HyperChIP: identification of hypervariable signals across ChIP-seq or ATAC-seq samples

Abstract

Identifying genomic regions with hypervariable ChIP-seq or ATAC-seq signals across given samples is essential for large-scale epigenetic studies. In particular, the hypervariable regions across tumors from different patients indicate their heterogeneity and can contribute to revealing potential cancer subtypes and the associated epigenetic markers. We present HyperChIP as the first complete statistical tool for the task. HyperChIP uses scaled variances that account for the mean-variance dependence to rank genomic regions, and it increases the statistical power by diminishing the influence of true hypervariable regions on model fitting. A pan-cancer case study illustrates the practical utility of HyperChIP.

Redox status of the plant cell determines epigenetic modifications under abiotic stress conditions and during developmental processes

“…Current biotechnological resources and escalating developments offer compelling promise for solutions to the unsolved mysteries of epigenetic development in plants. Recent technological developments such as nanopore sequencing, ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) [182] , epitranscriptomics [183] , gene editing [184] , proteomics, metabolomics, imaging of redox status components [185] , etc. are driving discoveries of molecular mechanisms involved in redox-mediated epigenetic changes.…”

EAP: a versatile cloud-based platform for comprehensive and interactive analysis of large-scale ChIP/ATAC-seq data sets

“…To address these gaps, we have developed EAP (Epigenomic Analysis Platform, https://www.biosino.org/epigenetics), a scalable, customizable and interactive ChIP/ATAC-seq data analysis platform based on cloud technology. EAP uses state-of-the-art computational and statistical algorithms to transform ChIP/ATAC-seq data generated from a large panel of samples into biologically meaningful and interpretable results 10–12 . Currently, EAP provides a series of data analytical tools with an interactive web interface to facilitate its use by researchers with limited programming experience, encompassing data preprocessing, supervised differential analysis, differential TF motifs enrichment analysis, differential TF activity analysis, unsupervised hypervariable analysis, clustering analysis, signature genes scoring analysis, etc.…”