plotIDR: plot irreproducible discovery rate

In imbforge/encodeChIPqc: A set of useful ChIPseq QC metrics from the ENCODE project

Description

Make plots from the output of the function calculateIDR

Usage

plotIDR(chipTuple, idrCutoff = 0.01)

Arguments

chipTuple	one item of the return value of \calccalculateIDR
idrCutoff	peaks with an IDR greater than this cut-off are colored red in the scatter plot

Details

The output of calculateIDR() is a list of tuples of ChIP samples. plotIDR() draws plots which compare the two members of a tuple. For every tuple six plots are generated: - number of peaks in common as a function of the number of _all_ significant peaks - slope of the previous plot - number of peaks in common as a function of the number of _matched_ significant peaks - slope of the previous plot - IDR as a function of the number of significant peaks - scatter plot of ranked peaks of the ChIP samples Refer to Qunhua Li et al (2011) for an explanation on how to interpret the plots.

Ref: Qunhua Li, James B. Brown, Haiyan Huang, and Peter J. Bickel: Measuring reproducibility of high-throughput experiments. Ann Appl Stat. 2011 October 13

Examples

chipTuples <- calculateIDR(c("IP1.bam", "IP2.bam"), c("input1.bam", "input2.bam"),
                            "Hsapiens", "UCSC", "hg19")
for (chipTuple in chipTuples) {
    pdf(paste(basename(chipTuple$rep1), "_VS_", basename(chipTuple$rep2), ".pdf", sep=""), paper="a4r", width=11, height=8.5)
    plotIDR(chipTuple)
    dev.off()
}

imbforge/encodeChIPqc documentation built on May 18, 2019, 4:45 a.m.