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bioRxiv · 10.1101/082347

geneXtendeR: R/Bioconductor package for functional annotation of histone modification ChIP-seq data in a 3D genome world

Khomtchouk, B.·Van Booven, D.·Wahlestedt, C.
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Abstract

MotivationDifferent 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, there exists an unmet need 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 and its surrounding genomic features.\n\nResultsgeneXtendeR optimizes the functional annotation of ChIP-seq peaks by exploring relative differences in annotating ChIP-seq peak sets to variable-length gene bodies. In contrast to prior techniques, geneXtendeR considers peak annotations beyond just the closest gene, allowing users to investigate peak summary statistics for the first-closest gene, second-closest gene, ..., nth-closest gene whilst ranking the output according to biologically relevant events and iteratively comparing the fidelity of peak-to-gene overlap across a user-defined range of upstream and downstream extensions on the original boundaries of each genes coordinates. We tested geneXtendeR on 547 human transcription factor ChIP-seq ENCODE datasets and 198 human histone modification ChIP-seq ENCODE datasets, providing the analysis results as case studies.\n\nAvailabilityThe 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/geneXtendeR/\n\nAuthor summarygeneXtendeR makes functional annotation of ChIP-seq data more robust and precise, regardless of peak variability attributable to parameter tuning or peak caller algorithmic differences. Since different ChIP-seq peak callers produce differentially enriched peaks with large variance in peak length distribution and total peak count, annotating peak lists with their nearest genes can often be a noisy process where an adjacent second or third-closest gene may constitute a more viable biological candidate, e.g., during cases of linked genes that are located close to each other. As such, 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.

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Khomtchouk, B., Van Booven, D., Wahlestedt, C.. 2016-10-21. geneXtendeR: R/Bioconductor package for functional annotation of histone modification ChIP-seq data in a 3D genome world. https://doi.org/10.1101/082347

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