOXC1	MA0032.2	1.1e-19	9.53e-17
MA0523.1	TCF7L2	MA0523.1	1.11e-19	9.56e-17
MA0125.1	Nobox	MA0125.1	1.44e-19	1.25e-16
MA0481.3	FOXP1	MA0481.3	1.55e-19	1.34e-16
MA0705.1	Lhx8	MA0705.1	1.6e-19	1.38e-16
MA0879.2	DLX1	MA0879.2	1.73e-19	1.49e-16
MA1113.2	PBX2	MA1113.2	1.86e-19	1.61e-16
MA0754.2	CUX1	MA0754.2	2.15e-19	1.86e-16
MA0882.1	DLX6	MA0882.1	2.56e-19	2.21e-16
MA0724.1	VENTX	MA0724.1	2.82e-19	2.44e-16
MA0075.3	PRRX2	MA0075.3	2.85e-19	2.46e-16
MA0716.1	PRRX1	MA0716.1	3.13e-19	2.71e-16
MA0122.3	Nkx3-2	MA0122.3	3.44e-19	2.97e-16
MA0077.1	SOX9	MA0077.1	3.64e-19	3.14e-16
MA0883.1	Dmbx1	MA0883.1	3.74e-19	3.23e-16
MA0710.1	NOTO	MA0710.1	4.19e-19	3.62e-16
MA1125.1	ZNF384	MA1125.1	8.32e-19	7.19e-16
MA0708.2	MSX2	MA0708.2	1.12e-18	9.65e-16
MA0875.1	BARX1	MA0875.1	1.95e-18	1.68e-15
MA0900.2	HOXA2	MA0900.2	2.73e-18	2.36e-15
MA0151.1	Arid3a	MA0151.1	2.97e-18	2.56e-15
MA1683.1	FOXA3	MA1683.1	3.79e-18	3.28e-15
MA0613.1	FOXG1	MA0613.1	4.34e-18	3.75e-15
MA0895.1	HMBOX1	MA0895.1	4.82e-18	4.16e-15
MA1115.1	POU5F1	MA1115.1	8.73e-18	7.54e-15
MA0717.1	RAX2	MA0717.1	1.2e-17	1.04e-14
MA0700.2	LHX2	MA0700.2	1.29e-17	1.12e-14
MA0847.3	FOXD2	MA0847.3	1.32e-17	1.14e-14
MA1518.2	Lhx1	MA1518.2	1.35e-17	1.16e-14
MA0068.2	PAX4	MA0068.2	1.43e-17	1.24e-14
MA0644.2	ESX1	MA0644.2	2.19e-17	1.89e-14
MA1530.1	NKX6-3	MA1530.1	2.55e-17	2.21e-14
MA1489.1	FOXN3	MA1489.1	2.75e-17	2.38e-14
MA0650.3	Hoxa13	MA0650.3	2.97e-17	2.56e-14
MA0911.1	Hoxa11	MA0911.1	3.47e-17	2.99e-14
MA1603.1	Dmrt1	MA1603.1	6.48e-17	5.6e-14
MA1103.2	FOXK2	MA1103.2	1e-16	8.66e-14
MA1463.1	ARGFX	MA1463.1	1.15e-16	9.98e-14
MA0903.1	HOXB3	MA0903.1	1.31e-16	1.13e-13
MA0913.2	HOXD9	MA0913.2	1.72e-16	1.48e-13
MA0888.1	EVX2	MA0888.1	3.06e-16	2.65e-13
MA0662.1	MIXL1	MA0662.1	3.1e-16	2.68e-13
MA0721.1	UNCX	MA0721.1	3.13e-16	2.7e-13
MA0497.1	MEF2C	MA0497.1	3.31e-16	2.86e-13
MA0140.2	GATA1::TAL1	MA0140.2	4.51e-16	3.89e-13
MA1476.2	Dlx5	MA1476.2	4.64e-16	4.01e-13
MA0108.2	TBP	MA0108.2	6.63e-16	5.73e-13
MA0876.1	BSX	MA0876.1	7.29e-16	6.3e-13
MA0854.1	Alx1	MA0854.1	7.83e-16	6.76e-13
MA1977.1 (ZNF324)	MEME-11	TYCTTYYYTYTCYTY	6.65e-11	1.2e-12
MA1577.1	TLX2	MA1577.1	1.54e-15	1.33e-12
MA1479.1	DMRTC2	MA1479.1	2.2e-15	1.9e-12
MA0467.2	Crx	MA0467.2	2.52e-15	2.18e-12
MA0892.1	GSX1	MA0892.1	2.92e-15	2.52e-12
MA0906.1	HOXC12	MA0906.1	3.13e-15	2.71e-12
MA0606.2	Nfat5	MA0606.2	4.03e-15	3.48e-12
MA0483.1	Gfi1B	MA0483.1	5.52e-15	4.77e-12
MA1500.1	HOXB6	MA1500.1	5.61e-15	4.85e-12
MA1709.1	ZIM3	MA1709.1	5.67e-15	4.9e-12
MA0033.2	FOXL1	MA0033.2	5.76e-15	4.98e-12
MA0648.1	GSC	MA0648.1	6.58e-15	5.68e-12
MA0714.1	PITX3	MA0714.1	7.48e-15	6.46e-12
MA1588.1	ZNF136	MA1588.1	8.18e-15	7.06e-12
MA0050.3	Irf1	MA0050.3	9.89e-15	8.54e-12
MA0893.2	GSX2	MA0893.2	1.09e-14	9.44e-12
MA1990.1 (Gli1)	MEME-10	GGCTGGTCTYGAACT	7.17e-05	1e-11
MA0849.1	FOXO6	MA0849.1	1.3e-14	1.12e-11
MA0891.1	GSC2	MA0891.1	1.53e-14	1.32e-11
MA1974.1	ZNF211	MA1974.1	3.1e-14	2.68e-11
MA0618.1	LBX1	MA0618.1	3.23e-14	2.79e-11
MA0117.2	Mafb	MA0117.2	3.64e-14	3.15e-11
MA0514.2	Sox3	MA0514.2	3.67e-14	3.17e-11
MA0642.2	EN2	MA0642.2	3.7e-14	3.2e-11
MA0887.1	EVX1	MA0887.1	3.97e-14	3.43e-11
MA0769.2	TCF7	MA0769.2	4.64e-14	4.01e-11
MA0043.3	HLF	MA0043.3	5.44e-14	4.7e-11
MA0157.3	Foxo3	MA0157.3	8.93e-14	7.72e-11
MA0896.1	Hmx1	MA0896.1	9.24e-14	7.99e-11
MA1120.1	SOX13	MA1120.1	1.08e-13	9.36e-11
MA0025.2	NFIL3	MA0025.2	1.14e-13	9.88e-11
MA0699.1	LBX2	MA0699.1	1.33e-13	1.15e-10
MA0078.2	Sox17	MA0078.2	1.58e-13	1.36e-10
MA0679.2	ONECUT1	MA0679.2	1.84e-13	1.59e-10
MA1960.1	MGA::EVX1	MA1960.1	3.22e-13	2.78e-10
MA1501.1	HOXB7	MA1501.1	3.28e-13	2.84e-10
MA0867.2	SOX4	MA0867.2	3.74e-13	3.23e-10
MA0874.1	Arx	MA0874.1	4.22e-13	3.65e-10
MA0843.1	TEF	MA0843.1	5.77e-13	4.98e-10
MA1504.1	HOXC4	MA1504.1	8.22e-13	7.1e-10
MA0837.2	CEBPE	MA0837.2	8.58e-13	7.41e-10
MA0614.1	Foxj2	MA0614.1	1e-12	8.64e-10
MA1478.1	DMRTA2	MA1478.1	1.08e-12	9.3e-10
MA0768.2	Lef1	MA0768.2	1.19e-12	1.03e-09
MA0829.2	SREBF1	MA0829.2	1.25e-12	1.08e-09
MA0715.1	PROP1	MA0715.1	1.28e-12	1.1e-09
MA0809.2	TEAD4	MA0809.2	1.3e-12	1.12e-09
MA0780.1	PAX3	MA0780.1	1.5e-12	1.29e-09
MA0040.1	Foxq1	MA0040.1	2.17e-12	1.87e-09
MA1562.1	SOX14	MA1562.1	2.19e-12	1.89e-09
MA1729.1	ZNF680	MA1729.1	2.47e-12	2.14e-09
MA0853.1	Alx4	MA0853.1	4.41e-12	3.81e-09
MA1496.1	HOXA4	MA1496.1	4.54e-12	3.92e-09
MA1563.2	SOX18	MA1563.2	4.9e-12	4.24e-09
MA1421.1	TCF7L1	MA1421.1	6.91e-12	5.97e-09
MA0757.1	ONECUT3	MA0757.1	9.3e-12	8.03e-09
MA0029.1	Mecom	MA0029.1	9.45e-12	8.17e-09
MA0712.2	OTX2	MA0712.2	2.03e-11	1.76e-08
MA0036.3 (GATA2)	STREME-2	2-AAGATAA	9.29e-44	2.14e-08
MA0711.1	OTX1	MA0711.1	2.69e-11	2.32e-08
MA0492.1	JUND	MA0492.1	2.75e-11	2.37e-08
MA1507.1	HOXD4	MA1507.1	3.76e-11	3.25e-08
MA0782.2	PKNOX1	MA0782.2	3.94e-11	3.41e-08
MA0852.2	FOXK1	MA0852.2	5.31e-11	4.59e-08
MA0102.4	CEBPA	MA0102.4	8.36e-11	7.22e-08
MA0842.2	NRL	MA0842.2	1.28e-10	1.11e-07
MA0689.1	TBX20	MA0689.1	1.29e-10	1.11e-07
MA0702.2	LMX1A	MA0702.2	2.16e-10	1.87e-07
MA0063.2	NKX2-5	MA0063.2	2.66e-10	2.3e-07
MA0848.1	FOXO4	MA0848.1	3.28e-10	2.84e-07
MA0070.1	PBX1	MA0070.1	3.63e-10	3.14e-07
MA1112.2	NR4A1	MA1112.2	3.89e-10	3.36e-07
MA1119.1	SIX2	MA1119.1	4.16e-10	3.59e-07
MA1139.1	FOSL2::JUNB	MA1139.1	5.38e-10	4.65e-07
MA0087.2	Sox5	MA0087.2	5.49e-10	4.74e-07
MA1547.2	PITX2	MA1547.2	6.26e-10	5.41e-07
MA0838.1	CEBPG	MA0838.1	8.75e-10	7.56e-07
MA1498.2	HOXA7	MA1498.2	9.87e-10	8.53e-07
MA0466.3	CEBPB	MA0466.3	1.11e-09	9.61e-07
MA0480.2	Foxo1	MA0480.2	1.21e-09	1.04e-06
MA1127.1	FOSB::JUN	MA1127.1	1.25e-09	1.08e-06
MA0836.2	CEBPD	MA0836.2	1.49e-09	1.29e-06
MA0488.1	JUN	MA0488.1	1.68e-09	1.45e-06
MA0093.3	USF1	MA0093.3	1.91e-09	1.65e-06
MA0639.1	DBP	MA0639.1	2e-09	1.73e-06
MA0621.1	mix-a	MA0621.1	2.57e-09	2.22e-06
MA1506.1	HOXD10	MA1506.1	2.91e-09	2.51e-06
MA0517.1	STAT1::STAT2	MA0517.1	3.03e-09	2.62e-06
MA1608.1	Isl1	MA1608.1	3.25e-09	2.81e-06
MA0030.1	FOXF2	MA0030.1	4.16e-09	3.59e-06
MA1991.1	Hnf1A	MA1991.1	4.17e-09	3.6e-06
MA0850.1	FOXP3	MA0850.1	8.2e-09	7.08e-06
MA1126.1	FOS::JUN	MA1126.1	8.98e-09	7.76e-06
MA0596.1	SREBF2	MA0596.1	9.38e-09	8.1e-06
TTTTTWGTAGAGAYR	MEME-12	TTTTTWGTAGAGAYR	8.66e-09	9e-06
MA0877.3	BARHL1	MA0877.3	1.13e-08	9.73e-06
MA0038.2	GFI1	MA0038.2	1.16e-08	1e-05
MA1118.1	SIX1	MA1118.1	1.34e-08	1.16e-05
MA1131.1	FOSL2::JUN	MA1131.1	1.35e-08	1.17e-05
MA1129.1	FOSL1::JUN	MA1129.1	1.55e-08	1.34e-05
MA0090.3	TEAD1	MA0090.3	2.25e-08	1.95e-05
MA0635.1	BARHL2	MA0635.1	3.18e-08	2.75e-05
MA0914.1	ISL2	MA0914.1	4.41e-08	3.81e-05
MA0878.3	CDX1	MA0878.3	6.56e-08	5.67e-05
MA0693.3	Vdr	MA0693.3	7.59e-08	6.56e-05
MA0884.2	DUXA	MA0884.2	7.6e-08	6.57e-05
3-ATWWWAT	STREME-3	3-ATWWWAT	1.19e-32	7.41e-05
MA0052.4 (MEF2A)	STREME-4	4-AAAAAT	5.18e-29	7.84e-05
MA0144.2	STAT3	MA0144.2	1.09e-07	9.42e-05
MA0907.1	HOXC13	MA0907.1	1.24e-07	0.000107
MA0042.2	FOXI1	MA0042.2	2.07e-07	0.000178
MA1975.1	ZNF214	MA1975.1	2.87e-07	0.000248
MA0498.2	MEIS1	MA0498.2	3.24e-07	0.00028
MA1133.1	JUN::JUNB	MA1133.1	3.81e-07	0.000329
MA1114.1	PBX3	MA1114.1	4.47e-07	0.000387
MA0018.4	CREB1	MA0018.4	4.73e-07	0.000408
MA0629.1	Rhox11	MA0629.1	6.68e-07	0.000577
MA0624.2	Nfatc1	MA0624.2	7.84e-07	0.000678
MA0719.1	RHOXF1	MA0719.1	7.94e-07	0.000686
MA1561.1	SOX12	MA1561.1	8.45e-07	0.00073
MA0706.1 (MEOX2)	STREME-5	5-TRATYA	8.55e-31	0.000746
MA0468.1	DUX4	MA0468.1	9.34e-07	0.000807
MA1111.1	NR2F2	MA1111.1	1.74e-06	0.0015
MA0687.1	SPIC	MA0687.1	2.32e-06	0.002
MA1645.1	NKX2-2	MA1645.1	3.84e-06	0.00332
MA0626.1	Npas2	MA0626.1	4.39e-06	0.00379
MA0124.2	Nkx3-1	MA0124.2	5.21e-06	0.0045
MA0595.1	SREBF1	MA0595.1	5.9e-06	0.0051
MA0631.1	Six3	MA0631.1	6.34e-06	0.00548
MA0515.1	Sox6	MA0515.1	6.72e-06	0.00581
MA0610.1	DMRT3	MA0610.1	7.72e-06	0.00667
MA0152.2	Nfatc2	MA0152.2	8.49e-06	0.00733
MA0141.3	ESRRB	MA0141.3	9.27e-06	0.00801
MA0461.2	Atoh1	MA0461.2	9.38e-06	0.0081
MA1980.1	ZNF418	MA1980.1	9.98e-06	0.00862
MA0620.3	MITF	MA0620.3	1.01e-05	0.00871
MA0784.2	POU1F1	MA0784.2	1.09e-05	0.00944
MA1596.1	ZNF460	MA1596.1	1.17e-05	0.0101
MA0069.1	PAX6	MA0069.1	1.61e-05	0.0139
MA1720.1	ZNF85	MA1720.1	1.74e-05	0.015
MA0060.3	NFYA	MA0060.3	1.85e-05	0.016
MA1632.1	ATF2	MA1632.1	2.26e-05	0.0195
MA1593.1	ZNF317	MA1593.1	2.87e-05	0.0248
MA1145.1	FOSL2::JUND	MA1145.1	3.92e-05	0.0338
MA0897.1	Hmx2	MA0897.1	4.55e-05	0.0393
MA1105.2	GRHL2	MA1105.2	5.42e-05	0.0468
MA1479.1 (DMRTC2)	STREME-6	6-TATCAA	7.87e-31	0.0472
MA1589.1 (ZNF140)	STREME-7	7-AGAATTGCT	3.05e-08	0.0569
8-GCTCACTGCA	STREME-8	8-GCTCACTGCA	2.12e-08	0.0616
MA1487.2 (FOXE1)	STREME-9	9-AAAAAAA	4.24e-19	0.214
10-CACTGCACTCCAGCC	STREME-10	10-CACTGCACTCCAGCC	5.54e-06	3.71
MA0676.1 (Nr2e1)	STREME-11	11-AGTCAW	6.79e-83	4.73

LR lists

# LR_open_10h_xstreme %>%
#   dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>%
#   arrange(.,EVALUE) %>%
#    dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
#   # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>%
#   # dplyr::filter(., EVALUE<0.05) %>%
#   kable(., caption = "Enriched motifs in LR_open") %>%
#   kable_paper("striped", full_width = TRUE) %>%
#   kable_styling(full_width = FALSE, font_size = 16) %>%
#   scroll_box(height = "800px")

LR_open_200xstreme %>%
  dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>%
  arrange(.,EVALUE) %>%
   dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
  # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>%
  # dplyr::filter(., EVALUE<0.05) %>%
  kable(., caption = "Enriched motifs in LR_open 200bp only") %>%
  kable_paper("striped", full_width = TRUE) %>%
  kable_styling(full_width = FALSE, font_size = 16) %>%
  scroll_box(height = "800px")

Enriched motifs in LR_open 200bp only
RANK	SIM_MOTIF	ALT_ID	ID	SEA_PVALUE	EVALUE
35	MA0659.3	Mafg	MA0659.3	1.2e-305	1.04e-305
10	MA1130.1	FOSL2::JUN	MA1130.1	1.19e-305	1.05e-305
1	MA1134.1 (FOS::JUNB)	STREME-1	1-DATGASTCATH	1.09e-305	1.09e-305
55	MA0680.2	Pax7	MA0680.2	1.33e-305	1.16e-305
26	MA1142.1	FOSL1::JUND	MA1142.1	1.58e-305	1.39e-305
48	MA0788.1	POU3F3	MA0788.1	1.64e-305	1.44e-305
32	MA0501.1	MAF::NFE2	MA0501.1	1.68e-305	1.46e-305
31	MA0496.3	MAFK	MA0496.3	1.77e-305	1.56e-305
15	MA1633.2	BACH1	MA1633.2	1.89e-305	1.65e-305
50	MA0153.2	HNF1B	MA0153.2	1.99e-305	1.74e-305
16	MA0490.2	JUNB	MA0490.2	2.13e-305	1.86e-305
24	MA0655.1	JDP2	MA0655.1	2.14e-305	1.86e-305
27	MA1101.2	BACH2	MA1101.2	2.17e-305	1.89e-305
47	MA0046.2	HNF1A	MA0046.2	2.16e-305	1.89e-305
7	MA0477.2	FOSL1	MA0477.2	2.29e-305	2.01e-305
41	MA0791.1	POU4F3	MA0791.1	2.37e-305	2.07e-305
13	MA0099.3	FOS::JUN	MA0099.3	2.4e-305	2.11e-305
3	MA1134.1	FOS::JUNB	MA1134.1	2.81e-305	2.45e-305
14	MA0491.2	JUND	MA0491.2	3.13e-305	2.75e-305
52	MA0886.1	EMX2	MA0886.1	3.15e-305	2.75e-305
28	MA1132.1	JUN::JUNB	MA1132.1	3.16e-305	2.79e-305
49	MA0681.2	PHOX2B	MA0681.2	3.32e-305	2.9e-305
17	MA1634.1	BATF	MA1634.1	3.66e-305	3.22e-305
37	MA1113.2	PBX2	MA1113.2	3.86e-305	3.37e-305
51	MA0902.2	HOXB2	MA0902.2	4.01e-305	3.5e-305
44	MA0786.1	POU3F1	MA0786.1	4.17e-305	3.65e-305
36	MA1639.1	MEIS1	MA1639.1	4.24e-305	3.74e-305
60	MA1115.1	POU5F1	MA1115.1	4.34e-305	3.79e-305
19	MA0462.2	BATF::JUN	MA0462.2	4.38e-305	3.81e-305
38	MA0676.1	Nr2e1	MA0676.1	4.68e-305	4.09e-305
9	MA1141.1	FOS::JUND	MA1141.1	5.32e-305	4.64e-305
54	MA0846.1	FOXC2	MA0846.1	5.57e-305	4.86e-305
5	MA0476.1	FOS	MA0476.1	5.63e-305	4.9e-305
23	MA1928.1	BNC2	MA1928.1	5.86e-305	5.16e-305
2	MA1144.1	FOSL2::JUND	MA1144.1	5.93e-305	5.22e-305
22	MA1137.1	FOSL1::JUNB	MA1137.1	6.36e-305	5.54e-305
62	MA0679.2	ONECUT1	MA0679.2	7.01e-305	6.12e-305
64	MA0787.1	POU3F2	MA0787.1	7.21e-305	6.3e-305
11	MA0489.2	Jun	MA0489.2	7.2e-305	6.34e-305
56	MA0785.1	POU2F1	MA0785.1	7.29e-305	6.37e-305
58	MA1487.2	FOXE1	MA1487.2	7.53e-305	6.58e-305
59	MA0789.1	POU3F4	MA0789.1	7.6e-305	6.64e-305
29	MA0841.1	NFE2	MA0841.1	7.56e-305	6.65e-305
42	MA1640.1	MEIS2	MA1640.1	7.76e-305	6.78e-305
18	MA1988.1	Atf3	MA1988.1	8.29e-305	7.3e-305
4	MA1138.1	FOSL2::JUNB	MA1138.1	8.36e-305	7.36e-305
20	MA0835.2	BATF3	MA0835.2	8.75e-305	7.62e-305
12	MA1128.1	FOSL1::JUN	MA1128.1	9.06e-305	7.9e-305
21	MA0478.1	FOSL2	MA0478.1	9.16999999999999e-305	8.07e-305
39	MA0790.1	POU4F1	MA0790.1	9.46e-305	8.26e-305
57	MA0591.1	Bach1::Mafk	MA0591.1	9.65e-305	8.43e-305
34	MA0150.2	Nfe2l2	MA0150.2	9.69999999999999e-305	8.45e-305
46	MA0142.1	Pou5f1::Sox2	MA0142.1	9.81e-305	8.57e-305
63	MA0792.1	POU5F1B	MA0792.1	9.90999999999999e-305	8.66e-305
53	MA0627.2	POU2F3	MA0627.2	9.99999999999999e-306	8.76e-305
30	MA0089.2	MAFG::NFE2L1	MA0089.2	1.05e-305	9.14999999999999e-305
8	MA1135.1	FOSB::JUNB	MA1135.1	1.08e-305	9.51999999999999e-305
43	MA0845.1	FOXB1	MA0845.1	1.09e-305	9.53e-305
40	MA1978.1	ZNF354A	MA1978.1	1.1e-305	9.57e-305
65	MA1143.1	FOSL1::JUND	MA1143.1	7e-303	6.11e-300
66	MA0032.2	FOXC1	MA0032.2	1.43e-295	1.25e-292
67	MA1963.1	SATB1	MA1963.1	3.33e-294	2.92e-291
69	MA0628.1	POU6F1	MA0628.1	4.21e-291	3.68e-288
70	MA0041.2	FOXD3	MA0041.2	1.21e-286	1.06e-283
71	MA1124.1	ZNF24	MA1124.1	1.62e-281	1.42e-278
72	MA0611.2	Dux	MA0611.2	2.29e-274	2e-271
74	MA0715.1	PROP1	MA0715.1	8.64e-270	7.56e-267
75	MA0851.1	Foxj3	MA0851.1	4.74e-269	4.14e-266
76	MA1471.1	BARX2	MA1471.1	3.05e-267	2.67e-264
77	MA0084.1	SRY	MA0084.1	9.72999999999999e-267	8.51e-264
78	MA1606.1	Foxf1	MA1606.1	1.23e-266	1.08e-263
79	MA1603.1	Dmrt1	MA1603.1	1.65e-266	1.44e-263
80	MA0148.4	FOXA1	MA0148.4	1.73e-266	1.51e-263
81	MA1607.1	Foxl2	MA1607.1	8.15e-266	7.12e-263
82	MA0713.1	PHOX2A	MA0713.1	1.06e-265	9.26e-263
83	MA1974.1	ZNF211	MA1974.1	2.44e-265	2.13e-262
84	MA0052.4	MEF2A	MA0052.4	3.03e-265	2.65e-262
85	MA0025.2	NFIL3	MA0025.2	2.4e-264	2.1e-261
86	MA1549.1	POU6F1	MA1549.1	3.71e-263	3.25e-260
87	MA0602.1	Arid5a	MA0602.1	3.46e-262	3.02e-259
89	MA0793.1	POU6F2	MA0793.1	1.66e-258	1.45e-255
90	MA0601.1	Arid3b	MA0601.1	1.18e-257	1.03e-254
91	MA0612.2	EMX1	MA0612.2	6.8e-257	5.95e-254
92	MA0722.1	VAX1	MA0722.1	3.41e-255	2.98e-252
93	MA0847.3	FOXD2	MA0847.3	1.32e-252	1.15e-249
94	MA0901.2	HOXB13	MA0901.2	6.73e-251	5.89e-248
95	MA0613.1	FOXG1	MA0613.1	1.34e-246	1.17e-243
96	MA0910.2	HOXD8	MA0910.2	1.52e-245	1.33e-242
97	MA0723.2	VAX2	MA0723.2	4.09e-245	3.58e-242
98	MA0158.2	HOXA5	MA0158.2	7.57e-245	6.62e-242
99	MA0908.1	HOXD11	MA0908.1	1.07e-239	9.37e-237
100	MA0495.3	MAFF	MA0495.3	2.34e-238	2.04e-235
101	MA0710.1	NOTO	MA0710.1	2.47e-238	2.16e-235
102	MA1502.1	HOXB8	MA1502.1	3.27e-238	2.86e-235
103	MA1636.1	CEBPG	MA1636.1	6.29e-238	5.49e-235
104	MA0706.1	MEOX2	MA0706.1	3e-236	2.63e-233
105	MA0614.1	Foxj2	MA0614.1	2.71e-234	2.37e-231
106	MA0707.2	MNX1	MA0707.2	7.25e-230	6.34e-227
107	MA0031.1	FOXD1	MA0031.1	2.68e-225	2.34e-222
108	MA0849.1	FOXO6	MA0849.1	1.4e-224	1.23e-221
110	MA0724.1	VENTX	MA0724.1	1.82e-223	1.59e-220
111	MA0700.2	LHX2	MA0700.2	1.02e-222	8.92e-220
112	MA0047.3	FOXA2	MA0047.3	3.58e-222	3.13e-219
113	MA0043.3	HLF	MA0043.3	3.01e-221	2.63e-218
114	MA0132.2	PDX1	MA0132.2	3.46e-221	3.02e-218
115	MA0497.1	MEF2C	MA0497.1	4.47e-221	3.91e-218
116	MA0903.1	HOXB3	MA0903.1	3.25e-220	2.84e-217
117	MA1505.1	HOXC8	MA1505.1	4.87e-220	4.25e-217
118	MA0465.2	CDX2	MA0465.2	2.39e-219	2.09e-216
120	MA1495.1	HOXA1	MA1495.1	3.38e-218	2.95e-215
121	MA1152.1	SOX15	MA1152.1	3.74e-218	3.27e-215
122	MA0654.1	ISX	MA0654.1	8.74999999999999e-217	7.65e-214
123	MA0042.2	FOXI1	MA0042.2	9.62999999999999e-217	8.42e-214
124	MA1125.1	ZNF384	MA1125.1	1.36e-216	1.19e-213
125	MA0675.1	NKX6-2	MA0675.1	5.76e-216	5.04e-213
126	MA0035.4	GATA1	MA0035.4	3.12e-215	2.72e-212
127	MA1479.1	DMRTC2	MA1479.1	1.25e-214	1.09e-211
128	MA0674.1	NKX6-1	MA0674.1	1.88e-214	1.65e-211
129	MA0661.1	MEOX1	MA0661.1	5.7e-214	4.98e-211
131	MA0033.2	FOXL1	MA0033.2	2.06e-209	1.8e-206
132	MA0122.3	Nkx3-2	MA0122.3	4.12e-208	3.6e-205
133	MA0905.1	HOXC10	MA0905.1	5.01e-205	4.38e-202
134	MA0701.2	LHX9	MA0701.2	2.84e-204	2.48e-201
135	MA1530.1	NKX6-3	MA1530.1	4.82e-204	4.21e-201
136	MA1463.1	ARGFX	MA1463.1	4.94e-204	4.32e-201
137	MA0718.1	RAX	MA0718.1	3.32e-203	2.9e-200
138	MA0848.1	FOXO4	MA0848.1	3.57e-203	3.12e-200
139	MA1489.1	FOXN3	MA1489.1	5.13e-203	4.48e-200
140	MA0630.1	SHOX	MA0630.1	1.55e-202	1.36e-199
141	MA0102.4	CEBPA	MA0102.4	1.81e-202	1.58e-199
142	MA0650.3	Hoxa13	MA0650.3	2.63e-202	2.3e-199
143	MA0878.3	CDX1	MA0878.3	1.93e-199	1.68e-196
144	MA1519.1	LHX5	MA1519.1	2.79e-199	2.44e-196
145	MA0682.2	PITX1	MA0682.2	3.07e-198	2.68e-195
146	MA0904.2	HOXB5	MA0904.2	3.89e-198	3.4e-195
147	MA0912.2	HOXD3	MA0912.2	2.04e-197	1.78e-194
148	MA1962.1	POU2F1::SOX2	MA1962.1	2.42e-197	2.12e-194
149	MA0899.1	HOXA10	MA0899.1	1.87e-196	1.63e-193
150	MA0644.2	ESX1	MA0644.2	8.66999999999999e-196	7.58e-193
151	MA0658.1	LHX6	MA0658.1	5.02e-195	4.39e-192
152	MA1481.1	DRGX	MA1481.1	9.9e-195	8.65e-192
153	MA0075.3	PRRX2	MA0075.3	1.01e-194	8.82e-192
154	MA0909.3	Hoxd13	MA0909.3	2.72e-194	2.38e-191
155	MA0913.2	HOXD9	MA0913.2	3.79e-194	3.32e-191
156	MA0725.1	VSX1	MA0725.1	1.54e-193	1.35e-190
157	MA1480.1	DPRX	MA1480.1	6.76e-192	5.91e-189
158	MA0709.1	Msx3	MA0709.1	6.05e-191	5.29e-188
159	MA1104.2	GATA6	MA1104.2	2.8e-190	2.45e-187
161	MA1970.1	TRPS1	MA1970.1	6.98e-188	6.1e-185
162	MA0151.1	Arid3a	MA0151.1	1.83e-187	1.6e-184
163	MA0716.1	PRRX1	MA0716.1	2.43e-187	2.12e-184
164	MA0833.2	ATF4	MA0833.2	7.56e-187	6.6e-184
165	MA0125.1	Nobox	MA0125.1	1.51e-186	1.32e-183
166	MA0108.2	TBP	MA0108.2	1.66e-185	1.45e-182
167	MA0892.1	GSX1	MA0892.1	6.9e-185	6.03e-182
168	MA1577.1	TLX2	MA1577.1	3.16e-184	2.76e-181
169	MA0880.1	Dlx3	MA0880.1	4.61e-183	4.03e-180
170	MA1103.2	FOXK2	MA1103.2	4.91e-183	4.29e-180
171	MA0027.2	EN1	MA0027.2	1.53e-182	1.34e-179
172	MA1499.1	HOXB4	MA1499.1	1.73e-182	1.51e-179
173	MA0882.1	DLX6	MA0882.1	4.44e-182	3.88e-179
174	MA0868.2	SOX8	MA0868.2	7.1e-182	6.21e-179
175	MA0726.1	VSX2	MA0726.1	7.92e-182	6.92e-179
176	MA0068.2	PAX4	MA0068.2	7.54e-181	6.59e-178
177	MA1563.2	SOX18	MA1563.2	1.24e-180	1.08e-177
178	MA0704.1	Lhx4	MA0704.1	1.34e-180	1.17e-177
179	MA0881.1	Dlx4	MA0881.1	3.86e-180	3.37e-177
180	MA0036.3	GATA2	MA0036.3	2.91e-179	2.54e-176
181	MA0143.4	SOX2	MA0143.4	3.52e-179	3.07e-176
182	MA0836.2	CEBPD	MA0836.2	9.95e-179	8.7e-176
183	MA0875.1	BARX1	MA0875.1	4.53e-177	3.96e-174
184	MA0481.3	FOXP1	MA0481.3	8.11e-177	7.09e-174
185	MA1683.1	FOXA3	MA1683.1	2.62e-175	2.29e-172
186	MA0040.1	Foxq1	MA0040.1	2.46e-174	2.15e-171
187	MA0755.1	CUX2	MA0755.1	3.54e-174	3.09e-171
188	MA0077.1	SOX9	MA0077.1	7.81e-174	6.82e-171
189	MA0890.1	GBX2	MA0890.1	2.1e-173	1.83e-170
190	MA0720.1	Shox2	MA0720.1	1.09e-171	9.51e-169
191	MA0721.1	UNCX	MA0721.1	1.11e-171	9.66e-169
192	MA0898.1	Hmx3	MA0898.1	7.7e-171	6.73e-168
193	MA0894.1	HESX1	MA0894.1	7.63e-170	6.67e-167
194	MA0717.1	RAX2	MA0717.1	8.06e-169	7.04e-166
195	MA0157.3	Foxo3	MA0157.3	8.09e-169	7.07e-166
196	MA0666.2	MSX1	MA0666.2	2.86e-168	2.5e-165
197	MA0634.1	ALX3	MA0634.1	7.52e-166	6.58e-163
198	MA0900.2	HOXA2	MA0900.2	1.61e-165	1.4e-162
199	MA0874.1	Arx	MA0874.1	2.08e-165	1.82e-162
200	MA0854.1	Alx1	MA0854.1	1.01e-163	8.85e-161
201	MA0885.2	Dlx2	MA0885.2	7.14e-163	6.24e-160
202	MA1657.1	ZNF652	MA1657.1	8.97e-163	7.84e-160
203	MA0662.1	MIXL1	MA0662.1	2.55e-162	2.23e-159
204	MA0876.1	BSX	MA0876.1	2.57e-162	2.25e-159
205	MA0683.1	POU4F2	MA0683.1	1.55e-161	1.35e-158
206	MA1476.2	Dlx5	MA1476.2	6.37e-161	5.57e-158
207	MA1709.1	ZIM3	MA1709.1	6.52e-161	5.7e-158
208	MA0757.1	ONECUT3	MA0757.1	1.61e-160	1.41e-157
209	MA0911.1	Hoxa11	MA0911.1	7.84e-159	6.85e-156
210	MA0889.1	GBX1	MA0889.1	1.16e-158	1.01e-155
211	MA0853.1	Alx4	MA0853.1	2.14e-158	1.87e-155
212	MA0887.1	EVX1	MA0887.1	8.67e-158	7.58e-155
213	MA1504.1	HOXC4	MA1504.1	4.15e-156	3.62e-153
214	MA1498.2	HOXA7	MA1498.2	4.77e-152	4.17e-149
215	MA0705.1	Lhx8	MA0705.1	4.04e-151	3.53e-148
216	MA0708.2	MSX2	MA0708.2	5.91e-151	5.17e-148
217	MA1496.1	HOXA4	MA1496.1	2.09e-150	1.83e-147
218	MA0879.2	DLX1	MA0879.2	1.04e-149	9.05e-147
219	MA0907.1	HOXC13	MA0907.1	9.08e-149	7.94e-146
220	MA1623.1	Stat2	MA1623.1	2.46e-146	2.15e-143
221	MA0618.1	LBX1	MA0618.1	6.23e-146	5.45e-143
222	MA0895.1	HMBOX1	MA0895.1	1.02e-145	8.9e-143
223	MA0037.4	Gata3	MA0037.4	1.33e-144	1.16e-141
224	MA0070.1	PBX1	MA0070.1	6.84e-144	5.97e-141
225	MA0884.2	DUXA	MA0884.2	3.6e-142	3.15e-139
226	MA0754.2	CUX1	MA0754.2	3.75e-142	3.28e-139
227	MA0780.1	PAX3	MA0780.1	9.47e-142	8.28e-139
228	MA1120.1	SOX13	MA1120.1	1.16e-141	1.01e-138
229	MA0442.2	SOX10	MA0442.2	1.52e-141	1.33e-138
230	MA0852.2	FOXK1	MA0852.2	1.56e-141	1.36e-138
231	MA0635.1	BARHL2	MA0635.1	9.17e-139	8.02e-136
232	MA0678.1	OLIG2	MA0678.1	7.49e-137	6.54e-134
233	MA0642.2	EN2	MA0642.2	1.03e-136	9e-134
234	MA0891.1	GSC2	MA0891.1	1.06e-135	9.22e-133
235	MA1707.1	DMRTA1	MA1707.1	3.57e-134	3.12e-131
236	MA1500.1	HOXB6	MA1500.1	6.91e-133	6.04e-130
237	MA0648.1	GSC	MA0648.1	5.33e-132	4.66e-129
238	MA0699.1	LBX2	MA0699.1	9.67e-132	8.45e-129
239	MA0842.2	NRL	MA0842.2	2.6e-131	2.27e-128
240	MA0117.2	Mafb	MA0117.2	7.2e-131	6.29e-128
241	MA1518.2	Lhx1	MA1518.2	9.47e-131	8.28e-128
242	MA1507.1	HOXD4	MA1507.1	1.02e-130	8.93e-128
243	MA0050.3	Irf1	MA0050.3	5.53e-130	4.84e-127
244	MA0850.1	FOXP3	MA0850.1	4.47e-125	3.91e-122
245	MA1562.1	SOX14	MA1562.1	1.2e-124	1.05e-121
246	MA0769.2	TCF7	MA0769.2	1.61e-123	1.41e-120
247	MA1497.1	HOXA6	MA1497.1	2.41e-123	2.1e-120
248	MA0838.1	CEBPG	MA0838.1	3.19e-122	2.79e-119
249	MA0843.1	TEF	MA0843.1	7.38e-122	6.45e-119
250	MA0135.1	Lhx3	MA0135.1	2.37e-121	2.07e-118
251	MA0144.2	STAT3	MA0144.2	1.12e-119	9.77e-117
252	MA0482.2	GATA4	MA0482.2	1.58e-118	1.38e-115
253	MA1608.1	Isl1	MA1608.1	3.83e-118	3.35e-115
254	MA0621.1	mix-a	MA0621.1	2.56e-117	2.24e-114
255	MA0712.2	OTX2	MA0712.2	6.82e-117	5.97e-114
256	MA0523.1	TCF7L2	MA0523.1	7.94e-117	6.94e-114
257	MA0626.1	Npas2	MA0626.1	1.12e-116	9.76e-114
258	MA0606.2	Nfat5	MA0606.2	1.3e-115	1.13e-112
259	MA0593.1	FOXP2	MA0593.1	3.59e-115	3.13e-112
260	MA0893.2	GSX2	MA0893.2	9.27e-115	8.11e-112
261	MA0078.2	Sox17	MA0078.2	1.39e-114	1.22e-111
262	MA0030.1	FOXF2	MA0030.1	1.23e-113	1.08e-110
263	MA0514.2	Sox3	MA0514.2	2.19e-113	1.92e-110
264	MA1960.1	MGA::EVX1	MA1960.1	1.13e-111	9.91e-109
265	MA0906.1	HOXC12	MA0906.1	1.73e-111	1.52e-108
266	MA1729.1	ZNF680	MA1729.1	2.27e-109	1.99e-106
267	MA0480.2	Foxo1	MA0480.2	3.43e-109	3e-106
268	MA0809.2	TEAD4	MA0809.2	1.96e-107	1.72e-104
269	MA0140.2	GATA1::TAL1	MA0140.2	3.01e-107	2.63e-104
270	MA0106.3	TP53	MA0106.3	6.31e-106	5.51e-103
271	MA0766.2	GATA5	MA0766.2	6.37e-105	5.57e-102
272	MA0867.2	SOX4	MA0867.2	1.67e-103	1.46e-100
273	MA1588.1	ZNF136	MA1588.1	3.56e-103	3.11e-100
6	MA1134.1 (FOS::JUNB)	MEME-1	NDRTGASTCA	1.97e-305	1.2e-99
274	MA0896.1	Hmx1	MA0896.1	3.4e-102	2.97e-99
275	MA0520.1	Stat6	MA0520.1	9.49e-102	8.3e-99
276	MA1478.1	DMRTA2	MA1478.1	5.52e-100	4.82e-97
277	MA0888.1	EVX2	MA0888.1	1.47e-98	1.29e-95
278	MA0639.1	DBP	MA0639.1	1.96e-96	1.71e-93
279	MA0897.1	Hmx2	MA0897.1	2.57e-95	2.25e-92
280	MA0468.1	DUX4	MA0468.1	2.97e-95	2.59e-92
281	MA0768.2	Lef1	MA0768.2	7.38e-94	6.45e-91
282	MA0883.1	Dmbx1	MA0883.1	1.24e-93	1.08e-90
283	MA0515.1	Sox6	MA0515.1	1.63e-93	1.43e-90
284	MA0629.1	Rhox11	MA0629.1	2.37e-93	2.07e-90
285	MA1501.1	HOXB7	MA1501.1	2.58e-93	2.25e-90
286	MA1503.1	HOXB9	MA1503.1	2.24e-89	1.96e-86
287	MA0018.4	CREB1	MA0018.4	2.34e-89	2.05e-86
288	MA0784.2	POU1F1	MA0784.2	3.49e-89	3.05e-86
289	MA0483.1	Gfi1B	MA0483.1	4.77e-89	4.17e-86
290	MA0479.1	FOXH1	MA0479.1	9.58e-89	8.38e-86
292	MA0914.1	ISL2	MA0914.1	2.25e-87	1.97e-84
293	MA0837.2	CEBPE	MA0837.2	5.29e-86	4.62e-83
294	MA1119.1	SIX2	MA1119.1	5.82e-86	5.09e-83
295	MA0702.2	LMX1A	MA0702.2	1.39e-85	1.21e-82
296	MA0631.1	Six3	MA0631.1	1.4e-85	1.22e-82
297	MA1632.1	ATF2	MA1632.1	1.03e-83	8.99e-81
298	MA1150.1	RORB	MA1150.1	2.39e-82	2.09e-79
299	MA0711.1	OTX1	MA0711.1	1.3e-81	1.14e-78
300	MA0714.1	PITX3	MA0714.1	3.69e-81	3.22e-78
301	MA0467.2	Crx	MA0467.2	1.12e-80	9.76e-78
302	MA1139.1	FOSL2::JUNB	MA1139.1	2.93e-80	2.56e-77
303	MA1561.1	SOX12	MA1561.1	4.82e-80	4.21e-77
304	MA0095.3	Yy1	MA0095.3	1.48e-79	1.3e-76
305	MA0087.2	Sox5	MA0087.2	5.68e-79	4.96e-76
306	MA0827.1	OLIG3	MA0827.1	1.3e-78	1.14e-75
307	MA0693.3	Vdr	MA0693.3	1.46e-75	1.28e-72
308	MA1580.1	ZBTB32	MA1580.1	7.45e-75	6.51e-72
309	MA0461.2	Atoh1	MA0461.2	4.75e-74	4.15e-71
310	MA0038.2	GFI1	MA0038.2	4.19e-73	3.66e-70
311	MA1126.1	FOS::JUN	MA1126.1	3.09e-72	2.7e-69
312	MA1131.1	FOSL2::JUN	MA1131.1	2.57e-71	2.25e-68
313	MA1118.1	SIX1	MA1118.1	5.54e-70	4.84e-67
314	MA0063.2	NKX2-5	MA0063.2	9.72e-70	8.49e-67
315	MA0873.1	HOXD12	MA0873.1	1.16e-69	1.01e-66
316	MA0877.3	BARHL1	MA0877.3	1.6e-69	1.4e-66
317	MA0507.2	POU2F2	MA0507.2	2.06e-67	1.8e-64
318	MA1520.1	MAF	MA1520.1	2.91e-67	2.55e-64
319	MA0152.2	Nfatc2	MA0152.2	6.03e-67	5.27e-64
320	MA0090.3	TEAD1	MA0090.3	1.29e-66	1.13e-63
321	MA0782.2	PKNOX1	MA0782.2	4.03e-66	3.52e-63
322	MA0861.1	TP73	MA0861.1	4.52e-66	3.95e-63
323	MA1506.1	HOXD10	MA1506.1	2.95e-65	2.58e-62
324	MA0689.1	TBX20	MA0689.1	1.5e-64	1.31e-61
325	MA1127.1	FOSB::JUN	MA1127.1	3.89e-64	3.4e-61
326	MA0620.3	MITF	MA0620.3	1.61e-63	1.41e-60
327	MA0869.2	Sox11	MA0869.2	2.22e-62	1.94e-59
328	MA0029.1	Mecom	MA0029.1	3.19e-62	2.79e-59
329	MA0525.2	TP63	MA0525.2	8.03e-62	7.02e-59
330	MA1991.1	Hnf1A	MA1991.1	2.34e-60	2.05e-57
331	MA1112.2	NR4A1	MA1112.2	1.67e-59	1.46e-56
332	MA0772.1	IRF7	MA0772.1	2.03e-59	1.78e-56
333	MA1994.1	Nkx2-1	MA1994.1	6.51e-58	5.69e-55
68	MA1125.1 (ZNF384)	MEME-2	TTTTTTTTTTTTTTT	7.38e-294	3.2e-54
334	MA0596.1	SREBF2	MA0596.1	7.77e-57	6.79e-54
335	MA1473.1	CDX4	MA1473.1	1.01e-56	8.83e-54
336	MA0069.1	PAX6	MA0069.1	1.4e-55	1.23e-52
337	MA0624.2	Nfatc1	MA0624.2	1.78e-55	1.55e-52
339	MA1145.1	FOSL2::JUND	MA1145.1	2.7e-55	2.36e-52
340	MA0808.1	TEAD3	MA0808.1	1.58e-54	1.38e-51
341	MA0817.1	BHLHE23	MA0817.1	3.45e-53	3.02e-50
342	MA0466.3	CEBPB	MA0466.3	6.53e-53	5.7e-50
343	MA1718.1	ZNF8	MA1718.1	1.15e-52	1.01e-49
344	MA0651.2	HOXC11	MA0651.2	2.46e-52	2.15e-49
345	MA1956.1	FOXO1::FLI1	MA1956.1	4.41e-52	3.86e-49
346	MA1151.1	RORC	MA1151.1	2.94e-51	2.57e-48
347	MA0492.1	JUND	MA0492.1	4.9e-51	4.28e-48
348	MA1720.1	ZNF85	MA1720.1	1.44e-50	1.26e-47
349	MA0773.1	MEF2D	MA0773.1	1.77e-50	1.55e-47
350	MA0619.1	LIN54	MA0619.1	2.37e-50	2.07e-47
351	MA1105.2	GRHL2	MA1105.2	5.87e-50	5.13e-47
352	MA0517.1	STAT1::STAT2	MA0517.1	1.37e-49	1.2e-46
353	MA1953.1	FOXO1::ELF1	MA1953.1	2.22e-49	1.94e-46
354	MA1975.1	ZNF214	MA1975.1	6.42e-49	5.61e-46
355	MA1129.1	FOSL1::JUN	MA1129.1	8.95e-49	7.82e-46
356	MA0826.1	OLIG1	MA0826.1	1.31e-48	1.15e-45
357	MA0488.1	JUN	MA0488.1	5.49e-47	4.8e-44
358	MA0124.2	Nkx3-1	MA0124.2	9.1e-47	7.96e-44
359	MA0829.2	SREBF1	MA0829.2	1.05e-46	9.21e-44
360	MA1108.2	MXI1	MA1108.2	1.06e-46	9.29e-44
361	MA0756.2	ONECUT2	MA0756.2	3.6e-46	3.15e-43
362	MA0594.2	HOXA9	MA0594.2	4.83e-46	4.22e-43
363	MA0660.1	MEF2B	MA0660.1	5.97e-46	5.21e-43
364	MA1989.1	Bcl11B	MA1989.1	8.43e-46	7.37e-43
365	MA1534.1	NR1I3	MA1534.1	8.93e-46	7.81e-43
366	MA0093.3	USF1	MA0093.3	2.6e-45	2.27e-42
367	MA1547.2	PITX2	MA1547.2	3.1e-42	2.71e-39
45	2-ATRYAT	STREME-2	2-ATRYAT	3.94e-305	2.82e-39
369	MA1593.1	ZNF317	MA1593.1	6.77e-41	5.91e-38
371	MA1980.1	ZNF418	MA1980.1	3.7e-39	3.24e-36
372	MA1523.1	MSANTD3	MA1523.1	3.74e-39	3.27e-36
373	MA0595.1	SREBF1	MA0595.1	2.25e-38	1.97e-35
374	MA1421.1	TCF7L1	MA1421.1	2.59e-38	2.26e-35
376	MA0647.1	GRHL1	MA0647.1	4.04e-37	3.53e-34
377	MA1592.1	ZNF274	MA1592.1	4.2e-37	3.67e-34
378	MA1136.1	FOSB::JUNB	MA1136.1	2.04e-36	1.78e-33
379	MA0684.2	RUNX3	MA0684.2	3.58e-35	3.13e-32
380	MA1570.1	TFAP4	MA1570.1	4.87e-35	4.26e-32
381	MA1121.1	TEAD2	MA1121.1	4.92e-35	4.3e-32
383	MA1952.1	FOXJ2::ELF1	MA1952.1	9.13e-35	7.98e-32
384	MA0743.2	SCRT1	MA0743.2	1.08e-34	9.4e-32
386	MA0518.1	Stat4	MA0518.1	3.87e-34	3.38e-31
387	MA0719.1	RHOXF1	MA0719.1	4.19e-34	3.66e-31
388	MA1111.1	NR2F2	MA1111.1	3.63e-33	3.18e-30
389	MA0137.3	STAT1	MA0137.3	3.74e-33	3.27e-30
390	MA1618.1	Ptf1a	MA1618.1	1.18e-32	1.03e-29
391	MA0687.1	SPIC	MA0687.1	1.51e-32	1.32e-29
392	MA0840.1	Creb5	MA0840.1	1.94e-32	1.69e-29
393	MA2001.1	Six4	MA2001.1	2.57e-32	2.25e-29
394	MA0164.1	Nr2e3	MA0164.1	3.14e-32	2.75e-29
61	MA0148.4 (FOXA1)	STREME-3	3-AAACAT	9.96e-305	1.14e-28
395	MA0485.2	HOXC9	MA0485.2	1.59e-31	1.39e-28
399	MA1644.1	NFYC	MA1644.1	1.67e-28	1.46e-25
401	MA1585.1	ZKSCAN1	MA1585.1	1.84e-27	1.61e-24
402	MA0623.2	NEUROG1	MA0623.2	2.36e-27	2.06e-24
404	MA0703.2	LMX1B	MA0703.2	1.99e-26	1.74e-23
33	MA1137.1 (FOSL1::JUNB)	STREME-4	4-ATGACTA	2.59e-305	6e-22
405	MA0072.1	RORA	MA0072.1	8.03e-25	7.01e-22
406	MA0669.1	NEUROG2	MA0669.1	8.84e-25	7.72e-22
407	MA1521.1	MAFA	MA1521.1	1.18e-24	1.03e-21
409	MA0508.3	PRDM1	MA0508.3	5.89e-24	5.15e-21
130	MA0041.2 (FOXD3)	STREME-5	5-AAATAA	3.75e-210	9.88e-21
411	MA1524.2	Msgn1	MA1524.2	1.45e-23	1.27e-20
413	MA0607.2	BHLHA15	MA0607.2	3.42e-23	2.99e-20
414	MA0804.1	TBX19	MA0804.1	3.78e-23	3.3e-20
415	MA0498.2	MEIS1	MA0498.2	6.75e-23	5.9e-20
416	MA1123.2	TWIST1	MA1123.2	1.68e-22	1.47e-19
417	MA0800.1	EOMES	MA0800.1	4.57e-21	3.99e-18
418	MA0519.1	Stat5a::Stat5b	MA0519.1	5.86e-21	5.12e-18
419	MA1624.1	Stat5a	MA1624.1	1.88e-20	1.64e-17
420	MA0494.1	Nr1h3::Rxra	MA0494.1	2.4e-20	2.1e-17
421	MA1594.1	ZNF382	MA1594.1	5.19e-20	4.53e-17
338	MA1547.2 (PITX2)	MEME-3	GCCTGTAATCCCAGC	1.9e-55	4.6e-16
109	6-ATTACA	STREME-6	6-ATTACA	2.12e-224	6.37e-16
422	MA1133.1	JUN::JUNB	MA1133.1	9.86e-19	8.62e-16
423	MA1148.1	PPARA::RXRA	MA1148.1	4.78e-18	4.18e-15
424	TGTGTRTGTGTGTGT	MEME-4	TGTGTRTGTGTGTGT	5.63e-18	5.4e-15
425	MA0802.1	TBR1	MA0802.1	1.19e-17	1.04e-14
426	MA1995.1	Npas4	MA1995.1	1.9e-17	1.66e-14
427	MA0698.1	ZBTB18	MA0698.1	2.81e-17	2.46e-14
428	MA0610.1	DMRT3	MA0610.1	5.11e-17	4.47e-14
73	7-WAGAGAW	STREME-7	7-WAGAGAW	2.09e-272	1.02e-13
429	MA1587.1	ZNF135	MA1587.1	2.62e-16	2.29e-13
431	MA0114.4	HNF4A	MA0114.4	1.31e-15	1.15e-12
432	MA0744.2	SCRT2	MA0744.2	4.1e-15	3.58e-12
433	MA0484.2	HNF4G	MA0484.2	4.28e-15	3.74e-12
434	MA0019.1	Ddit3::Cebpa	MA0019.1	7.23e-15	6.32e-12
436	MA0818.2	BHLHE22	MA0818.2	1.31e-14	1.14e-11
119	8-BTTSAAV	STREME-8	8-BTTSAAV	3.32e-219	2.65e-11
437	MA1114.1	PBX3	MA1114.1	5.01e-14	4.38e-11
438	MA0463.2	BCL6	MA0463.2	1.54e-13	1.34e-10
439	MA0688.1	TBX2	MA0688.1	4.77e-13	4.17e-10
440	MA0770.1	HSF2	MA0770.1	9e-13	7.86e-10
441	MA0071.1	RORA	MA0071.1	1.8e-12	1.57e-09
370	MA1596.1 (ZNF460)	MEME-5	TTTGGGAGGCYGAGG	9.78e-40	1.8e-09
442	MA1525.2	NFATC4	MA1525.2	9.09e-12	7.94e-09
443	MA0656.1	JDP2	MA0656.1	1.39e-11	1.22e-08
444	MA1955.1	FOXO1::ELK3	MA1955.1	1.62e-11	1.42e-08
445	MA0141.3	ESRRB	MA0141.3	2.06e-11	1.8e-08
160	9-AAWWTT	STREME-9	9-AAWWTT	3.17e-188	3.66e-08
446	MA0160.2	NR4A2	MA0160.2	6.65e-11	5.82e-08
447	MA0805.1	TBX1	MA0805.1	1.42e-10	1.24e-07
448	MA0066.1	PPARG	MA0066.1	3.11e-10	2.72e-07
449	MA1155.1	ZSCAN4	MA1155.1	3.81e-10	3.33e-07
450	MA0866.1	SOX21	MA0866.1	5.77e-10	5.04e-07
451	MA1645.1	NKX2-2	MA1645.1	7.49e-10	6.55e-07
452	MA1996.1	Nr1H2	MA1996.1	1.46e-09	1.27e-06
453	MA1468.1	ATOH7	MA1468.1	1.63e-09	1.43e-06
454	MA0486.2	HSF1	MA0486.2	1.83e-09	1.6e-06
455	MA0002.2	Runx1	MA0002.2	2.46e-09	2.15e-06
457	MA1596.1	ZNF460	MA1596.1	3.92e-09	3.43e-06
458	MA0728.1	Nr2F6	MA0728.1	6.05e-09	5.29e-06
460	MA0060.3	NFYA	MA0060.3	7.93e-09	6.93e-06
461	MA0828.2	SREBF2	MA0828.2	9.51e-09	8.31e-06
462	MA1714.1	ZNF675	MA1714.1	1.43e-08	1.25e-05
463	MA0831.3	TFE3	MA0831.3	1.56e-08	1.37e-05
464	MA1625.1	Stat5b	MA1625.1	2.37e-08	2.07e-05
25	MA0476.1 (FOS)	STREME-10	10-TGANTCA	7.22e-305	2.37e-05
88	MA0108.2 (TBP)	STREME-11	11-TWTAWA	2.2e-260	8.9e-05
465	MA1546.1	PAX3	MA1546.1	3.4e-07	0.000297
466	MA0673.1	NKX2-8	MA0673.1	3.88e-07	0.000339
467	MA0870.1	Sox1	MA0870.1	4.78e-07	0.000418
468	MA0797.1	TGIF2	MA0797.1	5.24e-07	0.000458
469	MA0051.1	IRF2	MA0051.1	5.54e-07	0.000485
368	MA1973.1 (ZKSCAN3)	STREME-12	12-CCAGCCTGGGCAACA	3.44e-42	0.000486
397	MA1716.1 (ZNF76)	STREME-13	13-GCACTTTGGGAGGC	4.92e-29	0.000877
470	MA0130.1	ZNF354C	MA0130.1	1.03e-06	0.000897
471	MA1541.1	NR6A1	MA1541.1	1.06e-06	0.00093
472	MA1943.1	ETV2::HOXB13	MA1943.1	1.34e-06	0.00117
473	MA0653.1	IRF9	MA0653.1	1.92e-06	0.00167
474	MA0859.1	Rarg	MA0859.1	2.23e-06	0.00195
475	MA1642.1	NEUROG2	MA1642.1	2.61e-06	0.00228
476	MA1467.2	Atoh1	MA1467.2	2.84e-06	0.00248
477	MA1419.1	IRF4	MA1419.1	2.94e-06	0.00257
478	MA0511.2	RUNX2	MA0511.2	3.07e-06	0.00268
479	MA0009.2	TBXT	MA0009.2	3.33e-06	0.00291
480	MA1950.1	FLI1::FOXI1	MA1950.1	4.38e-06	0.00383
481	MA1937.1	ERF::HOXB13	MA1937.1	5.36e-06	0.00469
412	14-AGTAGCTGG	STREME-14	14-AGTAGCTGG	1.83e-23	0.00473
482	MA1647.2	Prdm4	MA1647.2	5.44e-06	0.00476
483	MA0652.1	IRF8	MA0652.1	8.73e-06	0.00763
484	MA1638.1	HAND2	MA1638.1	9.47e-06	0.00828
396	MA1596.1 (ZNF460)	STREME-15	15-CCTGCCTCAGCCTCC	3.15e-29	0.00982
485	MA0691.1	TFAP4	MA0691.1	1.42e-05	0.0124
382	MA1973.1 (ZKSCAN3)	MEME-6	TGTYGCCCAGGCTGG	6.21e-35	0.013
486	MA0664.1	MLXIPL	MA0664.1	1.49e-05	0.013
487	MA1949.1	FLI1::DRGX	MA1949.1	1.57e-05	0.0137
488	MA0592.3	ESRRA	MA0592.3	1.64e-05	0.0143
400	MA1596.1 (ZNF460)	STREME-17	17-ACCTCTGCCTCCCAG	8.58e-28	0.0245
410	MA1107.2 (KLF9)	STREME-16	16-CACACACAC	8.57e-24	0.0245
398	18-ACACAGGCACAC	STREME-18	18-ACACAGGCACAC	7.04e-29	0.0255
291	MA1989.1 (Bcl11B)	STREME-19	19-AAACCA	1.31e-88	0.027
489	MA0795.1	SMAD3	MA0795.1	3.18e-05	0.0278
490	MA1589.1	ZNF140	MA1589.1	3.45e-05	0.0302
430	20-AGTGCAGTG	STREME-20	20-AGTGCAGTG	5.1e-16	0.0303
456	MA0803.1 (TBX15)	STREME-21	21-ACACTCACAC	3.08e-09	0.0321
491	MA1579.1	ZBTB26	MA1579.1	4.26e-05	0.0373
492	MA0643.1	Esrrg	MA0643.1	4.86e-05	0.0425
375	MA1515.1 (KLF2)	STREME-22	22-CCACCACRCCCRGC	1.4e-37	0.0471
459	MA1990.1 (Gli1)	STREME-23	23-ACACACCACACACA	7.92e-09	0.0525
408	MA1990.1 (Gli1)	STREME-24	24-CACACCACACAC	5.81e-24	0.055
435	25-ACCCACACAC	STREME-25	25-ACCCACACAC	1.06e-14	0.0713
385	MA1973.1 (ZKSCAN3)	STREME-26	26-AGACCAGCCTGGSC	2.71e-34	0.154
403	MA0803.1 (TBX15)	STREME-27	27-AGGTGGGAGGAT	8.18e-27	4.34

# LR_close_200xstreme %>% 
#   dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
#   arrange(.,EVALUE) %>%
#    dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
#   # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
#   # dplyr::filter(., EVALUE<0.05) %>% 
#   kable(., caption = "Enriched motifs  in LR close") %>%
#   kable_paper("striped", full_width = TRUE) %>%
#   kable_styling(full_width = FALSE, font_size = 16) %>%
#   scroll_box(height = "800px")
LR_close_200xstreme %>% 
  dplyr::select(RANK,SIM_MOTIF,ALT_ID, ID,SEA_PVALUE,EVALUE) %>% 
  arrange(.,EVALUE) %>%
   dplyr::mutate_if(is.numeric, funs(as.character(signif(., 3)))) %>%
  # separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  # dplyr::filter(., EVALUE<0.05) %>% 
  kable(., caption = "Enriched motifs in LR close, 200bp") %>%
  kable_paper("striped", full_width = TRUE) %>%
  kable_styling(full_width = FALSE, font_size = 16) %>%
  scroll_box(height = "800px")

Enriched motifs in LR close, 200bp
RANK	SIM_MOTIF	ALT_ID	ID	SEA_PVALUE	EVALUE
3	MA0774.1	MEIS2	MA0774.1	1.5e-109	1.3e-106
6	MA0775.1	MEIS3	MA0775.1	6.73e-67	5.82e-64
8	MA0672.1	NKX2-3	MA0672.1	4.18e-59	3.61e-56
11	MA2003.1	NKX2-4	MA2003.1	4.68e-53	4.05e-50
12	MA0673.1	NKX2-8	MA0673.1	1.63e-52	1.41e-49
325	MA1125.1 (ZNF384)	MEME-1	TTTTTTTTTTTTTTT	0.746	1.8e-47
13	MA0789.1	POU3F4	MA0789.1	6.61e-50	5.72e-47
14	MA0766.2	GATA5	MA0766.2	1.5e-48	1.3e-45
15	MA0498.2	MEIS1	MA0498.2	2.82e-46	2.44e-43
16	MA0792.1	POU5F1B	MA0792.1	3.06e-44	2.64e-41
18	MA0845.1	FOXB1	MA0845.1	1.04e-42	8.98e-40
19	MA0052.4	MEF2A	MA0052.4	1.32e-42	1.14e-39
20	MA0786.1	POU3F1	MA0786.1	1.5e-42	1.29e-39
21	MA0722.1	VAX1	MA0722.1	2.93e-41	2.54e-38
22	MA0124.2	Nkx3-1	MA0124.2	2.44e-40	2.11e-37
24	MA0785.1	POU2F1	MA0785.1	8.52e-40	7.37e-37
25	MA0797.1	TGIF2	MA0797.1	3.67e-39	3.18e-36
26	MA0718.1	RAX	MA0718.1	8.36e-39	7.23e-36
27	MA0720.1	Shox2	MA0720.1	8.88e-39	7.68e-36
28	MA0788.1	POU3F3	MA0788.1	1.08e-38	9.38e-36
29	MA1113.2	PBX2	MA1113.2	1.24e-38	1.08e-35
30	MA0710.1	NOTO	MA0710.1	1.39e-38	1.2e-35
31	MA0787.1	POU3F2	MA0787.1	1.94e-38	1.68e-35
33	MA0671.1	NFIX	MA0671.1	3.39e-38	2.94e-35
34	MA0650.3	Hoxa13	MA0650.3	1.13e-37	9.76e-35
35	MA0627.2	POU2F3	MA0627.2	1.81e-37	1.56e-34
322	MA1723.1 (PRDM9)	MEME-2	GGVAGGGVRRGRRRG	0.00232	1.9e-34
36	MA0670.1	NFIA	MA0670.1	2.8e-37	2.42e-34
37	MA0630.1	SHOX	MA0630.1	3.8e-37	3.29e-34
38	MA0626.1	Npas2	MA0626.1	5.05e-37	4.37e-34
39	MA0704.1	Lhx4	MA0704.1	1.29e-36	1.12e-33
40	MA0725.1	VSX1	MA0725.1	1.82e-36	1.57e-33
41	MA0036.3	GATA2	MA0036.3	1.86e-36	1.61e-33
42	MA1963.1	SATB1	MA1963.1	2.04e-36	1.76e-33
43	MA0031.1	FOXD1	MA0031.1	7.39e-35	6.39e-32
44	MA0809.2	TEAD4	MA0809.2	9.23e-35	7.99e-32
45	MA1104.2	GATA6	MA1104.2	1.42e-34	1.23e-31
46	MA0602.1	Arid5a	MA0602.1	1.82e-34	1.57e-31
47	MA0644.2	ESX1	MA0644.2	1.85e-34	1.6e-31
48	MA0901.2	HOXB13	MA0901.2	2.13e-34	1.84e-31
49	MA0047.3	FOXA2	MA0047.3	3.75e-34	3.24e-31
50	MA0808.1	TEAD3	MA0808.1	3.84e-34	3.33e-31
51	MA0700.2	LHX2	MA0700.2	4.45e-34	3.85e-31
52	MA0092.1	Hand1::Tcf3	MA0092.1	7.46e-34	6.45e-31
53	MA0125.1	Nobox	MA0125.1	9.09e-34	7.87e-31
54	MA0674.1	NKX6-1	MA0674.1	1.2e-33	1.03e-30
55	MA1978.1	ZNF354A	MA1978.1	2.51e-33	2.17e-30
56	MA0790.1	POU4F1	MA0790.1	2.64e-33	2.28e-30
57	MA0846.1	FOXC2	MA0846.1	3.72e-33	3.22e-30
58	MA0084.1	SRY	MA0084.1	5.01e-33	4.33e-30
59	MA0680.2	Pax7	MA0680.2	5.8e-33	5.01e-30
60	MA0142.1	Pou5f1::Sox2	MA0142.1	1.2e-32	1.03e-29
61	MA0882.1	DLX6	MA0882.1	1.56e-32	1.35e-29
62	MA0726.1	VSX2	MA0726.1	4.02e-32	3.47e-29
63	MA0497.1	MEF2C	MA0497.1	4.55e-32	3.93e-29
64	MA0033.2	FOXL1	MA0033.2	4.99e-32	4.31e-29
65	MA0027.2	EN1	MA0027.2	1.08e-31	9.31e-29
67	MA0465.2	CDX2	MA0465.2	1.63e-31	1.41e-28
68	MA1640.1	MEIS2	MA1640.1	2.4e-31	2.07e-28
69	MA0032.2	FOXC1	MA0032.2	4.1e-31	3.54e-28
70	MA1994.1	Nkx2-1	MA1994.1	7.83e-31	6.77e-28
71	MA0709.1	Msx3	MA0709.1	1.45e-30	1.26e-27
72	MA0675.1	NKX6-2	MA0675.1	2.46e-30	2.13e-27
73	MA1115.1	POU5F1	MA1115.1	2.47e-30	2.13e-27
75	MA1481.1	DRGX	MA1481.1	6.93e-30	6e-27
77	MA0077.1	SOX9	MA0077.1	1.96e-29	1.7e-26
78	MA1476.2	Dlx5	MA1476.2	3.61e-29	3.13e-26
79	MA0634.1	ALX3	MA0634.1	7.33e-29	6.34e-26
80	MA0723.2	VAX2	MA0723.2	8.21e-29	7.11e-26
81	MA1563.2	SOX18	MA1563.2	1.22e-28	1.05e-25
82	MA0628.1	POU6F1	MA0628.1	1.45e-28	1.25e-25
83	MA0635.1	BARHL2	MA0635.1	1.84e-28	1.59e-25
84	MA1970.1	TRPS1	MA1970.1	1.94e-28	1.68e-25
85	MA0654.1	ISX	MA0654.1	3.13e-28	2.7e-25
86	MA0793.1	POU6F2	MA0793.1	4.06e-28	3.51e-25
87	MA0880.1	Dlx3	MA0880.1	7.21e-28	6.24e-25
88	MA0890.1	GBX2	MA0890.1	8.73e-28	7.55e-25
89	MA0601.1	Arid3b	MA0601.1	9.82e-28	8.49e-25
90	MA0885.2	Dlx2	MA0885.2	9.96e-28	8.62e-25
91	MA0495.3	MAFF	MA0495.3	1.1e-27	9.49e-25
92	MA1505.1	HOXC8	MA1505.1	3.17e-27	2.74e-24
93	MA0881.1	Dlx4	MA0881.1	3.76e-27	3.25e-24
94	MA1683.1	FOXA3	MA1683.1	7.17e-27	6.2e-24
95	MA1997.1	Olig2	MA1997.1	2.04e-26	1.76e-23
96	MA0894.1	HESX1	MA0894.1	2.27e-26	1.97e-23
97	MA0481.3	FOXP1	MA0481.3	2.66e-26	2.3e-23
98	MA0025.2	NFIL3	MA0025.2	3.08e-26	2.67e-23
99	MA1607.1	Foxl2	MA1607.1	3.73e-26	3.23e-23
100	MA0037.4	Gata3	MA0037.4	6.41e-26	5.55e-23
101	MA0633.2	Twist2	MA0633.2	6.65e-26	5.75e-23
102	MA1993.1	Neurod2	MA1993.1	7.88e-26	6.82e-23
103	MA0132.2	PDX1	MA0132.2	9.28e-26	8.02e-23
104	MA0108.2	TBP	MA0108.2	1.17e-25	1.01e-22
106	MA0739.1	Hic1	MA0739.1	2.34e-25	2.02e-22
107	MA1635.1	BHLHE22	MA1635.1	3.55e-25	3.08e-22
108	MA0681.2	PHOX2B	MA0681.2	4.44e-25	3.84e-22
109	MA0514.2	Sox3	MA0514.2	4.92e-25	4.26e-22
110	MA0666.2	MSX1	MA0666.2	5.24e-25	4.53e-22
111	MA1103.2	FOXK2	MA1103.2	5.48e-25	4.74e-22
112	MA0679.2	ONECUT1	MA0679.2	5.54e-25	4.79e-22
113	MA0148.4	FOXA1	MA0148.4	6.02e-25	5.21e-22
114	MA0848.1	FOXO4	MA0848.1	9.4e-25	8.14e-22
115	MA0889.1	GBX1	MA0889.1	1.06e-24	9.13e-22
116	MA0783.1	PKNOX2	MA0783.1	1.8e-24	1.56e-21
117	MA1606.1	Foxf1	MA1606.1	1.88e-24	1.62e-21
118	MA0899.1	HOXA10	MA0899.1	2.34e-24	2.03e-21
119	MA1120.1	SOX13	MA1120.1	2.88e-24	2.49e-21
120	MA0041.2	FOXD3	MA0041.2	3.48e-24	3.01e-21
121	MA1152.1	SOX15	MA1152.1	3.68e-24	3.18e-21
122	MA0523.1	TCF7L2	MA0523.1	3.98e-24	3.44e-21
123	MA0791.1	POU4F3	MA0791.1	5.14e-24	4.45e-21
124	MA0724.1	VENTX	MA0724.1	7.07e-24	6.11e-21
125	MA1489.1	FOXN3	MA1489.1	7.94e-24	6.86e-21
126	MA0708.2	MSX2	MA0708.2	1.03e-23	8.88e-21
127	MA1471.1	BARX2	MA1471.1	1.36e-23	1.18e-20
128	MA1639.1	MEIS1	MA1639.1	2.21e-23	1.91e-20
129	MA0879.2	DLX1	MA0879.2	2.49e-23	2.15e-20
130	MA0642.2	EN2	MA0642.2	3.06e-23	2.64e-20
131	MA0143.4	SOX2	MA0143.4	4.75e-23	4.11e-20
132	MA0521.2	Tcf12	MA0521.2	7.08e-23	6.13e-20
133	MA0035.4	GATA1	MA0035.4	1.27e-22	1.1e-19
134	MA0769.2	TCF7	MA0769.2	1.89e-22	1.64e-19
135	MA0676.1	Nr2e1	MA0676.1	2.55e-22	2.21e-19
136	MA0886.1	EMX2	MA0886.1	3.26e-22	2.82e-19
137	MA0717.1	RAX2	MA0717.1	3.32e-22	2.87e-19
138	MA0151.1	Arid3a	MA0151.1	5.77e-22	5e-19
139	MA0669.1	NEUROG2	MA0669.1	6.39e-22	5.52e-19
140	MA0119.1	NFIC::TLX1	MA0119.1	6.79e-22	5.88e-19
141	MA0876.1	BSX	MA0876.1	1.42e-21	1.23e-18
142	MA0868.2	SOX8	MA0868.2	1.6e-21	1.39e-18
143	MA1974.1	ZNF211	MA1974.1	2.34e-21	2.02e-18
144	MA1498.2	HOXA7	MA1498.2	3.75e-21	3.24e-18
145	MA0711.1	OTX1	MA0711.1	4.67e-21	4.04e-18
146	MA1502.1	HOXB8	MA1502.1	5.77e-21	4.99e-18
147	MA0614.1	Foxj2	MA0614.1	6.11e-21	5.29e-18
148	MA0716.1	PRRX1	MA0716.1	8.76e-21	7.58e-18
149	MA1643.1	NFIB	MA1643.1	9.17e-21	7.93e-18
150	MA0042.2	FOXI1	MA0042.2	1.25e-20	1.08e-17
151	MA0068.2	PAX4	MA0068.2	2.28e-20	1.97e-17
152	MA0161.2	NFIC	MA0161.2	2.53e-20	2.19e-17
153	MA0706.1	MEOX2	MA0706.1	4.33e-20	3.74e-17
154	MA1112.2	NR4A1	MA1112.2	7.35e-20	6.35e-17
155	MA0713.1	PHOX2A	MA0713.1	9.3e-20	8.05e-17
156	MA0122.3	Nkx3-2	MA0122.3	1.13e-19	9.78e-17
157	MA0078.2	Sox17	MA0078.2	1.17e-19	1.01e-16
158	MA0648.1	GSC	MA0648.1	1.99e-19	1.73e-16
159	MA1121.1	TEAD2	MA1121.1	5.23e-19	4.53e-16
160	MA1608.1	Isl1	MA1608.1	5.72e-19	4.95e-16
161	MA0914.1	ISL2	MA0914.1	7.14e-19	6.18e-16
162	MA0623.2	NEUROG1	MA0623.2	7.84e-19	6.78e-16
163	MA1549.1	POU6F1	MA1549.1	1.29e-18	1.11e-15
164	MA0909.3	Hoxd13	MA0909.3	1.36e-18	1.17e-15
165	MA0461.2	Atoh1	MA0461.2	1.41e-18	1.22e-15
166	MA0910.2	HOXD8	MA0910.2	1.97e-18	1.7e-15
167	MA1497.1	HOXA6	MA1497.1	2.07e-18	1.79e-15
168	MA1636.1	CEBPG	MA1636.1	3.28e-18	2.84e-15
169	MA0618.1	LBX1	MA0618.1	5.01e-18	4.33e-15
170	MA1571.1	TGIF2LX	MA1571.1	5.93e-18	5.13e-15
171	MA0712.2	OTX2	MA0712.2	6.31e-18	5.46e-15
172	MA1562.1	SOX14	MA1562.1	7.96e-18	6.88e-15
173	MA0090.3	TEAD1	MA0090.3	1.84e-17	1.59e-14
175	MA0898.1	Hmx3	MA0898.1	4.26e-17	3.68e-14
176	MA1960.1	MGA::EVX1	MA1960.1	5.11e-17	4.42e-14
177	MA0667.1	MYF6	MA0667.1	6.66e-17	5.76e-14
178	MA0903.1	HOXB3	MA0903.1	1e-16	8.68e-14
179	MA1645.1	NKX2-2	MA1645.1	5.33e-16	4.61e-13
180	MA1619.1	Ptf1A	MA1619.1	5.76e-16	4.98e-13
181	MA0606.2	Nfat5	MA0606.2	6.14e-16	5.31e-13
182	MA0904.2	HOXB5	MA0904.2	1.27e-15	1.1e-12
1	MA0774.1 (MEIS2)	STREME-1	1-STGMCAG	2.05e-148	1.54e-12
183	MA1500.1	HOXB6	MA1500.1	1.8e-15	1.56e-12
184	MA0157.3	Foxo3	MA0157.3	1.88e-15	1.62e-12
185	MA0699.1	LBX2	MA0699.1	2.85e-15	2.47e-12
186	MA1487.2	FOXE1	MA1487.2	3.64e-15	3.15e-12
316	MA0496.3 (MAFK)	MEME-3	RGGCTGRG	3.76e-05	3.2e-12
187	MA0500.2	MYOG	MA0500.2	8.57e-15	7.42e-12
188	MA0063.2	NKX2-5	MA0063.2	9.6e-15	8.3e-12
189	MA0102.4	CEBPA	MA0102.4	9.65e-15	8.34e-12
190	MA0849.1	FOXO6	MA0849.1	1.11e-14	9.63e-12
191	MA1480.1	DPRX	MA1480.1	1.15e-14	9.97e-12
192	MA0887.1	EVX1	MA0887.1	1.4e-14	1.22e-11
193	MA0140.2	GATA1::TAL1	MA0140.2	1.48e-14	1.28e-11
194	MA1657.1	ZNF652	MA1657.1	1.76e-14	1.52e-11
195	MA1501.1	HOXB7	MA1501.1	2.09e-14	1.81e-11
196	MA0721.1	UNCX	MA0721.1	3.17e-14	2.74e-11
197	MA1472.2	Bhlha15	MA1472.2	3.24e-14	2.8e-11
198	MA0826.1	OLIG1	MA0826.1	3.75e-14	3.24e-11
199	MA1504.1	HOXC4	MA1504.1	3.85e-14	3.33e-11
200	MA0682.2	PITX1	MA0682.2	5.53e-14	4.78e-11
201	MA0875.1	BARX1	MA0875.1	6.04e-14	5.23e-11
202	MA1709.1	ZIM3	MA1709.1	6.6e-14	5.7e-11
203	MA0768.2	Lef1	MA0768.2	6.71e-14	5.8e-11
204	MA0892.1	GSX1	MA0892.1	7.57e-14	6.55e-11
2	MA0498.2 (MEIS1)	STREME-2	2-CTGTCADCAC	1.93e-116	8.05e-11
205	MA1479.1	DMRTC2	MA1479.1	1.05e-13	9.11e-11
206	MA0897.1	Hmx2	MA0897.1	1.97e-13	1.71e-10
207	MA0714.1	PITX3	MA0714.1	2.07e-13	1.79e-10
208	MA1593.1	ZNF317	MA1593.1	2.28e-13	1.97e-10
209	MA0816.1	Ascl2	MA0816.1	3.86e-13	3.34e-10
210	MA1707.1	DMRTA1	MA1707.1	4.05e-13	3.5e-10
211	MA0738.1	HIC2	MA0738.1	4.32e-13	3.74e-10
212	MA1468.1	ATOH7	MA1468.1	8.28e-13	7.16e-10
213	MA0877.3	BARHL1	MA0877.3	8.69e-13	7.52e-10
214	MA0802.1	TBR1	MA0802.1	9.31e-13	8.06e-10
215	MA0896.1	Hmx1	MA0896.1	1.03e-12	8.91e-10
216	MA0835.2	BATF3	MA0835.2	1.76e-12	1.52e-09
217	MA1641.1	MYF5	MA1641.1	1.81e-12	1.57e-09
218	MA1495.1	HOXA1	MA1495.1	1.88e-12	1.62e-09
219	MA0847.3	FOXD2	MA0847.3	1.93e-12	1.67e-09
220	MA0091.1	TAL1::TCF3	MA0091.1	2.1e-12	1.82e-09
221	MA1463.1	ARGFX	MA1463.1	2.39e-12	2.07e-09
222	MA0662.1	MIXL1	MA0662.1	2.62e-12	2.27e-09
324	MA1107.2 (KLF9)	MEME-4	GTGTGTGTGTGTGTG	0.651	2.8e-09
223	MA0755.1	CUX2	MA0755.1	3.38e-12	2.92e-09
224	MA0707.2	MNX1	MA0707.2	1.32e-11	1.14e-08
225	MA0018.4	CREB1	MA0018.4	1.43e-11	1.23e-08
226	MA0070.1	PBX1	MA0070.1	1.64e-11	1.42e-08
227	MA0442.2	SOX10	MA0442.2	2.06e-11	1.78e-08
228	MA0715.1	PROP1	MA0715.1	2.68e-11	2.32e-08
229	MA0144.2	STAT3	MA0144.2	3.81e-11	3.3e-08
230	MA0698.1	ZBTB18	MA0698.1	3.91e-11	3.38e-08
231	MA0836.2	CEBPD	MA0836.2	4.16e-11	3.6e-08
232	MA0043.3	HLF	MA0043.3	4.48e-11	3.88e-08
233	MA0850.1	FOXP3	MA0850.1	5.07e-11	4.38e-08
234	MA0607.2	BHLHA15	MA0607.2	6.01e-11	5.19e-08
4	MA0672.1 (NKX2-3)	STREME-3	3-STCAAGTGS	7.96e-82	6.92e-08
235	MA1572.1	TGIF2LY	MA1572.1	8.87e-11	7.67e-08
236	MA1478.1	DMRTA2	MA1478.1	8.88e-11	7.68e-08
237	MA0817.1	BHLHE23	MA0817.1	1.06e-10	9.18e-08
238	MA1530.1	NKX6-3	MA1530.1	1.54e-10	1.33e-07
239	MA1588.1	ZNF136	MA1588.1	1.55e-10	1.34e-07
240	MA0832.1	Tcf21	MA0832.1	1.56e-10	1.35e-07
241	MA0095.3	Yy1	MA0095.3	1.88e-10	1.63e-07
23	4-AWATWT	STREME-4	4-AWATWT	5.35e-40	2.23e-07
242	MA0891.1	GSC2	MA0891.1	3.27e-10	2.83e-07
243	MA0060.3	NFYA	MA0060.3	3.74e-10	3.23e-07
244	MA1991.1	Hnf1A	MA1991.1	4.66e-10	4.03e-07
245	MA0482.2	GATA4	MA0482.2	5.42e-10	4.68e-07
246	MA0867.2	SOX4	MA0867.2	9.75e-10	8.43e-07
247	MA1603.1	Dmrt1	MA1603.1	1.02e-09	8.78e-07
248	MA0827.1	OLIG3	MA0827.1	1.16e-09	1e-06
249	MA0624.2	Nfatc1	MA0624.2	1.38e-09	1.19e-06
250	MA0893.2	GSX2	MA0893.2	1.57e-09	1.36e-06
251	MA1528.1	NFIX	MA1528.1	2.37e-09	2.05e-06
252	MA0597.2	THAP1	MA0597.2	2.51e-09	2.17e-06
253	MA0851.1	Foxj3	MA0851.1	2.54e-09	2.2e-06
254	MA0462.2	BATF::JUN	MA0462.2	2.56e-09	2.22e-06
255	MA0902.2	HOXB2	MA0902.2	2.65e-09	2.29e-06
256	MA0629.1	Rhox11	MA0629.1	3.14e-09	2.72e-06
257	MA0678.1	OLIG2	MA0678.1	3.18e-09	2.75e-06
258	MA0818.2	BHLHE22	MA0818.2	3.4e-09	2.94e-06
259	MA1518.2	Lhx1	MA1518.2	4.34e-09	3.75e-06
260	MA0152.2	Nfatc2	MA0152.2	4.39e-09	3.8e-06
261	MA1634.1	BATF	MA1634.1	4.8e-09	4.15e-06
262	MA0480.2	Foxo1	MA0480.2	5.59e-09	4.83e-06
10	MA1960.1 (MGA::EVX1)	STREME-5	5-TGATAA	1.67e-54	5.13e-06
7	MA0161.2 (NFIC)	STREME-6	6-GCWTGGCA	7.5e-66	5.38e-06
263	MA1644.1	NFYC	MA1644.1	6.72e-09	5.82e-06
264	MA0050.3	Irf1	MA0050.3	7.31e-09	6.32e-06
265	MA1720.1	ZNF85	MA1720.1	8.15e-09	7.05e-06
5	7-SCAGVCA	STREME-7	7-SCAGVCA	5.41e-77	7.45e-06
266	MA1524.2	Msgn1	MA1524.2	1.36e-08	1.18e-05
267	MA0502.2	NFYB	MA0502.2	1.56e-08	1.35e-05
268	MA1975.1	ZNF214	MA1975.1	1.76e-08	1.52e-05
269	MA0158.2	HOXA5	MA0158.2	1.92e-08	1.66e-05
32	MA0769.2 (TCF7)	STREME-8	8-TTCAAA	2.97e-38	1.7e-05
271	MA0833.2	ATF4	MA0833.2	2.13e-08	1.84e-05
272	MA1638.1	HAND2	MA1638.1	2.32e-08	2e-05
273	MA0895.1	HMBOX1	MA0895.1	2.75e-08	2.38e-05
275	MA0911.1	Hoxa11	MA0911.1	3.3e-08	2.85e-05
276	MA0905.1	HOXC10	MA0905.1	3.3e-08	2.85e-05
277	MA0842.2	NRL	MA0842.2	3.38e-08	2.92e-05
278	MA1118.1	SIX1	MA1118.1	3.8e-08	3.28e-05
306	MA0471.2 (E2F6)	MEME-5	CAGGCTGGAGKGCAG	9.7e-06	4.5e-05
279	MA0853.1	Alx4	MA0853.1	6.82e-08	5.9e-05
280	MA0854.1	Alx1	MA0854.1	7.26e-08	6.28e-05
281	MA0852.2	FOXK1	MA0852.2	7.93e-08	6.86e-05
282	MA0805.1	TBX1	MA0805.1	9.89e-08	8.56e-05
283	MA1547.2	PITX2	MA1547.2	1.06e-07	9.2e-05
323	MA1107.2 (KLF9)	MEME-6	TGTGTGTGTGTGTGT	0.168	0.00011
284	MA1573.2	Thap11	MA1573.2	1.31e-07	0.000113
285	MA1623.1	Stat2	MA1623.1	1.44e-07	0.000125
286	MA0900.2	HOXA2	MA0900.2	1.44e-07	0.000125
287	MA1153.1	Smad4	MA1153.1	1.47e-07	0.000127
288	MA1728.1	ZNF549	MA1728.1	1.87e-07	0.000162
289	MA0803.1	TBX15	MA0803.1	1.87e-07	0.000162
290	MA0661.1	MEOX1	MA0661.1	2.72e-07	0.000235
17	MA1645.1 (NKX2-2)	STREME-9	9-CCWCTCA	1.67e-43	0.000328
291	MA0830.2	TCF4	MA0830.2	4.26e-07	0.000368
292	MA1114.1	PBX3	MA1114.1	5.05e-07	0.000437
293	MA0160.2	NR4A2	MA0160.2	5.15e-07	0.000445
294	MA0754.2	CUX1	MA0754.2	9.36e-07	0.00081
295	MA1625.1	Stat5b	MA1625.1	9.56e-07	0.000827
296	MA0690.2	TBX21	MA0690.2	1.73e-06	0.0015
297	MA0693.3	Vdr	MA0693.3	1.81e-06	0.00157
298	MA1618.1	Ptf1a	MA1618.1	2.46e-06	0.00213
299	MA0878.3	CDX1	MA0878.3	2.82e-06	0.00244
300	MA1125.1	ZNF384	MA1125.1	3.15e-06	0.00272
174	MA1731.1 (ZNF768)	STREME-10	10-CCAGAG	3.54e-17	0.00332
301	MA1467.2	Atoh1	MA1467.2	4e-06	0.00346
302	MA0668.2	Neurod2	MA0668.2	7.32e-06	0.00633
303	MA0087.2	Sox5	MA0087.2	7.53e-06	0.00652
304	MA1519.1	LHX5	MA1519.1	8.25e-06	0.00714
305	MA1102.2	CTCFL	MA1102.2	9.15e-06	0.00791
9	MA0739.1 (Hic1)	STREME-11	11-TGCCAMT	2.37e-57	0.00824
105	MA0668.2 (Neurod2)	STREME-12	12-ATCTGK	1.65e-25	0.00947
274	13-ATTGGAG	STREME-13	13-ATTGGAG	2.97e-08	0.0102
307	MA0883.1	Dmbx1	MA0883.1	1.43e-05	0.0124
308	MA1953.1	FOXO1::ELF1	MA1953.1	1.64e-05	0.0142
309	MA0860.1	Rarg	MA0860.1	1.66e-05	0.0144
310	MA1108.2	MXI1	MA1108.2	1.7e-05	0.0147
311	MA0719.1	RHOXF1	MA0719.1	1.92e-05	0.0166
312	MA1581.1	ZBTB6	MA1581.1	1.93e-05	0.0167
76	MA0138.2 (REST)	STREME-14	14-CTGTCCA	1.76e-29	0.0168
313	MA0083.3	SRF	MA0083.3	2.47e-05	0.0214
314	MA0907.1	HOXC13	MA0907.1	2.57e-05	0.0222
315	MA0688.1	TBX2	MA0688.1	3.12e-05	0.027
317	MA1567.2	Tbx6	MA1567.2	3.96e-05	0.0343
318	MA1151.1	RORC	MA1151.1	4.02e-05	0.0348
319	MA1124.1	ZNF24	MA1124.1	4.1e-05	0.0355
74	MA0773.1 (MEF2D)	STREME-15	15-AATAGA	3.97e-30	0.0359
320	MA1119.1	SIX2	MA1119.1	4.63e-05	0.04
66	16-AGTGCTR	STREME-16	16-AGTGCTR	1.37e-31	1.19
270	17-TACWGTA	STREME-17	17-TACWGTA	2.12e-08	1.23
321	MA0161.2 (NFIC)	STREME-18	18-TCTTGGCCCA	0.00101	3.92

### selecting just the list of names and checking for expression

All enriched motifs found

This area was for all motifs found in Xstreme analysis using NR peaks as background. #### EAR ##### EAR_open

mrc_palette <- c(
    "EAR_open" = "#F8766D",
    "EAR_close" = "#f6483c",
    "ESR_open" = "#7CAE00",
    "ESR_close" = "#587b00",
    "ESR_C"="grey40",
     "ESR_opcl"="grey40",
    "ESR_D"="tan",
     "ESR_clop"="tan",
     "ESR_OC" = "#6a9500",
     "LR_open" = "#00BFC4",
     "LR_close" = "#008d91",
     "NR" = "#C77CFF"
  )

 # spd_EARo<-EAR_open_xstreme%>% 
 #   mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
 #  dplyr::filter(EVALUE<0.05) %>% 
 #  left_join(., (sea_EAR_open %>%
 #                  # dplyr::rename("SEA_PVALUE"=PVALUE) %>%
 #                  dplyr::select(RANK,ID:PVALUE)),
 #            by= c("RANK"="RANK", "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS",  "ID"="ID")) %>% 
 #  separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
 #  mutate(motif_name= gsub("[()]","",NAME), mrc="EAR_open") %>%
 #  mutate(motif_name=
 #           if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
 #           if_else(is.na(motif_name),ID,motif_name))) 
 
 spd_EARo_200<-EAR_open_200xstreme%>% 
   mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
  dplyr::filter(EVALUE<0.05) %>% 
  left_join(., (sea_EAR_open_200_p2 %>%
                  anti_join(.,sea_EAR_open_200, by = c("ID"="ID","ALT_ID"="ALT_ID")) %>%
  rbind(sea_EAR_open_200) %>% 
  dplyr::select(DB:LOG_QVALUE)), by= c( "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS","ID"="ID"))%>% 
  separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  mutate(motif_name= gsub("[()]","",NAME), mrc="EAR_open") %>%
  mutate(motif_name=
           if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
           if_else(is.na(motif_name),ID,motif_name))) 
 #### breaks 
# spd_EARc <- EAR_close_xstreme%>% 
#    mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
#   dplyr::filter(EVALUE<0.05) %>% 
#   left_join(., (sea_EAR_close %>%
#                   # dplyr::rename("SEA_PVALUE"=PVALUE) %>%
#                   dplyr::select(RANK,ID:PVALUE)),
#             by= c("RANK"="RANK", "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS",  "ID"="ID")) %>% 
#   separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
#   mutate(motif_name= gsub("[()]","",NAME), mrc="EAR_close") %>%
#   mutate(motif_name=
#            if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
#            if_else(is.na(motif_name),ID,motif_name)))

spd_EARc_200 <- EAR_close_200xstreme%>% 
   mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
  dplyr::filter(EVALUE<0.05) %>% 
  left_join(., (sea_EAR_close_200_p2 %>%
                  anti_join(.,sea_EAR_close_200, by = c("ID"="ID","ALT_ID"="ALT_ID")) %>%
  rbind(sea_EAR_close_200) %>% 
  dplyr::select(DB:LOG_QVALUE)), by= c( "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS","ID"="ID"))%>% 
  separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  mutate(motif_name= gsub("[()]","",NAME), mrc="EAR_close") %>%
  mutate(motif_name=
           if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
           if_else(is.na(motif_name),ID,motif_name)))


##### breaks
# spd_ESRo <-ESR_open_xstreme%>%
#    mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
#   dplyr::filter(EVALUE<0.05) %>% 
#   left_join(., (sea_ESR_open %>%
#                   # dplyr::rename("SEA_PVALUE"=PVALUE) %>%
#                   dplyr::select(RANK,ID:PVALUE)),
#             by= c("RANK"="RANK", "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS",  "ID"="ID"))%>% 
#   separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
#   mutate(motif_name= gsub("[()]","",NAME), mrc="ESR_open") %>%
#   mutate(motif_name=
#            if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
#            if_else(is.na(motif_name),ID,motif_name)))

spd_ESRo_200 <-ESR_open_200xstreme%>%
   mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>%
  dplyr::filter(EVALUE<0.05) %>%
  left_join(., (sea_ESR_open_200_p2 %>%
                  anti_join(.,sea_ESR_open_200, by = c("ID"="ID","ALT_ID"="ALT_ID")) %>%
  rbind(sea_ESR_open_200) %>% 
  dplyr::select(DB:LOG_QVALUE)), by= c( "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS","ID"="ID"))%>% 
  separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  mutate(motif_name= gsub("[()]","",NAME), mrc="ESR_open") %>%
  mutate(motif_name=
           if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
           if_else(is.na(motif_name),ID,motif_name)))

# spd_ESRc <- ESR_close_xstreme%>% 
#    mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
#   dplyr::filter(EVALUE<0.05) %>% 
#   left_join(., (sea_ESR_close %>%
#                   # dplyr::rename("SEA_PVALUE"=PVALUE) %>%
#                   dplyr::select(RANK,ID:PVALUE)),
#             by= c("RANK"="RANK", "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS",  "ID"="ID")) %>% 
#   separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
#   mutate(motif_name= gsub("[()]","",NAME), mrc="ESR_close") %>%
#   mutate(motif_name=
#            if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
#            if_else(is.na(motif_name),ID,motif_name)))

spd_ESRc_200 <- ESR_close_200xstreme%>% 
   mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
  dplyr::filter(EVALUE<0.05) %>% 
  left_join(., (sea_ESR_close_200_p2 %>%
                  anti_join(.,sea_ESR_close_200, by = c("ID"="ID","ALT_ID"="ALT_ID")) %>%
  rbind(sea_ESR_close_200) %>% 
  dplyr::select(DB:LOG_QVALUE)), by= c( "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS","ID"="ID"))%>% 
  separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  mutate(motif_name= gsub("[()]","",NAME), mrc="ESR_close") %>%
  mutate(motif_name=
           if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
           if_else(is.na(motif_name),ID,motif_name)))


# spd_ESRoc <-ESR_OC_xstreme%>% 
#    mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
#   dplyr::filter(EVALUE<0.05) %>% 
#   left_join(., (sea_ESR_OC %>%
#                   # dplyr::rename("SEA_PVALUE"=PVALUE) %>%
#                   dplyr::select(RANK,ID:PVALUE)),
#             by= c("RANK"="RANK", "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS",  "ID"="ID")) %>% 
#   separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
#   mutate(motif_name= gsub("[()]","",NAME), mrc="ESR_OC") %>%
#   mutate(motif_name=
#            if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
#            if_else(is.na(motif_name),ID,motif_name)))
# #######rbind break too

spd_ESRopcl_200<-ESR_opcl_xstreme%>% 
   mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
  dplyr::filter(EVALUE<0.05) %>% 
  left_join(., (sea_ESR_opcl_200_p2 %>%
                  anti_join(.,sea_ESR_opcl_200, by = c("ID"="ID","ALT_ID"="ALT_ID")) %>%
  rbind(sea_ESR_opcl_200) %>% 
  dplyr::select(DB:LOG_QVALUE)), by= c( "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS","ID"="ID"))%>% 
  separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  mutate(motif_name= gsub("[()]","",NAME), mrc="ESR_opcl") %>%
  mutate(motif_name=
           if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
           if_else(is.na(motif_name),ID,motif_name)))

#### break for clop!

spd_ESRclop_200<-ESR_clop_xstreme%>% 
   mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
  dplyr::filter(EVALUE<0.05) %>% 
  left_join(., (sea_ESR_clop_200_p2 %>%
                  anti_join(.,sea_ESR_clop_200, by = c("ID"="ID","ALT_ID"="ALT_ID")) %>%
  rbind(sea_ESR_clop_200) %>% 
  dplyr::select(DB:LOG_QVALUE)), by= c( "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS","ID"="ID"))%>% 
  separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  mutate(motif_name= gsub("[()]","",NAME), mrc="ESR_clop") %>%
  mutate(motif_name=
           if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
           if_else(is.na(motif_name),ID,motif_name))) 
#opcl

###rbind break#####
# spd_LRo <-LR_open_xstreme%>%
#            mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
#   dplyr::filter(EVALUE<0.05) %>% 
#   left_join(., (sea_LR_open %>%
#                   # dplyr::rename("SEA_PVALUE"=PVALUE) %>%
#                   dplyr::select(RANK,ID:PVALUE)),
#             by= c("RANK"="RANK", "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS",  "ID"="ID")) %>% 
#   separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
#   mutate(motif_name= gsub("[()]","",NAME), mrc="LR_open") %>%
#   mutate(motif_name=
#            if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,  if_else(is.na(motif_name),ID,motif_name)))

spd_LRo_200 <-LR_open_200xstreme%>%
           mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
  dplyr::filter(EVALUE<0.05) %>% 
  left_join(., (sea_LR_open_200_p2 %>%
                  anti_join(.,sea_LR_open_200, by = c("ID"="ID","ALT_ID"="ALT_ID")) %>%
  rbind(sea_LR_open_200) %>% 
  dplyr::select(DB:LOG_QVALUE)), by= c( "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS","ID"="ID"))%>% 
  separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  mutate(motif_name= gsub("[()]","",NAME), mrc="LR_open") %>%
  mutate(motif_name=
           if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,  if_else(is.na(motif_name),ID,motif_name)))
 
### rbind break
# spd_LRc <- LR_close_xstreme%>% 
#    mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
#   dplyr::filter(EVALUE<0.05) %>% 
#   left_join(., (sea_LR_close %>%
#                   # dplyr::rename("SEA_PVALUE"=PVALUE) %>%
#                   dplyr::select(RANK,ID:PVALUE)),
#             by= c("RANK"="RANK", "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS",  "ID"="ID")) %>% 
#   separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
#   mutate(motif_name= gsub("[()]","",NAME), mrc="LR_close") %>%
#   mutate(motif_name=
#            if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
#            if_else(is.na(motif_name),ID,motif_name)))

spd_LRc_200 <- LR_close_200xstreme%>% 
   mutate(CONSENSUS=gsub('[[:digit:]]+-', '', CONSENSUS)) %>% 
  dplyr::filter(EVALUE<0.05) %>% 
  left_join(., (sea_LR_close_200_p2 %>%
                  anti_join(.,sea_LR_close_200, by = c("ID"="ID","ALT_ID"="ALT_ID")) %>%
  rbind(sea_LR_close_200) %>% 
  dplyr::select(DB:LOG_QVALUE)), by= c( "ALT_ID"="ALT_ID", "CONSENSUS"="CONSENSUS","ID"="ID"))%>% 
  separate(SIM_MOTIF, into= c("SIM_MOTIF", "NAME"), sep= " ") %>% 
  mutate(motif_name= gsub("[()]","",NAME), mrc="LR_close") %>%
  mutate(motif_name=
           if_else(is.na(motif_name)&str_detect(SIM_MOTIF,"^M"),ALT_ID,
           if_else(is.na(motif_name),ID,motif_name)))

# spec_dataframe <- spd_EARo %>% 
#   rbind(spd_EARc) %>% 
#   rbind(spd_ESRo) %>%
#    rbind(spd_ESRc) %>% 
#    rbind(spd_ESRoc) %>% 
#    rbind(spd_LRo) %>% 
#    rbind(spd_LRc)

spec_dataframe_200 <- spd_EARo_200 %>% 
  rbind(spd_EARc_200) %>% 
  rbind(spd_ESRo_200) %>%
   rbind(spd_ESRc_200) %>%
  rbind(spd_ESRopcl_200) %>% 
  rbind(spd_ESRclop_200) %>% 
   rbind(spd_LRo_200) %>% 
   rbind(spd_LRc_200)
spec_dataframe_200 %>% 
  dplyr::filter(mrc=="ESR_opcl")

# A tibble: 13 × 31
   RANK  SEED_MOTIF CLUSTER SOURCE ID    ALT_ID CONSENSUS WIDTH SITES SEA_PVALUE
   <chr>      <dbl>   <dbl> <chr>  <chr> <chr>  <chr>     <dbl> <dbl>      <dbl>
 1 2              1       2 MEME   AARW… MEME-1 AARWADAA…    15    52   1.73e-11
 2 4              1       4 ../mo… MA07… POU3F4 TATGCWAAT     9    77   5.29e- 8
 3 5              0       4 ../mo… MA07… POU3F2 WTATGCWA…    12    80   3.21e- 7
 4 6              1       5 ../mo… MA00… NKX2-5 NNCACTCA…    11    74   4.29e- 7
 5 7              1       6 ../mo… MA06… Nr2e1  AAAAGTCAA     9    81   4.70e- 7
 6 8              0       4 ../mo… MA05… POU2F2 AWTATGCA…    14    37   7.47e- 6
 7 10             0       4 ../mo… MA07… POU5F… TATGCWAAT     9    64   8.05e- 6
 8 11             1       8 ../mo… MA14… BARX2  NWWAAYMA…    12    84   8.51e- 6
 9 12             0       4 ../mo… MA07… POU3F3 WWTATGCW…    13    73   1.59e- 5
10 13             1       9 ../mo… MA09… HOXD9  GYMATAAA…    10    67   4.43e- 5
11 14             1      10 ../mo… MA07… POU4F1 ATGMATAA…    14    69   4.52e- 5
12 15             0       5 ../mo… MA04… CDX2   NDGCAATA…    12    54   4.76e- 5
13 16             1      11 MEME   GTGT… MEME-2 GTGTGTRT…    15    13   7.5 e- 2
# ℹ 21 more variables: EVALUE.x <dbl>, EVALUE_ACC <dbl>, SIM_SOURCE <chr>,
#   SIM_MOTIF <chr>, NAME <chr>, MOTIF_URL <chr>, DB <chr>, TP <dbl>,
#   `TP%` <dbl>, FP <dbl>, `FP%` <dbl>, ENR_RATIO <dbl>, SCORE_THR <dbl>,
#   PVALUE <dbl>, LOG_PVALUE <dbl>, EVALUE.y <dbl>, LOG_EVALUE <dbl>,
#   QVALUE <dbl>, LOG_QVALUE <dbl>, motif_name <chr>, mrc <chr>

# saveRDS(spec_dataframe_200,"data/Final_four_data/spec_dataframe_200.RDS")
spec_dataframe_200 <- readRDS("data/Final_four_data/spec_dataframe_200.RDS")

data plots from full sequences

###plotting 
# spec_dataframe %>% 
#  ggplot(.,aes(x=mrc,y=ENR_RATIO,fill=mrc))+
#   geom_boxplot()+ 
#    geom_hline(yintercept=1.2, col="red")+
#   theme_classic()+
#   ylab("Enrichment ratio")+
#   ggtitle("Enrichment ratio values across MRC")+
#   scale_fill_manual(values=mrc_palette)
# spec_dataframe %>% 
#   ggplot(., aes(x=ENR_RATIO, fill = mrc))+
#   geom_density(aes(alpha=0.4)) +
#    theme_classic()+
#   xlab("Enrichment ratio")+
#   ggtitle("Enrichment ratio histogram MRC")+
#   scale_fill_manual(values=mrc_palette)+
#   coord_cartesian(xlim=c(1,5))

# spec_dataframe %>% 
#   # dplyr::filter(mrc=="LR_open") %>% 
#   ggplot(., aes(x=mrc, y=-log(base=10,EVALUE), color=mrc))+
#     geom_jitter()+
#   theme_classic()+
#   ylab(expression("-log[10] Evalue"))+
#   ggtitle("Significant values across MRC motifs")+
#   scale_color_manual(values=mrc_palette)
# 
# spec_dataframe %>% 
#   # dplyr::filter(mrc=="LR_open") %>% 
#   ggplot(., aes(x=ENR_RATIO, y=-log(base=10,EVALUE), color=mrc))+
#     geom_point(alpha=0.3)+
#   theme_classic()+
#   ylab(expression("-log[10] Evalue"))+
#   ggtitle("Enrichment ratio against significance")+
#   scale_color_manual(values=mrc_palette)

data plots from 200 bp sequences

###plotting 
spec_dataframe_200 %>% 
 ggplot(.,aes(x=mrc,y=ENR_RATIO,fill=mrc))+
  geom_boxplot()+
   geom_hline(yintercept=1.2, col="red")+
  theme_classic()+
  ylab("Enrichment ratio")+
  ggtitle("Enrichment ratio values across MRC_200")+
  scale_fill_manual(values=mrc_palette)

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
f9c15bd	reneeisnowhere	2024-10-12
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200 %>% 
  ggplot(., aes(x=ENR_RATIO, fill = mrc))+
  geom_density(aes(alpha=0.4)) +
  theme_classic()+
  xlab("Enrichment ratio")+
  ggtitle("Enrichment ratio histogram MRC_200")+
  scale_fill_manual(values=mrc_palette)+
  coord_cartesian(xlim=c(1,5))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
f9c15bd	reneeisnowhere	2024-10-12
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200 %>% 
  # dplyr::filter(mrc=="LR_open") %>% 
  ggplot(., aes(x=mrc, y=-log(base=10,EVALUE.x), color=mrc))+
    geom_jitter()+
  theme_classic()+
  ylab(expression("-log[10] Evalue"))+
  ggtitle("Significant values across MRC motifs_200")+
  scale_color_manual(values=mrc_palette)

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
aa0769e	E. Renee Matthews	2025-01-02
5bf51a6	reneeisnowhere	2024-10-18
f9c15bd	reneeisnowhere	2024-10-12
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200 %>% 
  # dplyr::filter(mrc=="LR_open") %>% 
  ggplot(., aes(x=ENR_RATIO, y=-log(base=10,EVALUE.x), color=mrc))+
    geom_point(alpha=0.3)+
  theme_classic()+
  ylab(expression("-log[10] Evalue"))+
  ggtitle("Enrichment ratio against significance_200")+
  scale_color_manual(values=mrc_palette)

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
f9c15bd	reneeisnowhere	2024-10-12
d8eef0e	reneeisnowhere	2024-10-09

The enrichment ratio plot let me know where (sort of) to cut the plots to find the highest enrichment ratios by MRC. We decided that ER ratio is not correlated to the significance of the motif, so first filter will be slicing the top 20 by Evalue out, and the second plot will be what happens when we pull the top most significant representative from the cluster and show overall significance by cluster. (I evaluated the results of clustering by eye, to make sure the most significant (by evalue) of the cluster was called for the second figure) ### EAR bar plots

EAR open 200 bp barplots

ER_rat <- 1.25
mrc_type <- "EAR_open"
spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>%
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="ELK3",paste(motif_name, RANK, sep="_"),             if_else(str_starts(motif_name,"^Z*"),paste(motif_name, RANK, sep="_"), if_else(motif_name=="Nrf1",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
  geom_point(aes(x=`TP%`*1.25), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./1.25,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste( mrc_type,"response peaks(200bp)Enrichment ratio:",ER_rat))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200%>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>%
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="ELK3",paste(motif_name, RANK, sep="_"),             if_else(str_starts(motif_name,"^Z*"),paste(motif_name, RANK, sep="_"), if_else(motif_name=="Nrf1",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  distinct(CLUSTER,.keep_all = TRUE) %>% 
  slice_head(n=5) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
   geom_point(aes(x=`TP%`/1.5), size =4)+
   # geom_line(aes(x=`TP%`,y= motif_name, group=log10Evalue))+
  scale_x_continuous(expand=c (0,.25),sec.axis = sec_axis(transform= ~.*1.5,name="Percent of peaks with motif"))+
  # geom_text(aes())
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste( mrc_type,"response peaks(200bp)Enrichment ratio:",ER_rat," merged clusters"))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

EAR_close

EAR_close 200bp

ER_rat <- 1.25
mrc_type <- "EAR_close"
spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="MEIS1",paste(motif_name, RANK, sep="_"),             if_else(motif_name=="ZNF384",paste(motif_name, RANK, sep="_"), if_else(motif_name=="ZNF257",paste(motif_name, RANK,sep="_"),motif_name))))%>%
   slice_head(n=40) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
  geom_point(aes(x=`TP%`*1), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./1,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste( mrc_type,"response peaks (200bp) Enrichment ratio:",ER_rat))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="MEIS1",paste(motif_name, RANK, sep="_"),             if_else(motif_name=="ZNF384",paste(motif_name, RANK, sep="_"), if_else(motif_name=="ZNF257",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  distinct(CLUSTER,.keep_all = TRUE) %>% 
   slice_head(n=5) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
   geom_point(aes(x=`TP%`/1.25), size =4)+
   # geom_line(aes(x=`TP%`,y= motif_name, group=log10Evalue))+
  scale_x_continuous(expand=c (0,.25),sec.axis = sec_axis(transform= ~.*1.25,name="Percent of peaks with motif"))+
  # geom_text(aes())
  theme_classic()+
  ylab("Enriched TF motif")+
   ggtitle(paste( mrc_type,"response peaks (200bp) Enrichment ratio:",ER_rat," merged clusters"))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  # dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  # arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  # mutate(motif_name=if_else(motif_name=="MEIS1",paste(motif_name, RANK, sep="_"),             if_else(motif_name=="ZNF384",paste(motif_name, RANK, sep="_"), if_else(motif_name=="ZNF257",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  distinct(CLUSTER,.keep_all = TRUE) %>% 
  arrange(.,EVALUE.x) %>%
   slice_head(n=5) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
   geom_point(aes(x=`TP%`/1.25), size =4)+
   # geom_line(aes(x=`TP%`,y= motif_name, group=log10Evalue))+
  scale_x_continuous(expand=c (0,.25),sec.axis = sec_axis(transform= ~.*1.25,name="Percent of peaks with motif"))+
  # geom_text(aes())
  theme_classic()+
  ylab("Enriched TF motif")+
   ggtitle(paste( mrc_type,"response peaks (200bp) Enrichment ratio: not applied  modified merged clusters"))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  # dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  # arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  # mutate(motif_name=if_else(motif_name=="MEIS1",paste(motif_name, RANK, sep="_"),             if_else(motif_name=="ZNF384",paste(motif_name, RANK, sep="_"), if_else(motif_name=="ZNF257",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  distinct(CLUSTER,.keep_all = TRUE) %>% 
  arrange(.,EVALUE.x) %>%
   slice_head(n=5)

# A tibble: 5 × 13
  RANK  CLUSTER SITES SIM_MOTIF ALT_ID ID       EVALUE.x    TP `TP%`    FP `FP%`
  <chr>   <dbl> <dbl> <chr>     <chr>  <chr>       <dbl> <dbl> <dbl> <dbl> <dbl>
1 1           2  1920 MA1988.1  Atf3   MA1988.1 4.97e-76  1920 49.6  26835 34.5 
2 345        58   822 MA1125.1  MEME-1 AAAAAAA… 5.20e-59   102  2.64  1371  1.76
3 348        61  1254 MA1596.1  MEME-2 GGGAGGV… 3   e-47  2915 75.4  57854 74.5 
4 29          9  3737 MA0676.1  Nr2e1  MA0676.1 4.35e-43  3737 96.6  70456 90.7 
5 33          4  3543 MA0790.1  POU4F1 MA0790.1 2.53e-40  3543 91.6  65240 84.0 
# ℹ 2 more variables: motif_name <chr>, log10Evalue <dbl>

ESR

ESR_open

ER_rat <- 1.25
mrc_type <- "ESR_open"
spec_dataframe_200 %>% 
  dplyr::filter(mrc=="ESR_open") %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=
           if_else(str_starts(motif_name,"JUND"),paste(motif_name, RANK, sep="_"),             if_else(str_starts(motif_name,"^ZN*"),paste(motif_name, RANK, sep="_"),    if_else(motif_name=="ZSCAN4", paste(motif_name, RANK,sep="_"),if_else(motif_name=="KLF9",paste(motif_name,RANK,sep="_"), motif_name)))))%>%
  slice_head(n=40) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette["ESR_open"]) +
  geom_point(aes(x=`TP%`*2), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./2,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
   ggtitle(paste( mrc_type,"response peaks 200 bpEnrichment ratio:",ER_rat))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200 %>% 
  dplyr::filter(mrc=="ESR_open") %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
   mutate(motif_name=
           if_else(str_starts(motif_name,"JUND"),paste(motif_name, RANK, sep="_"),             if_else(str_starts(motif_name,"^ZN*"),paste(motif_name, RANK, sep="_"),    if_else(motif_name=="ZSCAN4", paste(motif_name, RANK,sep="_"),if_else(motif_name=="KLF9",paste(motif_name,RANK,sep="_"), motif_name)))))%>%
  distinct(CLUSTER,.keep_all = TRUE) %>% 
   slice_head(n=5) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette["ESR_open"]) +
   geom_point(aes(x=`TP%`*4.7), size =4)+
   # geom_line(aes(x=`TP%`,y= motif_name, group=log10Evalue))+
  scale_x_continuous(expand=c (0,.25),sec.axis = sec_axis(transform= ~./4.7,name="Percent of peaks with motif"))+
  # geom_text(aes())
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste(mrc_type,"response peaks 200bp Enrichment ratio:",ER_rat," merged motif clusters"))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200 %>% 
  dplyr::filter(mrc=="ESR_open") %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
   mutate(motif_name=
           if_else(str_starts(motif_name,"JUND"),paste(motif_name, RANK, sep="_"),             if_else(str_starts(motif_name,"^ZN*"),paste(motif_name, RANK, sep="_"),    if_else(motif_name=="ZSCAN4", paste(motif_name, RANK,sep="_"),if_else(motif_name=="KLF9",paste(motif_name,RANK,sep="_"), motif_name)))))%>%
  distinct(CLUSTER,.keep_all = TRUE) %>% 
   slice_head(n=5)

# A tibble: 5 × 13
  RANK  CLUSTER SITES SIM_MOTIF   ALT_ID ID     EVALUE.x    TP `TP%`    FP `FP%`
  <chr>   <dbl> <dbl> <chr>       <chr>  <chr>     <dbl> <dbl> <dbl> <dbl> <dbl>
1 16          3   800 MA0490.2    JUNB   MA04… 3   e-106   800 16.9   5381  6.93
2 3           1   682 GTGTGTGTGT… MEME-1 GTGT… 5   e-101   582 12.3   2893  3.72
3 44          2   808 MA1155.1    ZSCAN4 MA11… 1.75e- 63   808 17.0   6872  8.84
4 45          4   367 MA0861.1    TP73   MA08… 7.58e- 63   367  7.73  2046  2.63
5 50          5   188 MA0073.1    RREB1  MA00… 4.9 e- 39   188  3.96   894  1.15
# ℹ 2 more variables: motif_name <chr>, log10Evalue <dbl>

ESR_close

ER_rat <- 1.25
mrc_type <- "ESR_close"
spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="KLF9",paste(motif_name, RANK, sep="_"),             if_else(motif_name=="^ZN*",paste(motif_name, RANK, sep="_"), if_else(motif_name=="ZSCAN4",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  slice_head(n=40) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
  geom_point(aes(x=`TP%`*1.25), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./1.25,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
 ggtitle(paste( mrc_type,"response peaks 200bp Enrichment ratio:",ER_rat))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>(ER_rat+.1)) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="KLF9",paste(motif_name, RANK, sep="_"),             if_else(motif_name=="^ZN*",paste(motif_name, RANK, sep="_"), if_else(motif_name=="ZSCAN4",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  distinct(CLUSTER,.keep_all = TRUE) %>% 
  slice_head(n=5) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
   geom_point(aes(x=`TP%`/0.5), size =4)+
   # geom_line(aes(x=`TP%`,y= motif_name, group=log10Evalue))+
  scale_x_continuous(expand=c (0,.25),sec.axis = sec_axis(transform= ~.*0.5,name="Percent of peaks with motif"))+
  # geom_text(aes())
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste( mrc_type,"response peaks 200bp Enrichment ratio:",ER_rat+.1," merged motif clusters"))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

ESR_opcl {C}

ER_rat <- 1.25
mrc_type <- "ESR_opcl"
spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="KLF9",paste(motif_name, RANK, sep="_"),             if_else(motif_name=="^ZN*",paste(motif_name, RANK, sep="_"), if_else(motif_name=="ZSCAN4",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  slice_head(n=40) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
  geom_point(aes(x=`TP%`*1.25), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./1.25,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
 ggtitle(paste( mrc_type,"response peaks 200bp Enrichment ratio:",ER_rat))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>(ER_rat)) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="KLF9",paste(motif_name, RANK, sep="_"),             if_else(motif_name=="^ZN*",paste(motif_name, RANK, sep="_"), if_else(motif_name=="ZSCAN4",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  distinct(CLUSTER,.keep_all = TRUE) %>% 
  slice_head(n=5) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
   geom_point(aes(x=`TP%`/3), size =4)+
   # geom_line(aes(x=`TP%`,y= motif_name, group=log10Evalue))+
  scale_x_continuous(expand=c (0,.25),sec.axis = sec_axis(transform= ~.*3,name="Percent of peaks with motif"))+
  # geom_text(aes())
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste( mrc_type,"response peaks 200bp Enrichment ratio:",ER_rat," merged motif clusters"))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
f9c15bd	reneeisnowhere	2024-10-12
d8eef0e	reneeisnowhere	2024-10-09

ESR_clop {D}

ER_rat <- 1.25
mrc_type <- "ESR_clop"
spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="KLF9",paste(motif_name, RANK, sep="_"),             if_else(motif_name=="^ZN*",paste(motif_name, RANK, sep="_"), if_else(motif_name=="ZSCAN4",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  slice_head(n=40) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
  geom_point(aes(x=`TP%`*1.25), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./1.25,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
 ggtitle(paste( mrc_type,"response peaks 200bp Enrichment ratio:",ER_rat))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
f9c15bd	reneeisnowhere	2024-10-12

spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>(ER_rat)) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="KLF9",paste(motif_name, RANK, sep="_"),             if_else(motif_name=="^ZN*",paste(motif_name, RANK, sep="_"), if_else(motif_name=="ZSCAN4",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  distinct(CLUSTER,.keep_all = TRUE) %>% 
  slice_head(n=5) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
   geom_point(aes(x=`TP%`*2.3), size =4)+
   # geom_line(aes(x=`TP%`,y= motif_name, group=log10Evalue))+
  scale_x_continuous(expand=c (0,.25),sec.axis = sec_axis(transform= ~./2.3,name="Percent of peaks with motif"))+
  # geom_text(aes())
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste( mrc_type,"response peaks 200bp Enrichment ratio:",ER_rat," merged motif clusters"))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
f9c15bd	reneeisnowhere	2024-10-12

LR

LR_open

ER_rat <- 1.25
mrc_type <- "LR_open"
spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
 mutate(motif_name=
           if_else(str_starts(motif_name,"BATF"),paste(motif_name, RANK, sep="_"),             if_else(str_starts(motif_name,"^FO*"),paste(motif_name, RANK, sep="_"),    if_else(motif_name=="ZSCAN4", paste(motif_name, RANK,sep="_"),if_else(motif_name=="KLF9",paste(motif_name,RANK,sep="_"), motif_name)))))%>%
  slice_head(n=60) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
  geom_point(aes(x=`TP%`*4), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./4,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
 ggtitle(paste( mrc_type,"response peaks 200 bp Enrichment ratio:",ER_rat))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=
           if_else(str_starts(motif_name,"BATF"),paste(motif_name, RANK, sep="_"),             if_else(str_starts(motif_name,"^FO*"),paste(motif_name, RANK, sep="_"),    if_else(motif_name=="ZSCAN4", paste(motif_name, RANK,sep="_"),if_else(motif_name=="KLF9",paste(motif_name,RANK,sep="_"), motif_name)))))%>%
  distinct(CLUSTER,.keep_all = TRUE) %>% 
   slice_head(n=5) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
   geom_point(aes(x=`TP%`*5), size =4)+
   # geom_line(aes(x=`TP%`,y= motif_name, group=log10Evalue))+
  scale_x_continuous(expand=c (0,.25),sec.axis = sec_axis(transform= ~./5,name="Percent of peaks with motif"))+
  # geom_text(aes())
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste( mrc_type,"response peaks 200 bp Enrichment ratio:",ER_rat," merged motif clusters"))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

LR_close

ER_rat <- 1.25
mrc_type <- "LR_close"
spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="KLF9",paste(motif_name, RANK, sep="_"),             if_else(str_starts(motif_name,"^R*"),paste(motif_name, RANK, sep="_"), if_else(motif_name=="PKNOX2",paste(motif_name, RANK,sep="_"),motif_name))))%>%
    slice_head(n=40) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
  geom_point(aes(x=`TP%`*1.25), size =4)+
  scale_x_continuous(expand=c (0,.125),sec.axis = sec_axis(transform= ~./1.25,name="Percent of peaks with motif"))+
  theme_classic()+
  ylab("Enriched TF motif")+
 ggtitle(paste( mrc_type,"response peaks 200bp Enrichment ratio:",ER_rat))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

spec_dataframe_200 %>% 
  dplyr::filter(mrc==mrc_type) %>% 
  dplyr::filter(ENR_RATIO>ER_rat) %>% 
  dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
  arrange(.,EVALUE.x) %>%
  mutate(log10Evalue= log(EVALUE.x, base = 10)*(-1)) %>% 
  mutate(motif_name=if_else(motif_name=="KLF9",paste(motif_name, RANK, sep="_"),             if_else(str_starts(motif_name,"^R*"),paste(motif_name, RANK, sep="_"), if_else(motif_name=="PKNOX2",paste(motif_name, RANK,sep="_"),motif_name))))%>%
  distinct(CLUSTER,.keep_all = TRUE) %>% 
  slice_head(n=5) %>% 
  ggplot(., aes (y= reorder(motif_name,log10Evalue))) +
  geom_col(aes(x=log10Evalue),fill=mrc_palette[mrc_type]) +
   geom_point(aes(x=`TP%`/.4), size =4)+
   # geom_line(aes(x=`TP%`,y= motif_name, group=log10Evalue))+
  scale_x_continuous(expand=c (0,.25),sec.axis = sec_axis(transform= ~.*.4,name="Percent of peaks with motif"))+
  # geom_text(aes())
  theme_classic()+
  ylab("Enriched TF motif")+
  ggtitle(paste( mrc_type,"response peaks 200bp Enrichment ratio:",ER_rat," merged motif clusters"))

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18
d8eef0e	reneeisnowhere	2024-10-09

# spec_dataframe %>% 
#   dplyr::filter(mrc==mrc_type) %>% 
#   dplyr::filter(ENR_RATIO>ER_rat) #%>% 
#   dplyr::select(RANK,CLUSTER, SITES,SIM_MOTIF,ALT_ID, ID,EVALUE, TP:'FP%', motif_name)

motif and peak section

NR_gr <- import("data/Final_four_data/meme_bed/NR_df.bed")
EAR_open_gr <- import("data/Final_four_data/meme_bed/EAR_open.bed")
EAR_close_gr <- import("data/Final_four_data/meme_bed/EAR_close.bed")
ESR_open_gr <- import("data/Final_four_data/meme_bed/ESR_open.bed")
ESR_OC_gr <- import("data/Final_four_data/meme_bed/ESR_OC.bed")
ESR_close_gr <- import("data/Final_four_data/meme_bed/ESR_close.bed")
LR_open_gr <- import("data/Final_four_data/meme_bed/LR_open.bed")
LR_close_gr <- import("data/Final_four_data/meme_bed/LR_close.bed")
ESR_C_gr <- import("data/Final_four_data/meme_bed/ESR_C.bed")
 
ESR_D_gr <- import("data/Final_four_data/meme_bed/ESR_D.bed")
 
# rtracklayer::export.bed(ESR_D_resized,con = "data/Final_four_data/meme_bed/ESR_D_resized.bed")
ESR_C_resized <- resize(ESR_C_gr, width = 400,fix='center')
ESR_D_resized <- resize(ESR_D_gr, width = 400,fix='center')
EAR_open_resized <- resize(EAR_open_gr, width = 400,fix='center')
ESR_open_resized <- resize(ESR_open_gr, width = 400,fix='center')
LR_open_resized <- resize(LR_open_gr, width = 400,fix='center')
NR_resized <- resize(NR_gr, width = 400,fix='center')

EAR_close_resized <- resize(EAR_close_gr, width = 400,fix='center')
ESR_close_resized <- resize(ESR_close_gr, width = 400,fix='center')
LR_close_resized <- resize(LR_close_gr, width = 400,fix='center')
ESR_OC_resized <- resize(ESR_OC_gr, width = 400,fix='center')



# BiocManager::install('PWMEnrich')

# seq_list_cd <- list(EAR_open_resized=EAR_open_resized,EAR_close_resized=EAR_close_resized,ESR_open_resized=ESR_open_resized,ESR_close_resized=ESR_close_resized,ESR_C_resized=ESR_C_resized,ESR_D_resized=ESR_D_resized,LR_open_resized=LR_open_resized,LR_close_resized=LR_close_resized,NR_resized=NR_resized)



# seq_all_cd_200 <- lapply(seq_list_cd, getSeq, x=BSgenome.Hsapiens.UCSC.hg38)
# seq_all_200

# saveRDS(seq_all_cd_200, "data/Final_four_data/sequencing_cd_200_object8_motif.RDS")
# seq_all_200 <- readRDS("data/Final_four_data/sequencing_R200_object8_motif.RDS")
seq_all_cd_200 <- readRDS("data/Final_four_data/sequencing_cd_200_object8_motif.RDS")

# spec_dataframe_200 %>% 
#   # dplyr::filter(stringr::str_detect( motif_name,"Mafg^*")) %>%
#   dplyr::filter(mrc=="EAR_close") %>% 
#   dplyr::select(RANK,CLUSTER,ENR_RATIO,SIM_MOTIF,ALT_ID, ID,EVALUE.x, TP:'FP%', motif_name)%>%
#   dplyr::filter(CLUSTER==58|CLUSTER==58) %>%
#   arrange(.,EVALUE.x)# %>%

spec_dataframe_200 <- readRDS("data/Final_four_data/spec_dataframe_200.RDS")

spec_dataframe_200 %>% 
  dplyr::select(CLUSTER, ID:CONSENSUS,motif_name, mrc,NAME,ENR_RATIO,EVALUE.x) %>% 
  dplyr::filter(ENR_RATIO>1.2) %>% 
 dplyr::filter(EVALUE.x<0.05)%>% 
  group_by(mrc,CLUSTER) %>% 
  summarize(ID=paste(unique(ID), collapse = ";"),
            ALT_ID=paste(unique(ALT_ID), collapse = ";"),
            motif_name=paste(unique(motif_name),collapse="; "),
            NAME=paste((NAME),collapse =";"),
            mrc=unique(mrc),
            sig_val=paste0(min(EVALUE.x),"-",max(EVALUE.x)),
            order_val=min(EVALUE.x)) %>% 
    arrange(mrc,order_val) #%>%

# A tibble: 163 × 8
# Groups:   mrc [8]
   mrc       CLUSTER ID                ALT_ID motif_name NAME  sig_val order_val
   <chr>       <dbl> <chr>             <chr>  <chr>      <chr> <chr>       <dbl>
 1 EAR_close       2 MA1988.1;MA0099.… Atf3;… Atf3; FOS… NA;N… 4.97e-…  4.97e-76
 2 EAR_close      58 AAAAAAAAAAAAAAW   MEME-1 ZNF384     (ZNF… 5.2e-5…  5.20e-59
 3 EAR_close       1 MA0766.2;MA0482.2 GATA5… GATA5; GA… NA;NA 9.06e-…  9.06e-50
 4 EAR_close      17 MA0842.2          NRL    NRL        NA    5.88e-…  5.88e-22
 5 EAR_close      54 TGTYGCCCAGGCTGG   MEME-3 ZKSCAN3    (ZKS… 2.8e-2…  2.8 e-21
 6 EAR_close      59 WGCTGGGATTACAGG   MEME-4 PITX1      (PIT… 4.2e-1…  4.20e-19
 7 EAR_close      29 MA0492.1;MA0488.1 JUND;… JUND; JUN  NA;NA 4.53e-…  4.53e-15
 8 EAR_close      37 MA0029.1          Mecom  Mecom      NA    1.06e-…  1.06e-10
 9 EAR_close      51 MA1110.2          Nr1H4  Nr1H4      NA    2.4e-1…  2.40e-10
10 EAR_close      47 MA1643.1;MA0119.… NFIB;… NFIB; NFI… NA;N… 7.56e-…  7.56e- 8
# ℹ 153 more rows

  # write_delim(.,"data/Final_four_data/motif_cluster_dataframe.txt",delim="\t")

meme_motifs_EAR_open <- read_meme("C:/Users/renee/ATAC_folder/ATAC_meme_data/200bp/EAR_open_200xstreme/xstreme.txt")
meme_motifs_ESR_open <- read_meme("C:/Users/renee/ATAC_folder/ATAC_meme_data/200bp/ESR_open_200xstreme/xstreme.txt")
meme_motifs_LR_open <- read_meme("C:/Users/renee/ATAC_folder/ATAC_meme_data/200bp/LR_open_200xstreme/xstreme.txt")
meme_motifs_EAR_close <- read_meme("C:/Users/renee/ATAC_folder/ATAC_meme_data/200bp/EAR_close_200xstreme/xstreme.txt")
meme_motifs_ESR_close <- read_meme("C:/Users/renee/ATAC_folder/ATAC_meme_data/200bp/ESR_close_200xstreme/xstreme.txt")
meme_motifs_LR_close <- read_meme("C:/Users/renee/ATAC_folder/ATAC_meme_data/200bp/LR_close_200xstreme/xstreme.txt")
meme_motifs_ESR_opcl <- read_meme("C:/Users/renee/ATAC_folder/ATAC_meme_data/200bp/ESR_C_200xstreme/xstreme.txt")
meme_motifs_ESR_clop <- read_meme("C:/Users/renee/ATAC_folder/ATAC_meme_data/200bp/ESR_D_200xstreme/xstreme.txt")


holder_EAR_open <- meme_motifs_EAR_open[[4]]
holder_ESR_open <- meme_motifs_ESR_open[[3]]
holder_LR_open <- meme_motifs_LR_open[[1]]
holder_ESR_opcl <- meme_motifs_ESR_opcl[[2]]
holder_EAR_close <- meme_motifs_EAR_close[[2]]
holder_ESR_close <- meme_motifs_ESR_close[[18]]
holder_LR_close <- meme_motifs_LR_close[[1]]
holder_ESR_clop <- meme_motifs_ESR_clop[[1]]

EAR open top motif

# pw_matrix_earo <- convert_motifs(holder_EAR_open, class = "TFBSTools-PWMatrix")
# 
# motif_EAR_open_4_results <- lapply(seq_all_cd_200, function(sequences) {
# matchMotifs(pw_matrix_earo, sequences, out = "positions")
# })
# 
# motifstorage_earo <-motif_positions_df <- do.call(rbind, lapply(seq_along(motif_EAR_open_4_results), function(i) {
  # positions <- motif_EAR_open_4_results[[i]]  # Positions from matchMotifs
  # seq_name <- names(seq_all_cd_200)[i]  # Get sequence ID from the original list
  # 
  # if (length(positions) > 0) {
  #   # Create a data frame with sequence_id and motif positions
  #   data.frame(
  #     sequence_id = seq_name,  # Use the sequence name here
  #     motif_position = unlist(positions)
  #   )
  # } else {
  #   NULL  # If no positions, return NULL
#   }
# }))

 # saveRDS(motifstorage_earo, "data/Final_four_data/matchr_EAR_open_4.RDS")
##### PLOTING CODE BELOW THIS LINE FOR EAR_OPEN  #####
 # motifstorage_earo <- readRDS("data/Final_four_data/matchr_EAR_open_6.RDS")
motifstorage_earo <- readRDS("data/Final_four_data/matchr_EAR_open_4.RDS")
motifstorage_earo %>% 
mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  # dplyr::filter(id =="EAR_open"|id == "NR") %>%
   # dplyr::filter(relScore>.90) %>%
  mutate(position=motif_position.start-200) %>% 
  ggplot(.,aes(position, color = sequence_id))+
  geom_density(trim = FALSE,size=1.5) +
  theme_bw() +
  scale_color_manual(values=mrc_palette)+
  ggtitle("ZBTB14")

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
b5b2c0f	reneeisnowhere	2024-10-18
5bf51a6	reneeisnowhere	2024-10-18

EAR_open_density_plot <- motifstorage_earo %>% 
  mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  dplyr::filter(sequence_id == "EAR_open" | sequence_id == "NR") %>%
   mutate(position=motif_position.start-200) %>% 
  ggplot(., aes(position, color = sequence_id)) +
  geom_density(trim = FALSE, size = 1.5) +
  theme_bw() +
  scale_color_manual(values = mrc_palette) +
  ggtitle("ZBTB14")

# Assuming you already have the motif in a matrix or data frame for ggseqlogo

EAR_open_matrix_eg <- holder_EAR_open@motif  # If your motif is in PWM format

# Create the motif logo plot, this adds bits instead of "p" which is probability.
EAR_open_motif_logo_plot <- ggseqlogo(EAR_open_matrix_eg, method = "bits") + 
  theme_classic() +  
  ggtitle("EAR_open Motif Logo")
  
# Combine the density plot and motif logo plot using cowplot
  EAR_open_toprow <- plot_grid(NULL,EAR_open_motif_logo_plot, NULL, ncol = 3, rel_widths = c(.2,1,.2))
EAR_open_combined_plot <- plot_grid(EAR_open_toprow,EAR_open_density_plot,nrow=2, rel_heights = c(0.7,2))

# Print the combined plot
print(EAR_open_combined_plot)

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
b5b2c0f	reneeisnowhere	2024-10-18
5bf51a6	reneeisnowhere	2024-10-18

ESR open top motif

# pw_matrix_ESRo <- convert_motifs(holder_ESR_open, class = "TFBSTools-PWMatrix")
# 
# motif_ESR_open_6_results <- lapply(seq_all_cd_200, function(sequences) {
# matchMotifs(pw_matrix_ESRo, sequences, out = "positions")
# })
# 
# motifstorage_ESRo <-motif_positions_df <- do.call(rbind, lapply(seq_along(motif_ESR_open_6_results), function(i) {
#   positions <- motif_ESR_open_6_results[[i]]  # Positions from matchMotifs
#   seq_name <- names(seq_all_cd_200)[i]  # Get sequence ID from the original list
# # 
#   if (length(positions) > 0) {
#     # Create a data frame with sequence_id and motif positions
#     data.frame(
#       sequence_id = seq_name,  # Use the sequence name here
#       motif_position = unlist(positions)
#     )
#   } else {
#     NULL  # If no positions, return NULL
#   }
# }))
# #   
#  saveRDS(motifstorage_ESRo, "data/Final_four_data/matchr_ESR_open_3.RDS")
#### PLOTING CODE BELOW THIS LINE FOR ESR_OPEN  #####
motifstorage_ESRo <- readRDS("data/Final_four_data/matchr_ESR_open_3.RDS")
motifstorage_ESRo %>% 
mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  # dplyr::filter(id =="ESR_open"|id == "NR") %>%
   # dplyr::filter(relScore>.90) %>%
  mutate(position=motif_position.start-200) %>% 
  ggplot(.,aes(position, color = sequence_id))+
  geom_density(trim = FALSE,size=1.5) +
  theme_bw() +
  scale_color_manual(values=mrc_palette)+
  ggtitle("motifish")

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

ESR_open_density_plot <- motifstorage_ESRo %>% 
  mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  dplyr::filter(sequence_id == "ESR_open" | sequence_id == "NR") %>%
   mutate(position=motif_position.start-200) %>% 
  ggplot(., aes(position, color = sequence_id)) +
  geom_density(trim = FALSE, size = 1.5) +
  theme_bw() +
  scale_color_manual(values = mrc_palette) +
  ggtitle("JUNB")

# Assuming you already have the motif in a matrix or data frame for ggseqlogo

ESR_open_matrix_eg <- holder_ESR_open@motif  # If your motif is in PWM format

# Create the motif logo plot, this adds bits instead of "p" which is probability.
ESR_open_motif_logo_plot <- ggseqlogo(ESR_open_matrix_eg, method = "bits") + 
  theme_classic() +  
  ggtitle("ESR_open Motif Logo")
  
# Combine the density plot and motif logo plot using cowplot
  ESR_open_toprow <- plot_grid(NULL,ESR_open_motif_logo_plot, NULL, ncol = 3, rel_widths = c(.2,1,.2))
ESR_open_combined_plot <- plot_grid(ESR_open_toprow,ESR_open_density_plot,nrow=2, rel_heights = c(0.7,2))

# Print the combined plot
print(ESR_open_combined_plot)

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

LR open top motif

# pw_matrix_LRo <- convert_motifs(holder_LR_open, class = "TFBSTools-PWMatrix")
# 
# motif_LR_open_1_results <- lapply(seq_all_cd_200, function(sequences) {
# matchMotifs(pw_matrix_LRo, sequences, out = "positions")
# })
# 
# motifstorage_LRo <-motif_positions_df <- do.call(rbind, lapply(seq_along(motif_LR_open_1_results), function(i) {
#   positions <- motif_LR_open_1_results[[i]]  # Positions from matchMotifs
#   seq_name <- names(seq_all_cd_200)[i]  # Get sequence ID from the original list
# # 
#   if (length(positions) > 0) {
#     # Create a data frame with sequence_id and motif positions
#     data.frame(
#       sequence_id = seq_name,  # Use the sequence name here
#       motif_position = unlist(positions)
#     )
#   } else {
#     NULL  # If no positions, return NULL
#   }
# }))
# #   
 # saveRDS(motifstorage_LRo, "data/Final_four_data/matchr_LR_open_1.RDS")
#### PLOTING CODE BELOW THIS LINE FOR LR_OPEN  #####
motifstorage_LRo <- readRDS("data/Final_four_data/matchr_LR_open_1.RDS")
motifstorage_LRo %>% 
mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  # dplyr::filter(id =="LR_open"|id == "NR") %>%
   # dplyr::filter(relScore>.90) %>%
  mutate(position=motif_position.start-200) %>% 
  ggplot(.,aes(position, color = sequence_id))+
  geom_density(trim = FALSE,size=1.5) +
  theme_bw() +
  scale_color_manual(values=mrc_palette)+
  ggtitle("Mafg")

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

LR_open_density_plot <- motifstorage_LRo %>% 
  mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  dplyr::filter(sequence_id == "LR_open" | sequence_id == "NR") %>%
   mutate(position=motif_position.start-200) %>% 
  ggplot(., aes(position, color = sequence_id)) +
  geom_density(trim = FALSE, size = 1.5) +
  theme_bw() +
  scale_color_manual(values = mrc_palette) +
  ggtitle("Mafg")

# Assuming you already have the motif in a matrix or data frame for ggseqlogo

LR_open_matrix_eg <- holder_LR_open@motif  # If your motif is in PWM format

# Create the motif logo plot, this adds bits instead of "p" which is probability.
LR_open_motif_logo_plot <- ggseqlogo(LR_open_matrix_eg, method = "bits") + 
  theme_classic() +  
  ggtitle("LR_open Motif Logo")
  
# Combine the density plot and motif logo plot using cowplot
  LR_open_toprow <- plot_grid(NULL,LR_open_motif_logo_plot, NULL, ncol = 3, rel_widths = c(.2,1,.2))
LR_open_combined_plot <- plot_grid(LR_open_toprow,LR_open_density_plot,nrow=2, rel_heights = c(0.7,2))

# Print the combined plot
print(LR_open_combined_plot)

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

EAR_close top motif

# pw_matrix_EARc <- convert_motifs(holder_EAR_close, class = "TFBSTools-PWMatrix")
# 
# motif_EAR_close_1_results <- lapply(seq_all_cd_200, function(sequences) {
# matchMotifs(pw_matrix_EARc, sequences, out = "positions")
# })

# motifstorage_EARc <-motif_positions_df <- do.call(rbind, lapply(seq_along(motif_EAR_close_1_results), function(i) {
#   positions <- motif_EAR_close_1_results[[i]]  # Positions from matchMotifs
#   seq_name <- names(seq_all_cd_200)[i]  # Get sequence ID from the original list
#
#   if (length(positions) > 0) {
#     # Create a data frame with sequence_id and motif positions
#     data.frame(
#       sequence_id = seq_name,  # Use the sequence name here
#       motif_position = unlist(positions)
#     )
#   } else {
#     NULL  # If no positions, return NULL
#   }
# }))
# #   
 # saveRDS(motifstorage_EARc, "data/Final_four_data/matchr_EAR_close_2.RDS")
#### PLOTING CODE BELOW THIS LINE FOR EAR_close  #####
motifstorage_EARc <- readRDS("data/Final_four_data/matchr_EAR_close_2.RDS")
motifstorage_EARc %>% 
mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  # dplyr::filter(id =="EAR_close"|id == "NR") %>%
   # dplyr::filter(relScore>.90) %>%
  mutate(position=motif_position.start-200) %>% 
  ggplot(.,aes(position, color = sequence_id))+
  geom_density(trim = FALSE,size=1.5) +
  theme_bw() +
  scale_color_manual(values=mrc_palette)+
  ggtitle("Atf3")

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

EAR_close_density_plot <- motifstorage_EARc %>% 
  mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  dplyr::filter(sequence_id == "EAR_close" | sequence_id == "NR") %>%
   mutate(position=motif_position.start-200) %>% 
  ggplot(., aes(position, color = sequence_id)) +
  geom_density(trim = FALSE, size = 1.5) +
  theme_bw() +
  scale_color_manual(values = mrc_palette) +
  ggtitle("Atf3")

# Assuming you already have the motif in a matrix or data frame for ggseqlogo

EAR_close_matrix_eg <- holder_EAR_close@motif  # If your motif is in PWM format

# Create the motif logo plot, this adds bits instead of "p" which is probability.
EAR_close_motif_logo_plot <- ggseqlogo(EAR_close_matrix_eg, method = "bits") + 
  theme_classic() +  
  ggtitle("EAR_close Motif Logo")
  
# Combine the density plot and motif logo plot using cowplot
  EAR_close_toprow <- plot_grid(NULL,EAR_close_motif_logo_plot, NULL, ncol = 3, rel_widths = c(.2,1,.2))
EAR_close_combined_plot <- plot_grid(EAR_close_toprow,EAR_close_density_plot,nrow=2, rel_heights = c(0.7,2))

# Print the combined plot
print(EAR_close_combined_plot)

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

ESR_close top motif

# pw_matrix_ESRc <- convert_motifs(holder_ESR_close, class = "TFBSTools-PWMatrix")
# # 
# motif_ESR_close_18_results <- lapply(seq_all_cd_200, function(sequences) {
# matchMotifs(pw_matrix_ESRc, sequences, out = "positions")
# })
# 
# motifstorage_ESRc <-motif_positions_df <- do.call(rbind, lapply(seq_along(motif_ESR_close_18_results), function(i) {
#   positions <- motif_ESR_close_18_results[[i]]  # Positions from matchMotifs
#   seq_name <- names(seq_all_cd_200)[i]  # Get sequence ID from the original list
# 
#   if (length(positions) > 0) {
#     # Create a data frame with sequence_id and motif positions
#     data.frame(
#       sequence_id = seq_name,  # Use the sequence name here
#       motif_position = unlist(positions)
#     )
#   } else {
#     NULL  # If no positions, return NULL
#   }
# }))
# #
#  saveRDS(motifstorage_ESRc, "data/Final_four_data/matchr_ESR_close_18.RDS")
#### PLOTING CODE BELOW THIS LINE FOR ESR_close  #####
motifstorage_ESRc <- readRDS("data/Final_four_data/matchr_ESR_close_18.RDS")
motifstorage_ESRc %>% 
mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  # dplyr::filter(id =="ESR_close"|id == "NR") %>%
   # dplyr::filter(relScore>.90) %>%
  mutate(position=motif_position.start-200) %>% 
  ggplot(.,aes(position, color = sequence_id))+
  geom_density(trim = FALSE,size=1.5) +
  theme_bw() +
  scale_color_manual(values=mrc_palette)+
  ggtitle("ZNF281")

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

ESR_close_density_plot <- motifstorage_ESRc %>% 
  mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  dplyr::filter(sequence_id == "ESR_close" | sequence_id == "NR") %>%
   mutate(position=motif_position.start-200) %>% 
  ggplot(., aes(position, color = sequence_id)) +
  geom_density(trim = FALSE, size = 1.5) +
  theme_bw() +
  scale_color_manual(values = mrc_palette) +
  ggtitle("ZNF281")

# Assuming you already have the motif in a matrix or data frame for ggseqlogo

ESR_close_matrix_eg <- holder_ESR_close@motif  # If your motif is in PWM format

# Create the motif logo plot, this adds bits instead of "p" which is probability.
ESR_close_motif_logo_plot <- ggseqlogo(ESR_close_matrix_eg, method = "bits") + 
  theme_classic() +  
  ggtitle("ESR_close Motif Logo")
  
# Combine the density plot and motif logo plot using cowplot
  ESR_close_toprow <- plot_grid(NULL,ESR_close_motif_logo_plot, NULL, ncol = 3, rel_widths = c(.2,1,.2))
ESR_close_combined_plot <- plot_grid(ESR_close_toprow,ESR_close_density_plot,nrow=2, rel_heights = c(0.7,2))

# Print the combined plot
print(ESR_close_combined_plot)

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

LR_close top motif

# pw_matrix_LRc <- convert_motifs(holder_LR_close, class = "TFBSTools-PWMatrix")
# # 
# motif_LR_close_1_results <- lapply(seq_all_cd_200, function(sequences) {
# matchMotifs(pw_matrix_LRc, sequences, out = "positions")
# })
# 
# motifstorage_LRc <-motif_positions_df <- do.call(rbind, lapply(seq_along(motif_LR_close_1_results), function(i) {
#   positions <- motif_LR_close_1_results[[i]]  # Positions from matchMotifs
#   seq_name <- names(seq_all_cd_200)[i]  # Get sequence ID from the original list
# 
#   if (length(positions) > 0) {
#     # Create a data frame with sequence_id and motif positions
#     data.frame(
#       sequence_id = seq_name,  # Use the sequence name here
#       motif_position = unlist(positions)
#     )
#   } else {
#     NULL  # If no positions, return NULL
#   }
# }))
# #
#  saveRDS(motifstorage_LRc, "data/Final_four_data/matchr_LR_close_1.RDS")
#### PLOTING CODE BELOW THIS LINE FOR LR_close  #####
motifstorage_LRc <- readRDS("data/Final_four_data/matchr_LR_close_1.RDS")
motifstorage_LRc %>% 
mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  # dplyr::filter(id =="LR_close"|id == "NR") %>%
   # dplyr::filter(relScore>.90) %>%
  mutate(position=motif_position.start-200) %>% 
  ggplot(.,aes(position, color = sequence_id))+
  geom_density(trim = FALSE,size=1.5) +
  theme_bw() +
  scale_color_manual(values=mrc_palette)+
  ggtitle("MEIS2")

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

LR_close_density_plot <- motifstorage_LRc %>% 
  mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  dplyr::filter(sequence_id == "LR_close" | sequence_id == "NR") %>%
   mutate(position=motif_position.start-200) %>% 
  ggplot(., aes(position, color = sequence_id)) +
  geom_density(trim = FALSE, size = 1.5) +
  theme_bw() +
  scale_color_manual(values = mrc_palette) +
  ggtitle("MEIS2")

# Assuming you already have the motif in a matrix or data frame for ggseqlogo

LR_close_matrix_eg <- holder_LR_close@motif  # If your motif is in PWM format

# Create the motif logo plot, this adds bits instead of "p" which is probability.
LR_close_motif_logo_plot <- ggseqlogo(LR_close_matrix_eg, method = "bits") + 
  theme_classic() +  
  ggtitle("LR_close Motif Logo")
  
# Combine the density plot and motif logo plot using cowplot
  LR_close_toprow <- plot_grid(NULL,LR_close_motif_logo_plot, NULL, ncol = 3, rel_widths = c(.2,1,.2))
LR_close_combined_plot <- plot_grid(LR_close_toprow,LR_close_density_plot,nrow=2, rel_heights = c(0.7,2))

# Print the combined plot
print(LR_close_combined_plot)

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

ESR_opcl top motif

# pw_matrix_ESR_opcl <- convert_motifs(holder_ESR_opcl, class = "TFBSTools-PWMatrix")
# #
# motif_ESR_opcl_2_results <- lapply(seq_all_cd_200, function(sequences) {
# matchMotifs(pw_matrix_ESR_opcl, sequences, out = "positions")
# })

# motifstorage_ESR_opcl <-motif_positions_df <- do.call(rbind, lapply(seq_along(motif_ESR_opcl_2_results), function(i) {
#   positions <- motif_ESR_opcl_2_results[[i]]  # Positions from matchMotifs
#   seq_name <- names(seq_all_cd_200)[i]  # Get sequence ID from the original list
# # 
#   if (length(positions) > 0) {
#     # Create a data frame with sequence_id and motif positions
#     data.frame(
#       sequence_id = seq_name,  # Use the sequence name here
#       motif_position = unlist(positions)
#     )
#   } else {
#     NULL  # If no positions, return NULL
#   }
# }))
#
 # saveRDS(motifstorage_ESR_opcl, "data/Final_four_data/matchr_ESR_opcl_2.RDS")
#### PLOTING CODE BELOW THIS LINE FOR ESR_opcl  #####
motifstorage_ESR_opcl <- readRDS("data/Final_four_data/matchr_ESR_opcl_2.RDS")
motifstorage_ESR_opcl %>% 
mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  # dplyr::filter(id =="ESR_opcl"|id == "NR") %>%
   # dplyr::filter(relScore>.90) %>%
  mutate(position=motif_position.start-200) %>% 
  ggplot(.,aes(position, color = sequence_id))+
  geom_density(trim = FALSE,size=1.5) +
  theme_bw() +
  scale_color_manual(values=mrc_palette)+
  ggtitle("ZNF384")

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

ESR_opcl_density_plot <- motifstorage_ESR_opcl %>% 
  mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  dplyr::filter(sequence_id == "ESR_C" | sequence_id == "NR") %>%
   mutate(position=motif_position.start-200) %>% 
  ggplot(., aes(position, color = sequence_id)) +
  geom_density(trim = FALSE, size = 1.5) +
  theme_bw() +
  scale_color_manual(values = mrc_palette) +
  ggtitle("ZNF384")

# Assuming you already have the motif in a matrix or data frame for ggseqlogo

ESR_opcl_matrix_eg <- holder_ESR_opcl@motif  # If your motif is in PWM format

# Create the motif logo plot, this adds bits instead of "p" which is probability.
ESR_opcl_motif_logo_plot <- ggseqlogo(ESR_opcl_matrix_eg, method = "bits") + 
  theme_classic() +  
  ggtitle("ESR_opcl Motif Logo")
  
# Combine the density plot and motif logo plot using cowplot
  ESR_opcl_toprow <- plot_grid(NULL,ESR_opcl_motif_logo_plot, NULL, ncol = 3, rel_widths = c(.2,1,.2))
ESR_opcl_combined_plot <- plot_grid(ESR_opcl_toprow,ESR_opcl_density_plot,nrow=2, rel_heights = c(0.7,2))

# Print the combined plot
print(ESR_opcl_combined_plot)

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

ESR_clop top motif

# pw_matrix_ESR_clop <- convert_motifs(holder_ESR_clop, class = "TFBSTools-PWMatrix")
# # #
# motif_ESR_clop_1_results <- lapply(seq_all_cd_200, function(sequences) {
# matchMotifs(pw_matrix_ESR_clop, sequences, out = "positions")
# })

# motifstorage_ESR_clop <-motif_positions_df <- do.call(rbind, lapply(seq_along(motif_ESR_clop_1_results), function(i) {
#   positions <- motif_ESR_clop_1_results[[i]]  # Positions from matchMotifs
#   seq_name <- names(seq_all_cd_200)[i]  # Get sequence ID from the original list
# #
#   if (length(positions) > 0) {
#     # Create a data frame with sequence_id and motif positions
#     data.frame(
#       sequence_id = seq_name,  # Use the sequence name here
#       motif_position = unlist(positions)
#     )
#   } else {
#     NULL  # If no positions, return NULL
#   }
# }))
#
 # saveRDS(motifstorage_ESR_clop, "data/Final_four_data/matchr_ESR_clop_1.RDS")
#### PLOTING CODE BELOW THIS LINE FOR ESR_clop  #####
motifstorage_ESR_clop <- readRDS("data/Final_four_data/matchr_ESR_clop_1.RDS")
motifstorage_ESR_clop %>% 
mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  # dplyr::filter(id =="ESR_clop"|id == "NR") %>%
   # dplyr::filter(relScore>.90) %>%
  mutate(position=motif_position.start-200) %>% 
  ggplot(.,aes(position, color = sequence_id))+
  geom_density(trim = FALSE,size=1.5) +
  theme_bw() +
  scale_color_manual(values=mrc_palette)+
  ggtitle("ATF3")

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

ESR_clop_density_plot <- motifstorage_ESR_clop %>% 
  mutate(sequence_id= gsub("_resized","",sequence_id)) %>% 
  dplyr::filter(sequence_id == "ESR_D" | sequence_id == "NR") %>%
   mutate(position=motif_position.start-200) %>% 
  ggplot(., aes(position, color = sequence_id)) +
  geom_density(trim = FALSE, size = 1.5) +
  theme_bw() +
  scale_color_manual(values = mrc_palette) +
  ggtitle("ATF3")

# Assuming you already have the motif in a matrix or data frame for ggseqlogo

ESR_clop_matrix_eg <- holder_ESR_clop@motif  # If your motif is in PWM format

# Create the motif logo plot, this adds bits instead of "p" which is probability.
ESR_clop_motif_logo_plot <- ggseqlogo(ESR_clop_matrix_eg, method = "bits") + 
  theme_classic() +  
  ggtitle("ESR_clop Motif Logo")
  
# Combine the density plot and motif logo plot using cowplot
  ESR_clop_toprow <- plot_grid(NULL,ESR_clop_motif_logo_plot, NULL, ncol = 3, rel_widths = c(.2,1,.2))
ESR_clop_combined_plot <- plot_grid(ESR_clop_toprow,ESR_clop_density_plot,nrow=2, rel_heights = c(0.7,2))

# Print the combined plot
print(ESR_clop_combined_plot)

Version	Author	Date
8520f12	E. Renee Matthews	2025-01-27
5bf51a6	reneeisnowhere	2024-10-18

sessionInfo()

R version 4.4.2 (2024-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/Chicago
tzcode source: internal

attached base packages:
[1] grid      stats4    stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] motifmatchr_1.28.0                      
 [2] ggseqlogo_0.2                           
 [3] universalmotif_1.24.2                   
 [4] data.table_1.17.0                       
 [5] BSgenome.Hsapiens.UCSC.hg38_1.4.5       
 [6] BSgenome_1.74.0                         
 [7] BiocIO_1.16.0                           
 [8] MotifDb_1.48.0                          
 [9] Biostrings_2.74.1                       
[10] XVector_0.46.0                          
[11] TFBSTools_1.44.0                        
[12] JASPAR2022_0.99.8                       
[13] BiocFileCache_2.14.0                    
[14] dbplyr_2.5.0                            
[15] devtools_2.4.5                          
[16] usethis_3.1.0                           
[17] ggpubr_0.6.0                            
[18] BiocParallel_1.40.0                     
[19] Cormotif_1.52.0                         
[20] affy_1.84.0                             
[21] scales_1.3.0                            
[22] VennDiagram_1.7.3                       
[23] futile.logger_1.4.3                     
[24] gridExtra_2.3                           
[25] ggfortify_0.4.17                        
[26] edgeR_4.4.2                             
[27] limma_3.62.2                            
[28] rtracklayer_1.66.0                      
[29] org.Hs.eg.db_3.20.0                     
[30] TxDb.Hsapiens.UCSC.hg38.knownGene_3.20.0
[31] GenomicFeatures_1.58.0                  
[32] AnnotationDbi_1.68.0                    
[33] Biobase_2.66.0                          
[34] GenomicRanges_1.58.0                    
[35] GenomeInfoDb_1.42.3                     
[36] IRanges_2.40.1                          
[37] S4Vectors_0.44.0                        
[38] BiocGenerics_0.52.0                     
[39] ChIPseeker_1.42.1                       
[40] RColorBrewer_1.1-3                      
[41] broom_1.0.7                             
[42] kableExtra_1.4.0                        
[43] cowplot_1.1.3                           
[44] lubridate_1.9.4                         
[45] forcats_1.0.0                           
[46] stringr_1.5.1                           
[47] dplyr_1.1.4                             
[48] purrr_1.0.4                             
[49] readr_2.1.5                             
[50] tidyr_1.3.1                             
[51] tibble_3.2.1                            
[52] ggplot2_3.5.1                           
[53] tidyverse_2.0.0                         
[54] workflowr_1.7.1                         

loaded via a namespace (and not attached):
  [1] fs_1.6.5                               
  [2] matrixStats_1.5.0                      
  [3] bitops_1.0-9                           
  [4] DirichletMultinomial_1.48.0            
  [5] enrichplot_1.26.6                      
  [6] httr_1.4.7                             
  [7] profvis_0.4.0                          
  [8] tools_4.4.2                            
  [9] backports_1.5.0                        
 [10] utf8_1.2.4                             
 [11] R6_2.6.1                               
 [12] lazyeval_0.2.2                         
 [13] urlchecker_1.0.1                       
 [14] withr_3.0.2                            
 [15] preprocessCore_1.68.0                  
 [16] cli_3.6.4                              
 [17] formatR_1.14                           
 [18] labeling_0.4.3                         
 [19] sass_0.4.9                             
 [20] Rsamtools_2.22.0                       
 [21] systemfonts_1.2.1                      
 [22] yulab.utils_0.2.0                      
 [23] DOSE_4.0.0                             
 [24] svglite_2.1.3                          
 [25] R.utils_2.13.0                         
 [26] sessioninfo_1.2.3                      
 [27] plotrix_3.8-4                          
 [28] rstudioapi_0.17.1                      
 [29] RSQLite_2.3.9                          
 [30] generics_0.1.3                         
 [31] gridGraphics_0.5-1                     
 [32] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
 [33] gtools_3.9.5                           
 [34] car_3.1-3                              
 [35] GO.db_3.20.0                           
 [36] Matrix_1.7-3                           
 [37] abind_1.4-8                            
 [38] R.methodsS3_1.8.2                      
 [39] lifecycle_1.0.4                        
 [40] whisker_0.4.1                          
 [41] yaml_2.3.10                            
 [42] carData_3.0-5                          
 [43] SummarizedExperiment_1.36.0            
 [44] gplots_3.2.0                           
 [45] qvalue_2.38.0                          
 [46] SparseArray_1.6.2                      
 [47] blob_1.2.4                             
 [48] promises_1.3.2                         
 [49] pwalign_1.2.0                          
 [50] crayon_1.5.3                           
 [51] miniUI_0.1.1.1                         
 [52] ggtangle_0.0.6                         
 [53] lattice_0.22-6                         
 [54] annotate_1.84.0                        
 [55] KEGGREST_1.46.0                        
 [56] pillar_1.10.1                          
 [57] knitr_1.49                             
 [58] fgsea_1.32.2                           
 [59] rjson_0.2.23                           
 [60] boot_1.3-31                            
 [61] codetools_0.2-20                       
 [62] fastmatch_1.1-6                        
 [63] glue_1.8.0                             
 [64] getPass_0.2-4                          
 [65] ggfun_0.1.8                            
 [66] remotes_2.5.0                          
 [67] vctrs_0.6.5                            
 [68] png_0.1-8                              
 [69] treeio_1.30.0                          
 [70] poweRlaw_1.0.0                         
 [71] gtable_0.3.6                           
 [72] cachem_1.1.0                           
 [73] xfun_0.51                              
 [74] S4Arrays_1.6.0                         
 [75] mime_0.12                              
 [76] statmod_1.5.0                          
 [77] ellipsis_0.3.2                         
 [78] nlme_3.1-167                           
 [79] ggtree_3.14.0                          
 [80] bit64_4.6.0-1                          
 [81] filelock_1.0.3                         
 [82] rprojroot_2.0.4                        
 [83] bslib_0.9.0                            
 [84] affyio_1.76.0                          
 [85] KernSmooth_2.23-26                     
 [86] splitstackshape_1.4.8                  
 [87] seqLogo_1.72.0                         
 [88] colorspace_2.1-1                       
 [89] DBI_1.2.3                              
 [90] tidyselect_1.2.1                       
 [91] processx_3.8.6                         
 [92] bit_4.6.0                              
 [93] compiler_4.4.2                         
 [94] curl_6.2.1                             
 [95] git2r_0.35.0                           
 [96] xml2_1.3.7                             
 [97] DelayedArray_0.32.0                    
 [98] caTools_1.18.3                         
 [99] callr_3.7.6                            
[100] digest_0.6.37                          
[101] rmarkdown_2.29                         
[102] htmltools_0.5.8.1                      
[103] pkgconfig_2.0.3                        
[104] MatrixGenerics_1.18.1                  
[105] fastmap_1.2.0                          
[106] rlang_1.1.5                            
[107] htmlwidgets_1.6.4                      
[108] UCSC.utils_1.2.0                       
[109] shiny_1.10.0                           
[110] farver_2.1.2                           
[111] jquerylib_0.1.4                        
[112] jsonlite_1.9.1                         
[113] GOSemSim_2.32.0                        
[114] R.oo_1.27.0                            
[115] RCurl_1.98-1.16                        
[116] magrittr_2.0.3                         
[117] Formula_1.2-5                          
[118] GenomeInfoDbData_1.2.13                
[119] ggplotify_0.1.2                        
[120] patchwork_1.3.0                        
[121] munsell_0.5.1                          
[122] Rcpp_1.0.14                            
[123] ape_5.8-1                              
[124] stringi_1.8.4                          
[125] MASS_7.3-65                            
[126] zlibbioc_1.52.0                        
[127] plyr_1.8.9                             
[128] pkgbuild_1.4.6                         
[129] parallel_4.4.2                         
[130] ggrepel_0.9.6                          
[131] CNEr_1.42.0                            
[132] splines_4.4.2                          
[133] hms_1.1.3                              
[134] locfit_1.5-9.12                        
[135] ps_1.9.0                               
[136] igraph_2.1.4                           
[137] ggsignif_0.6.4                         
[138] reshape2_1.4.4                         
[139] pkgload_1.4.0                          
[140] TFMPvalue_0.0.9                        
[141] futile.options_1.0.1                   
[142] XML_3.99-0.18                          
[143] evaluate_1.0.3                         
[144] lambda.r_1.2.4                         
[145] BiocManager_1.30.25                    
[146] tzdb_0.4.0                             
[147] httpuv_1.6.15                          
[148] xtable_1.8-4                           
[149] restfulr_0.0.15                        
[150] tidytree_0.4.6                         
[151] rstatix_0.7.2                          
[152] later_1.4.1                            
[153] viridisLite_0.4.2                      
[154] aplot_0.2.5                            
[155] memoise_2.0.1                          
[156] GenomicAlignments_1.42.0               
[157] timechange_0.3.0