False-positive rate (FPR) analysis for human ES cells (H3K27me3 data from ENCODE Broad database) for the two replicates.

<p>We see the percentage of false positive using various methods. Experiments: unit-mean; quantile; MACS peak finder; ChIPDiff; Rank normalization; two-stage unit-mean; ChIPnorm. The thresholds used are same as those in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039573#pone-0039573-t002" target="_blank">Table 2</a>.</p

ChIPnorm: A Statistical Method for Normalizing and Identifying Differential Regions in Histone Modification ChIP-seq Libraries

<div><p>The advent of high-throughput technologies such as ChIP-seq has made possible the study of histone modifications. A problem of particular interest is the identification of regions of the genome where different cell types from the same organism exhibit different patterns of histone enrichment. This problem turns out to be surprisingly difficult, even in simple pairwise comparisons, because of the significant level of noise in ChIP-seq data. In this paper we propose a two-stage statistical method, called ChIPnorm, to normalize ChIP-seq data, and to find differential regions in the genome, given two libraries of histone modifications of different cell types. We show that the ChIPnorm method removes most of the noise and bias in the data and outperforms other normalization methods. We correlate the histone marks with gene expression data and confirm that histone modifications H3K27me3 and H3K4me3 act as respectively a repressor and an activator of genes. Compared to what was previously reported in the literature, we find that a substantially higher fraction of bivalent marks in ES cells for H3K27me3 and H3K4me3 move into a K27-only state. We find that most of the promoter regions in protein-coding genes have differential histone-modification sites. The software for this work can be downloaded from <a href="http://lcbb.epfl.ch/software.html">http://lcbb.epfl.ch/software.html</a>.</p> </div

The schematic diagram of the ChIPnorm method.

<p>In the first stage one we find the enriched-significant bins by removing various kinds of errors in the data. In the second stage we normalize the two ChIP-seq libraries and find differentially enriched bins.</p

Overview of ChIP-seq process.

<p>We see how we can get the ChIP-seq library, input DNA control, and the random distribution (null hypothesis).</p

Two ROC curves are shown for various methods.

<p>(a) first ROC: Class 1 – four-fold NP differentially over-expressed genes compared to ES; Class 0: rest of the genes. (b) second ROC: Class 1 – four-fold ES differentially over-expressed genes compared to NP; Class 0: rest of the genes.</p

Enrichment level of bins with respect to gene density in a 1 Mbp region.

<p>The axis indicates lowest to highest gene density. (a) The axis indicates the total number of H3K27me3 ChIP-seq fragments divided by the number of Mbp regions (counts per megabase) found in each gene density. (b) The plots are re-normalized so that the axis range is same for both ES and NP cell data. We see that the enrichment level of ChIP-seq data increases with respect to gene density for both ES and NP cells.</p

Bivalent regions in genes; (a) in 333 selected genes; (b) in UCSC known genes.

<p>Genes are attributed to classes according to the presence of modifications in ES and NP cells. The “A–B” notation in the labels indicates the presence of modification of type “A” in ES cells and modification of type “B” in NP cells. (*) marked labels have bivalent domains in ES cells.</p

Bivalent gene profile vs. expression data.

<p>Genes are grouped in (A–E) according to increasing ratio of expression level in ES cells and NP cells. Each bar shows the percentage of genes with the corresponding “A–B” modifications (as listed in the box), “A” for modifications in ES cells and “B” for modifications in NP cells. It is seen that there is a strong over-representation of the K4+K27-K4 transition (yellow) in the genes class, which is strongly up-regulated in NP cells.</p

Robustness studies: sensitivity and error analysis for ChIPnorm by fixing the fold-change threshold and varying the bin size from 200 bp to 2000 bp in steps of 200 bp.

<p>Data from Mikkelsen et al. 2007 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039573#pone.0039573-Mikkelsen1" target="_blank">[8]</a>.</p

Plot of over five different threshold values.

<p>(a) NP is differentially over-expressed compared to ES, (b) ES is differentially over-expressed compared to NP.</p