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<title>Compare CENTIPEDE predictions for MEF2D for regions that differentially open between hypoxia vs. normoxia</title>
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<h1 class="title toc-ignore">Compare CENTIPEDE predictions for MEF2D for regions that differentially open between hypoxia vs. normoxia</h1>
<h4 class="author"><em>Kaixuan Luo</em></h4>
<h4 class="date"><em>7/25/2018</em></h4>
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<p><strong>Last updated:</strong> 2018-07-26</p>
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compare centipede predictions for MEF2D in DiffAC regions
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<p></details></p>
<hr />
<pre class="r"><code>library(ggplot2)
library(grid)
library(gridExtra)
suppressPackageStartupMessages(library(GenomicRanges))
library(limma)</code></pre>
<pre><code>
Attaching package: 'limma'</code></pre>
<pre><code>The following object is masked from 'package:BiocGenerics':
plotMA</code></pre>
<pre class="r"><code>library(edgeR)
library(VennDiagram)</code></pre>
<pre><code>Warning: package 'VennDiagram' was built under R version 3.4.4</code></pre>
<pre><code>Loading required package: futile.logger</code></pre>
<pre class="r"><code>message <- futile.logger::flog.threshold(futile.logger::ERROR, name = "VennDiagramLogger")
## venn diagram
plot_venn_overlaps <- function(overlaps.m, title = "", col_fill = NULL, category.names = NULL){
grid.newpage()
overlaps_venn.l <- lapply(as.data.frame(overlaps.m), function(x) which(x == 1))
if(is.null(col_fill)){
col_fill <- 1:length(overlaps_venn.l)
}
if(is.null(category.names)){
category.names <- names(x)
}
venn.plot <- venn.diagram(
x = overlaps_venn.l,
category.names = category.names,
filename = NULL,
fill = col_fill,
alpha=rep(0.5, length(overlaps_venn.l)),
cex = 1.5,
cat.fontface=4,
main=title)
grid.draw(venn.plot)
}</code></pre>
<div id="parameters" class="section level2">
<h2>parameters</h2>
<pre class="r"><code>tf_name <- "MEF2D"
pwm_name <- "MEF2D_MA0773.1_1e-4"
thresh_PostPr_bound <- 0.99
flank <- 100
cat("PWM name: ", pwm_name, "\n")</code></pre>
<pre><code>PWM name: MEF2D_MA0773.1_1e-4 </code></pre>
</div>
<div id="load-diff-accessibility-test-results-comparing-hypoxia-vs.normoxia." class="section level2">
<h2>load diff accessibility test results, comparing hypoxia vs. normoxia.</h2>
<ul>
<li>log fold change > 0 indicates differentially open in hypoxia.</li>
<li>log fold change < 0 indicates differentially open in normoxia.</li>
</ul>
<pre class="r"><code>diffAC_regions.df <- read.csv("~/Dropbox/research/ATAC_DNase/ATAC-seq_Olivia_Gray/results/DiffAC_regions/ordered_results_withcoords.csv")
cat(nrow(diffAC_regions.df), "regions in total \n")</code></pre>
<pre><code>138927 regions in total </code></pre>
<pre class="r"><code>diffAC_regions.df <- diffAC_regions.df[, c("chr", "Start", "End","GeneID", "baseMean", "Strand", "log2FoldChange", "lfcSE", "stat", "pvalue", "padj")]
diffAC_sig_regions.df <- diffAC_regions.df[diffAC_regions.df$padj < 0.1, ]
cat(nrow(diffAC_sig_regions.df), "significant regions \n")</code></pre>
<pre><code>2390 significant regions </code></pre>
<pre class="r"><code>hist(diffAC_regions.df$log2FoldChange, xlab = "log2FoldChange", main = "Differentially open regions (FDR < 10%)")</code></pre>
<p><img src="figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-3-1.png" width="672" style="display: block; margin: auto;" /></p>
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<pre class="r"><code>diffAC_sigH_regions.df <- diffAC_sig_regions.df[diffAC_sig_regions.df$log2FoldChange > 0, ]
cat(nrow(diffAC_sigH_regions.df), "regions differentially open in hypoxia. \n")</code></pre>
<pre><code>201 regions differentially open in hypoxia. </code></pre>
<pre class="r"><code>diffAC_sigN_regions.df <- diffAC_sig_regions.df[diffAC_sig_regions.df$log2FoldChange < 0, ]
cat(nrow(diffAC_sigN_regions.df), "regions differentially open in normoxia. \n")</code></pre>
<pre><code>2189 regions differentially open in normoxia. </code></pre>
<pre class="r"><code>diffAC_sig_regions.gr <- makeGRangesFromDataFrame(diffAC_sig_regions.df, start.field = "Start", end.field = "End", keep.extra.columns = T)
diffAC_sigH_regions.gr <- makeGRangesFromDataFrame(diffAC_sigH_regions.df, start.field = "Start", end.field = "End", keep.extra.columns = T)
diffAC_sigN_regions.gr <- makeGRangesFromDataFrame(diffAC_sigN_regions.df, start.field = "Start", end.field = "End", keep.extra.columns = T)</code></pre>
</div>
<div id="load-centipede-predictions" class="section level2">
<h2>load CENTIPEDE predictions</h2>
<pre class="r"><code>dir_predictions <- paste0("~/Dropbox/research/ATAC_DNase/ATAC-seq_Olivia_Gray/results/centipede_predictions/", pwm_name)
## condition: N
bam_namelist_N <- c("N1_nomito_rdup.bam", "N2_nomito_rdup.bam", "N3_nomito_rdup.bam")
site_predictions_N.l <- vector("list", 3)
names(site_predictions_N.l) <- bam_namelist_N
for(i in 1:length(bam_namelist_N)){
bam_basename <- tools::file_path_sans_ext(basename(bam_namelist_N[[i]]))
site_predictions_N.l[[i]] <- read.table(paste0(dir_predictions, "/", pwm_name, "_", bam_basename, "_predictions.txt"), header = T, stringsAsFactors = F)
}
CentPostPr_N.df <- data.frame(N1 = site_predictions_N.l[[1]]$CentPostPr,
N2 = site_predictions_N.l[[2]]$CentPostPr,
N3 = site_predictions_N.l[[3]]$CentPostPr)
CentLogRatios_N.df <- data.frame(N1 = site_predictions_N.l[[1]]$CentLogRatios,
N2 = site_predictions_N.l[[2]]$CentLogRatios,
N3 = site_predictions_N.l[[3]]$CentLogRatios)
## condition: H
bam_namelist_H <- c("H1_nomito_rdup.bam", "H2_nomito_rdup.bam", "H3_nomito_rdup.bam")
site_predictions_H.l <- vector("list", 3)
names(site_predictions_H.l) <- bam_namelist_H
for(i in 1:length(bam_namelist_H)){
bam_basename <- tools::file_path_sans_ext(basename(bam_namelist_H[[i]]))
site_predictions_H.l[[i]] <- read.table(paste0(dir_predictions, "/", pwm_name, "_", bam_basename, "_predictions.txt"), header = T, stringsAsFactors = F)
}
CentPostPr_H.df <- data.frame(H1 = site_predictions_H.l[[1]]$CentPostPr,
H2 = site_predictions_H.l[[2]]$CentPostPr,
H3 = site_predictions_H.l[[3]]$CentPostPr)
CentLogRatios_H.df <- data.frame(H1 = site_predictions_H.l[[1]]$CentLogRatios,
H2 = site_predictions_H.l[[2]]$CentLogRatios,
H3 = site_predictions_H.l[[3]]$CentLogRatios)
if(any(site_predictions_N.l[[1]]$name != site_predictions_H.l[[1]]$name)){
stop("sites not match!")
}
sites.df <- site_predictions_N.l[[1]][,1:7]
## get motif coordinates
if(sites.df[1, "end"] - sites.df[1, "start"] > flank){
sites.df$start <- sites.df$start + flank
sites.df$end <- sites.df$end - flank
}
sites.gr <- makeGRangesFromDataFrame(sites.df, start.field = "start", end.field = "end", keep.extra.columns = F)
CentPostPr.df <- cbind(CentPostPr_N.df, CentPostPr_H.df)
CentLogRatios.df <- cbind(CentLogRatios_N.df, CentLogRatios_H.df)
sites_CentPostPr.df <- cbind(sites.df, CentPostPr_N.df, CentPostPr_H.df)
sites_CentLogRatios.df <- cbind(sites.df, CentLogRatios_N.df, CentLogRatios_H.df)</code></pre>
</div>
<div id="intersect-centipede-sites-with-diffac-regions" class="section level2">
<h2>intersect CENTIPEDE sites with diffAC regions</h2>
<pre class="r"><code>overlaps_diffAC.df <- as.data.frame(findOverlaps(query = sites.gr, subject = diffAC_sig_regions.gr, type = "within", ignore.strand = T))
idx_sites_diffAC <- unique(overlaps_diffAC.df$queryHits)
cat(length(idx_sites_diffAC), "candidate motif sites differentially open in hypoxia or normoxia. \n")</code></pre>
<pre><code>123 candidate motif sites differentially open in hypoxia or normoxia. </code></pre>
<pre class="r"><code>overlaps_sigH.df <- as.data.frame(findOverlaps(query = sites.gr, subject = diffAC_sigH_regions.gr, type = "within", ignore.strand = T))
idx_sites_sigH <- unique(overlaps_sigH.df$queryHits)
cat(length(idx_sites_sigH), "candidate motif sites differentially open in hypoxia. \n")</code></pre>
<pre><code>23 candidate motif sites differentially open in hypoxia. </code></pre>
<pre class="r"><code>overlaps_sigN.df <- as.data.frame(findOverlaps(query = sites.gr, subject = diffAC_sigN_regions.gr, type = "within", ignore.strand = T))
idx_sites_sigN <- unique(overlaps_sigN.df$queryHits)
cat(length(idx_sites_sigN), "candidate motif sites differentially open in normoxia. \n")</code></pre>
<pre><code>100 candidate motif sites differentially open in normoxia. </code></pre>
</div>
<div id="number-of-reads-mapped" class="section level2">
<h2>number of reads mapped</h2>
<pre class="r"><code>dir_bam <- "~/Dropbox/research/ATAC_DNase/ATAC-seq_Olivia_Gray/ATAC-seq_BAMfiles/"
bam_basename_list <- c("N1_nomito_rdup", "N2_nomito_rdup", "N3_nomito_rdup",
"H1_nomito_rdup", "H2_nomito_rdup", "H3_nomito_rdup")
reads_mapped <- rep(NA, length = length(bam_basename_list))
names(reads_mapped) <- bam_basename_list
for(bam_basename in bam_basename_list){
readstats_name <- paste0(dir_bam, "/", bam_basename, ".idxstats.txt")
readstats.df <- read.table(readstats_name, header = F)
reads_mapped[bam_basename] <- sum(readstats.df[,3])
}
cat("Number of reads mapped (million): \n")</code></pre>
<pre><code>Number of reads mapped (million): </code></pre>
<pre class="r"><code>print(reads_mapped/1e6)</code></pre>
<pre><code>N1_nomito_rdup N2_nomito_rdup N3_nomito_rdup H1_nomito_rdup H2_nomito_rdup
44.52970 45.87505 43.06390 30.81426 38.17168
H3_nomito_rdup
37.04096 </code></pre>
</div>
<div id="binarize-to-bound-and-unbound" class="section level2">
<h2>binarize to bound and unbound</h2>
<pre class="r"><code>cat("Number of bound sites that are differentially open in hypoxia: \n")</code></pre>
<pre><code>Number of bound sites that are differentially open in hypoxia: </code></pre>
<pre class="r"><code>colSums(CentPostPr.df[idx_sites_sigH, ] > thresh_PostPr_bound)</code></pre>
<pre><code>N1 N2 N3 H1 H2 H3
19 19 16 23 20 23 </code></pre>
<pre class="r"><code>cat("Number of bound sites that are differentially open in normoxia: \n")</code></pre>
<pre><code>Number of bound sites that are differentially open in normoxia: </code></pre>
<pre class="r"><code>colSums(CentPostPr.df[idx_sites_sigN, ] > thresh_PostPr_bound)</code></pre>
<pre><code> N1 N2 N3 H1 H2 H3
100 99 99 80 71 90 </code></pre>
</div>
<div id="average-binding-probablity-and-average-logratios" class="section level2">
<h2>Average binding probablity and average logRatios</h2>
<div id="all-motif-sites" class="section level3">
<h3>all motif sites</h3>
<pre class="r"><code># binding probablity
par(pty="s")
plot(rowMeans(CentPostPr_N.df), rowMeans(CentPostPr_H.df),
xlab = "N average P(Bound)", ylab = "H average P(Bound)", main = tf_name,
pch = ".", col = rgb(0,0,1,0.7))
abline(a=0, b=1, col = "darkgray")</code></pre>
<p><img src="figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-8-1.png" width="672" style="display: block; margin: auto;" /></p>
<details> <summary><em>Expand here to see past versions of unnamed-chunk-8-1.png:</em></summary>
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Author
</th>
<th style="text-align:left;">
Date
</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;">
<a href="https://github.com/kevinlkx/ATAC-seq_footprint_analysis/blob/84c08c3f01cee2e3c199d98e31f053501908bdcf/docs/figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-8-1.png" target="_blank">84c08c3</a>
</td>
<td style="text-align:left;">
kevinlkx
</td>
<td style="text-align:left;">
2018-07-26
</td>
</tr>
</tbody>
</table>
<p></details></p>
<pre class="r"><code># logRatios
par(mfrow = c(1,2))
par(pty="s")
plot(rowMeans(CentLogRatios_N.df), rowMeans(CentLogRatios_H.df),
xlab = "N average logRatios", ylab = "H average logRatios", main = tf_name,
pch = ".", col = rgb(0,0,1,0.7))
abline(a=0,b=1,col = "darkgray")
plot(x = (rowMeans(CentLogRatios_H.df)+rowMeans(CentLogRatios_N.df))/2,
y = rowMeans(CentLogRatios_H.df) - rowMeans(CentLogRatios_N.df),
xlab = "average logRatios", ylab = "Difference in logRatios (H - N)", main = tf_name,
pch = ".", col = rgb(0,0,1,0.7))
abline(v=0, h=0, col = "darkgray")</code></pre>
<p><img src="figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-8-2.png" width="672" style="display: block; margin: auto;" /></p>
<details> <summary><em>Expand here to see past versions of unnamed-chunk-8-2.png:</em></summary>
<table style="border-collapse:separate; border-spacing:5px;">
<thead>
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<th style="text-align:left;">
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</th>
<th style="text-align:left;">
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</th>
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</thead>
<tbody>
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<td style="text-align:left;">
<a href="https://github.com/kevinlkx/ATAC-seq_footprint_analysis/blob/84c08c3f01cee2e3c199d98e31f053501908bdcf/docs/figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-8-2.png" target="_blank">84c08c3</a>
</td>
<td style="text-align:left;">
kevinlkx
</td>
<td style="text-align:left;">
2018-07-26
</td>
</tr>
</tbody>
</table>
<p></details></p>
</div>
<div id="sites-that-are-differentially-open-in-hypoxia" class="section level3">
<h3>sites that are differentially open in hypoxia</h3>
<pre class="r"><code>cat(length(idx_sites_sigH), "candidate motif sites differentially open in hypoxia. \n")</code></pre>
<pre><code>23 candidate motif sites differentially open in hypoxia. </code></pre>
<pre class="r"><code># binding probablity
par(pty="s")
plot(rowMeans(CentPostPr_N.df[idx_sites_sigH,]), rowMeans(CentPostPr_H.df[idx_sites_sigH,]),
xlab = "N average P(Bound)", ylab = "H average P(Bound)", main = paste(tf_name, "bound sites"),
pch = 20, col = rgb(0,0,1,0.7))
abline(a=0, b=1, col = "darkgray")</code></pre>
<p><img src="figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-9-1.png" width="672" style="display: block; margin: auto;" /></p>
<details> <summary><em>Expand here to see past versions of unnamed-chunk-9-1.png:</em></summary>
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Author
</th>
<th style="text-align:left;">
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<td style="text-align:left;">
<a href="https://github.com/kevinlkx/ATAC-seq_footprint_analysis/blob/84c08c3f01cee2e3c199d98e31f053501908bdcf/docs/figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-9-1.png" target="_blank">84c08c3</a>
</td>
<td style="text-align:left;">
kevinlkx
</td>
<td style="text-align:left;">
2018-07-26
</td>
</tr>
</tbody>
</table>
<p></details></p>
<pre class="r"><code># logRatios
par(mfrow = c(1,2))
par(pty="s")
plot(rowMeans(CentLogRatios_N.df[idx_sites_sigH,]), rowMeans(CentLogRatios_H.df[idx_sites_sigH,]),
xlab = "N average logRatios", ylab = "H average logRatios", main = tf_name,
pch = 20, col = rgb(0,0,1,0.7))
abline(a=0,b=1,col = "darkgray")
plot(x = (rowMeans(CentLogRatios_H.df[idx_sites_sigH,])+rowMeans(CentLogRatios_N.df[idx_sites_sigH,]))/2,
y = rowMeans(CentLogRatios_H.df[idx_sites_sigH,]) - rowMeans(CentLogRatios_N.df[idx_sites_sigH,]),
xlab = "average logRatios", ylab = "Difference in logRatios (H - N)", main = tf_name,
pch = 20, col = rgb(0,0,1,0.7))
abline(v=0, h=0, col = "darkgray")</code></pre>
<p><img src="figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-9-2.png" width="672" style="display: block; margin: auto;" /></p>
<details> <summary><em>Expand here to see past versions of unnamed-chunk-9-2.png:</em></summary>
<table style="border-collapse:separate; border-spacing:5px;">
<thead>
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<th style="text-align:left;">
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<td style="text-align:left;">
<a href="https://github.com/kevinlkx/ATAC-seq_footprint_analysis/blob/84c08c3f01cee2e3c199d98e31f053501908bdcf/docs/figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-9-2.png" target="_blank">84c08c3</a>
</td>
<td style="text-align:left;">
kevinlkx
</td>
<td style="text-align:left;">
2018-07-26
</td>
</tr>
</tbody>
</table>
<p></details></p>
</div>
<div id="sites-that-are-differentially-open-in-normoxia" class="section level3">
<h3>sites that are differentially open in normoxia</h3>
<pre class="r"><code>cat(length(idx_sites_sigN), "candidate motif sites differentially open in normoxia \n")</code></pre>
<pre><code>100 candidate motif sites differentially open in normoxia </code></pre>
<pre class="r"><code># binding probablity
par(pty="s")
plot(rowMeans(CentPostPr_N.df[idx_sites_sigN,]), rowMeans(CentPostPr_H.df[idx_sites_sigN,]),
xlab = "N average P(Bound)", ylab = "H average P(Bound)", main = paste(tf_name, "bound sites"),
pch = 20, col = rgb(0,0,1,0.7))
abline(a=0, b=1, col = "darkgray")</code></pre>
<p><img src="figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-10-1.png" width="672" style="display: block; margin: auto;" /></p>
<details> <summary><em>Expand here to see past versions of unnamed-chunk-10-1.png:</em></summary>
<table style="border-collapse:separate; border-spacing:5px;">
<thead>
<tr>
<th style="text-align:left;">
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<th style="text-align:left;">
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</th>
<th style="text-align:left;">
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</th>
</tr>
</thead>
<tbody>
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<td style="text-align:left;">
<a href="https://github.com/kevinlkx/ATAC-seq_footprint_analysis/blob/84c08c3f01cee2e3c199d98e31f053501908bdcf/docs/figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-10-1.png" target="_blank">84c08c3</a>
</td>
<td style="text-align:left;">
kevinlkx
</td>
<td style="text-align:left;">
2018-07-26
</td>
</tr>
</tbody>
</table>
<p></details></p>
<pre class="r"><code># logRatios
par(mfrow = c(1,2))
par(pty="s")
plot(rowMeans(CentLogRatios_N.df[idx_sites_sigN,]), rowMeans(CentLogRatios_H.df[idx_sites_sigN,]),
xlab = "N average logRatios", ylab = "H average logRatios", main = tf_name,
pch = 20, col = rgb(0,0,1,0.7))
abline(a=0,b=1,col = "darkgray")
plot(x = (rowMeans(CentLogRatios_H.df[idx_sites_sigN,])+rowMeans(CentLogRatios_N.df[idx_sites_sigN,]))/2,
y = rowMeans(CentLogRatios_H.df[idx_sites_sigN,]) - rowMeans(CentLogRatios_N.df[idx_sites_sigN,]),
xlab = "average logRatios", ylab = "Difference in logRatios (H - N)", main = tf_name,
pch = 20, col = rgb(0,0,1,0.7))
abline(v=0, h=0, col = "darkgray")</code></pre>
<p><img src="figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-10-2.png" width="672" style="display: block; margin: auto;" /></p>
<details> <summary><em>Expand here to see past versions of unnamed-chunk-10-2.png:</em></summary>
<table style="border-collapse:separate; border-spacing:5px;">
<thead>
<tr>
<th style="text-align:left;">
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</th>
<th style="text-align:left;">
Author
</th>
<th style="text-align:left;">
Date
</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;">
<a href="https://github.com/kevinlkx/ATAC-seq_footprint_analysis/blob/84c08c3f01cee2e3c199d98e31f053501908bdcf/docs/figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-10-2.png" target="_blank">84c08c3</a>
</td>
<td style="text-align:left;">
kevinlkx
</td>
<td style="text-align:left;">
2018-07-26
</td>
</tr>
</tbody>
</table>
<p></details></p>
</div>
</div>
<div id="compare-logratios-for-differentially-accessible-sites-using-limma" class="section level2">
<h2>Compare logRatios for differentially accessible sites using limma</h2>
<pre class="r"><code>targets <- data.frame(bam = c(bam_namelist_N, bam_namelist_H),
label = colnames(CentLogRatios.df),
condition = rep(c("N", "H"), each = 3))
print(targets)</code></pre>
<pre><code> bam label condition
1 N1_nomito_rdup.bam N1 N
2 N2_nomito_rdup.bam N2 N
3 N3_nomito_rdup.bam N3 N
4 H1_nomito_rdup.bam H1 H
5 H2_nomito_rdup.bam H2 H
6 H3_nomito_rdup.bam H3 H</code></pre>
<pre class="r"><code>condition <- factor(targets$condition, levels = c("N", "H"))
design <- model.matrix(~0+condition)
colnames(design) <- levels(condition)
print(design)</code></pre>
<pre><code> N H
1 1 0
2 1 0
3 1 0
4 0 1
5 0 1
6 0 1
attr(,"assign")
[1] 1 1
attr(,"contrasts")
attr(,"contrasts")$condition
[1] "contr.treatment"</code></pre>
<pre class="r"><code>CentLogRatios_diffAC.df <- CentLogRatios.df[idx_sites_diffAC, ]
fit <- lmFit(CentLogRatios_diffAC.df, design)
contrasts <- makeContrasts(H-N, levels=design)
fit2 <- contrasts.fit(fit, contrasts)
fit2 <- eBayes(fit2, trend=TRUE)
num_diffbind <- summary(decideTests(fit2))
percent_diffbind <- round(num_diffbind / sum(num_diffbind) * 100, 2)
cat(num_diffbind[1], "sites differentially open in normoxia (", percent_diffbind[1], "%) \n",
num_diffbind[3], "sites differentially open in hypoxia (", percent_diffbind[3], "%) \n",
num_diffbind[2], "sites not significantly different (", percent_diffbind[2], "%) \n")</code></pre>
<pre><code>0 sites differentially open in normoxia ( 0 %)
0 sites differentially open in hypoxia ( 0 %)
123 sites not significantly different ( 100 %) </code></pre>
<pre class="r"><code># volcanoplot(fit2, main="H vs. N", xlab = "Difference in logRatios (H - N)")
plot(x = fit2$coef, y = -log10(fit2$p.value),
xlab = "Difference in logRatios (H - N)", ylab = "-log10(P-value)", main= paste(tf_name, "H vs. N"),
pch = 16, cex = 0.35)</code></pre>
<p><img src="figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-11-1.png" width="672" style="display: block; margin: auto;" /></p>
<details> <summary><em>Expand here to see past versions of unnamed-chunk-11-1.png:</em></summary>
<table style="border-collapse:separate; border-spacing:5px;">
<thead>
<tr>
<th style="text-align:left;">
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</th>
<th style="text-align:left;">
Author
</th>
<th style="text-align:left;">
Date
</th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;">
<a href="https://github.com/kevinlkx/ATAC-seq_footprint_analysis/blob/84c08c3f01cee2e3c199d98e31f053501908bdcf/docs/figure/compare_centipede_predictions_DiffACregions_MEF2D.Rmd/unnamed-chunk-11-1.png" target="_blank">84c08c3</a>
</td>
<td style="text-align:left;">
kevinlkx
</td>
<td style="text-align:left;">
2018-07-26
</td>
</tr>
</tbody>
</table>
<p></details></p>
</div>
<div id="session-information" class="section level2">
<h2>Session information</h2>
<pre class="r"><code>sessionInfo()</code></pre>
<pre><code>R version 3.4.3 (2017-11-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.6
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] parallel stats4 grid stats graphics grDevices utils
[8] datasets methods base
other attached packages:
[1] VennDiagram_1.6.20 futile.logger_1.4.3 edgeR_3.20.9
[4] limma_3.34.9 GenomicRanges_1.30.3 GenomeInfoDb_1.14.0
[7] IRanges_2.12.0 S4Vectors_0.16.0 BiocGenerics_0.24.0
[10] gridExtra_2.3 ggplot2_2.2.1
loaded via a namespace (and not attached):
[1] Rcpp_0.12.16 formatR_1.5 XVector_0.18.0
[4] compiler_3.4.3 pillar_1.2.2 git2r_0.21.0
[7] plyr_1.8.4 workflowr_1.1.1 futile.options_1.0.1
[10] zlibbioc_1.24.0 R.methodsS3_1.7.1 R.utils_2.6.0
[13] bitops_1.0-6 tools_3.4.3 digest_0.6.15
[16] lattice_0.20-35 evaluate_0.10.1 tibble_1.4.2
[19] gtable_0.2.0 rlang_0.2.0 yaml_2.1.18
[22] GenomeInfoDbData_1.0.0 stringr_1.3.0 knitr_1.20
[25] locfit_1.5-9.1 rprojroot_1.3-2 rmarkdown_1.9
[28] lambda.r_1.2.2 magrittr_1.5 whisker_0.3-2
[31] splines_3.4.3 backports_1.1.2 scales_0.5.0
[34] htmltools_0.3.6 colorspace_1.3-2 stringi_1.1.7
[37] RCurl_1.95-4.10 lazyeval_0.2.1 munsell_0.4.3
[40] R.oo_1.22.0 </code></pre>
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