TY - JOUR T1 - geneXtendeR: optimized functional annotation of ChIP-seq data JF - bioRxiv DO - 10.1101/082347 SP - 082347 AU - Bohdan B. Khomtchouk AU - Derek J. Van Booven AU - Claes Wahlestedt Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/08/06/082347.abstract N2 - Motivation Different ChIP-seq peak callers often produce different output results from the same input. Since different peak callers are known to produce differentially enriched peaks with a large variance in peak length distribution and total peak count, accurately annotating peak lists with their nearest genes can be an arduous process. Functional genomic annotation of histone modification ChIP-seq data can be a particularly challenging task, as chromatin marks that have inherently broad peaks with a diffuse range of signal enrichment (e.g., H3K9me1, H3K27me3) differ significantly from narrow peaks that exhibit a compact and localized enrichment pattern (e.g., H3K4me3, H3K9ac). In addition, varying degrees of tissue-dependent broadness of an epigenetic mark can make it difficult to accurately and reliably link sequencing data to biological function. Thus, it would be useful to develop a software program that can precisely tailor the computational analysis of a ChIP-seq dataset to the specific peak coordinates of the data.Results geneXtendeR is an R/Bioconductor package that optimizes the functional annotation of ChIP-seq peaks using fast iterative peak-coordinate/GTF alignment algorithms focused on cis-regulatory regions and proximal-promoter regions of nearest genes. The goal of geneXtendeR is to robustly link differentially enriched peaks with their respective genes, thereby aiding experimental follow-up and validation in designing primers for a set of prospective gene candidates during qPCR. We have tested geneXtendeR on 547 human transcription factor ChIP-seq ENCODE datasets and 214 human histone modification ChIP-seq ENCODE datasets, providing the analysis results as case studies.Availability The geneXtendeR R/Bioconductor package (including detailed introductory vignettes) is available under the GPL-3 Open Source license and is freely available to download from Bioconductor at: https://bioconductor.org/packages/devel/geneXtendeR/.Contact bohdan{at}stanford.eduSupplementary information Supplementary data are available at Bioinformatics online. ER -