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figure_2_a_b.Rmd
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figure_2_a_b.Rmd
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``` {r setup, echo=FALSE, message=FALSE, include=FALSE, error=FALSE}
library(xtable)
library(magrittr)
library(ggplot2)
library(BSgenome.Dmelanogaster.UCSC.dm3)
library(BSgenome.Hsapiens.UCSC.hg19)
# Output folder for this document
options(knitr.figure_dir = "figure_2_a_b_output")
source("shared_code/knitr_common.r")
source("shared_code/granges_common.r")
source("shared_code/samples.r")
source("shared_code/ggplot_theme.r")
```
# Figure 2
``` {r header_child, child="child_docs/header_child.Rmd"}
```
## Overview
MACS v2 was run on ChIP-nexus samples with these settings: `--keep-dup=all --call-summits` and `-g dm` or `-g hg`, depending on species.
``` {r set_bigwig_paths, include=FALSE}
chipseq.bws <- list(hsap_k562_tbp_chipseq_01=data_path("bigwigs/hsap_k562_tbp_chipseq_01.bw"),
dmel_embryo_twi_chipseq_01=data_path("bigwigs/dmel_embryo_twi_chipseq_01.bw"),
dmel_embryo_dl_chipseq_01=data_path("bigwigs/dmel_embryo_dl_chipseq_01.bw"))
```
``` {r macs_import, include=FALSE}
factor_name_from_filename <- function(filename) {
gsub("^...._.*_(.*)_chip.*_0._.*$", "\\1", basename(filename))
}
import_and_filter_peaks <- function(filename, max.peaks=10000) {
factor_name <- factor_name_from_filename(filename)
peaks.gr <- filter_chrs(import(filename))
peaks.gr <- peaks.gr[order(peaks.gr$score, decreasing=TRUE)]
peaks.gr <- resize(peaks.gr, width=201, fix="center")
peaks.gr <- peaks.gr[1:min(c(length(peaks.gr), max.peaks))]
peaks.gr
}
peak_summary_table <- function(grl) {
data.frame(sample=names(grl),
peaks=pn(elementLengths(grl)),
median_width=sapply(grl, function(gr) { median(width(gr)) }))
}
chipseq_peak_files <- list.files("peak_calling/macs", "chipseq.*bed\\.gz$", full.names=TRUE)
chipseq.grl <- cache("chipseq.grl.rds", function() {
lapply(chipseq_peak_files, import_and_filter_peaks)
})
names(chipseq.grl) <- chipseq_peak_files %>%
gsub("_summits\\.bed\\.gz$", "", .) %>%
gsub("peak_calling/macs/", "", .)
chipnexus_peak_files <- list.files("peak_calling/macs", "chipnexus.*bed\\.gz$", full.names=TRUE)
chipnexus.grl <- cache("chipnexus.grl.rds", function() {
lapply(chipnexus_peak_files, import_and_filter_peaks)
})
names(chipnexus.grl) <- chipnexus_peak_files %>%
gsub("_summits\\.bed\\.gz$", "", .) %>%
gsub("peak_calling/macs/", "", .)
```
``` {r scatterplots_common}
add_signal <- function(peaks.gr, sample1.cov, sample2.cov) {
mcols(peaks.gr)$signal_1 <- regionSums(peaks.gr, sample1.cov)
mcols(peaks.gr)$signal_2 <- regionSums(peaks.gr, sample2.cov)
peaks.gr
}
finite_range <- function(values) {
values <- values[is.finite(values)]
list(max=max(values), min=min(values))
}
make_plot <- function(peaks.gr, title, sample1, sample2) {
if(length(grep("chipseq", sample1)) > 0) {
sample1.cov <- chipseq.bws[[sample1]]
} else {
sample1.cov <- get_sample_cl(sample1)$cov
}
if(length(grep("chipseq", sample2)) > 0) {
sample2.cov <- chipseq.bws[[sample2]]
} else {
sample2.cov <- get_sample_cl(sample2)$cov
}
peaks.gr <- add_signal(peaks.gr, sample1.cov, sample2.cov)
pearson.cor <- round(with(mcols(peaks.gr), cor(signal_1, signal_2, method="pearson")), 3)
xmin <- min(log2(mcols(peaks.gr)$signal_1))
ymax <- max(log2(mcols(peaks.gr)$signal_2))
even_numbers <- seq(from=0, to=50, by=2)
xrange <- finite_range(log2(mcols(peaks.gr)$signal_1))
yrange <- finite_range(log2(mcols(peaks.gr)$signal_2))
xbreaks <- even_numbers[even_numbers >= xrange$min & even_numbers <= xrange$max]
ybreaks <- even_numbers[even_numbers >= yrange$min & even_numbers <= yrange$max]
g <- ggplot(as.data.frame(peaks.gr), aes(x=log2(signal_1), y=log2(signal_2))) +
geom_point(size=1, alpha=0.5, color="black") +
scale_x_continuous(breaks=xbreaks) +
scale_y_continuous(breaks=ybreaks) +
annotate("text", x=xmin, y=ymax,
color="darkblue",
hjust=-1,
label=paste0("Pearson: ", pearson.cor)) +
theme_manuscript(16) +
labs(x=paste0(sample1, " signal (log2)"),
y=paste0(sample2, " signal (log2)"),
title=title)
g
}
make_plot_with_labels <- function(peaks.gr, title, sample1, sample2, labeled_regions.gr) {
ol <- as.data.frame(findOverlaps(peaks.gr, labeled_regions.gr, ignore.strand=TRUE))
peaks.gr$region_label <- ""
peaks.gr$region_label[ol$queryHits] <- paste0(" ", labeled_regions.gr$name[ol$subjectHits])
peaks.gr$known_enhancer <- "No"
peaks.gr$known_enhancer[ol$queryHits] <- "Yes"
if(length(grep("chipseq", sample1)) > 0) {
sample1.cov <- chipseq.bws[[sample1]]
} else {
sample1.cov <- get_sample_cl(sample1)$cov
}
if(length(grep("chipseq", sample2)) > 0) {
sample2.cov <- chipseq.bws[[sample2]]
} else {
sample2.cov <- get_sample_cl(sample2)$cov
}
peaks.gr <- add_signal(peaks.gr, sample1.cov, sample2.cov)
pearson.cor <- round(with(mcols(peaks.gr), cor(signal_1, signal_2, method="pearson")), 3)
xmin <- min(log2(mcols(peaks.gr)$signal_1))
ymax <- max(log2(mcols(peaks.gr)$signal_2))
even_numbers <- seq(from=0, to=50, by=2)
xrange <- finite_range(log2(mcols(peaks.gr)$signal_1))
yrange <- finite_range(log2(mcols(peaks.gr)$signal_2))
xbreaks <- even_numbers[even_numbers >= xrange$min & even_numbers <= xrange$max]
ybreaks <- even_numbers[even_numbers >= yrange$min & even_numbers <= yrange$max]
g <- ggplot(as.data.frame(peaks.gr), aes(x=log2(signal_1), y=log2(signal_2), color=known_enhancer)) +
geom_point(aes(size=known_enhancer), alpha=0.5) +
scale_size_manual(values=c("Yes"=3, "No"=1), guide="none") +
geom_text(data=subset(as.data.frame(peaks.gr), region_label != ""),
size=3, hjust=0, vjust=0, color="red",
aes(label=region_label)) +
scale_colour_manual(name="Known enhancer",
values=c("Yes"="red", "No"="black"),
guide=guide_legend(override.aes=list(alpha=1, size=3))) +
scale_x_continuous(breaks=xbreaks) +
scale_y_continuous(breaks=ybreaks) +
annotate("text", x=xmin, y=ymax,
color="darkblue",
hjust=-1,
label=paste0("Pearson: ", pearson.cor)) +
theme_manuscript(16) +
labs(x=paste0(sample1, " signal (log2)"),
y=paste0(sample2, " signal (log2)"),
title=title)
g
}
knitr::opts_chunk$set(dev=c("png", "pdf"))
knitr::opts_chunk$set(fig.cap="", fig.width=7, fig.height=7)
```
## Figure 2A
``` {r tbp_and_dorsal_chipnexus_vs_chipnexus}
make_plot(chipnexus.grl[["hsap_k562_tbp_chipnexus_01"]],
"TBP ChIP-nexus peaks: replicate comparison",
"hsap_k562_tbp_chipnexus_01",
"hsap_k562_tbp_chipnexus_02")
make_plot(chipnexus.grl[["dmel_embryo_dl_chipnexus_01"]],
"Dorsal ChIP-nexus peaks: replicate comparison",
"dmel_embryo_dl_chipnexus_01",
"dmel_embryo_dl_chipnexus_02")
```
## Figure 2B
``` {r tbp_and_dorsal_chipseq_vs_chipnexus}
make_plot(chipseq.grl[["hsap_k562_tbp_chipseq_01"]],
"TBP ChIP-seq peaks vs ChIP-nexus",
"hsap_k562_tbp_chipseq_01",
"hsap_k562_tbp_chipnexus_01")
make_plot(chipseq.grl[["dmel_embryo_dl_chipseq_01"]],
"Dorsal ChIP-seq peaks vs ChIP-nexus",
"dmel_embryo_dl_chipseq_01",
"dmel_embryo_dl_chipnexus_01")
known.df <- subset(read.csv("internal_data/dl_known_targets.csv", stringsAsFactors=FALSE), name %in% c("rho", "dpp", "vn", "vnd"))
known.gr <- makeGRangesFromDataFrame(known.df, keep.extra=TRUE)
make_plot_with_labels(chipseq.grl[["dmel_embryo_dl_chipseq_01"]],
"Dorsal ChIP-seq peaks vs ChIP-nexus",
"dmel_embryo_dl_chipseq_01",
"dmel_embryo_dl_chipnexus_01",
known.gr)
```
``` {r session_info_child, child="child_docs/session_info_child.Rmd"}
```