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Published in NAR genomics and bioinformatics - 01 Jun 2022

Daunesse Maëlle, Legendre Rachel, Varet Hugo, Pain Adrien, Chica Claudia

Link to Pubmed [PMID] – 35664802

Link to DOI – 10.1093/nargab/lqac041

Link to HAL - Pasteur – https://hal-pasteur.archives-ouvertes.fr/pasteur-03683990

NAR Genom Bioinform 2022 Jun; 4(2): lqac041

We present ePeak, a Snakemake-based pipeline for the identification and quantification of reproducible peaks from raw ChIP-seq, CUT&RUN and CUT&Tag epigenomic profiling techniques. It also includes a statistical module to perform tailored differential marking and binding analysis with state of the art methods. ePeak streamlines critical steps like the quality assessment of the immunoprecipitation, spike-in calibration and the selection of reproducible peaks between replicates for both narrow and broad peaks. It generates complete reports for data quality control assessment and optimal interpretation of the results. We advocate for a differential analysis that accounts for the biological dynamics of each chromatin factor. Thus, ePeak provides linear and nonlinear methods for normalisation as well as conservative and stringent models for variance estimation and significance testing of the observed marking/binding differences. Using a published ChIP-seq dataset, we show that distinct populations of differentially marked/bound peaks can be identified. We study their dynamics in terms of read coverage and summit position, as well as the expression of the neighbouring genes. We propose that ePeak can be used to measure the richness of the epigenomic landscape underlying a biological process by identifying diverse regulatory regimes.

https://pubmed.ncbi.nlm.nih.gov/35664802