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SPAN and JBR: analysis and visualization toolkit for peak calling

The widespread application of ChIP-seq led to a growing need for analysis or comparison of multiple epigenetics profiles, for instance, in human studies where multiple replicates are a common element of design. Peak calling is one of the fundamental steps of ChIP-seq analysis followed by motif analysis, gene set enrichment analysis etc. The most widely used tools for peak calling like MACS2 [1] or SICER [2] perform analysis independently for each sample, small differences in signal quality lead to a very different number of peaks for individual samples, making group-level analysis and comparison between samples difficult. On the other side, when samples are pooled together, or processed with a single joint statistical data model, individual-level statistical differences are ignored. MACS2 produced from 5,000 to 18,000 peaks for promoter-associated mark H3K4me3 and up to 3x fold change on other marks for the same cell types taken from different donors. In contrast, SPAN results were more consistent for all histone marks (e.g. 16,000 - 19,000 H3K4me3 peaks) across samples with substantially different signal-to-noise ratios. Also, this approach was successfully applied for the bulk peak calling step in the pipeline for integrative analysis of multiple single-cell ATAC-seq datasets [4]. The semi-supervised peak calling approach is implemented as a part of JBR genome browser, a stand-alone application that allows for accessible and streamlined annotation, analysis, and data visualization and is fully integrated with SPAN. Markup annotation can be created directly within the JBR genome browser and used to calibrate sample-specific peak calling parameters of SPAN by leveraging annotation information. Moreover, JBR supports standard genome browser capabilities like IGV [5], and was designed for efficient data processing, resulting in fast viewing and analysis of multiple replicates, up to thousands of tracks. SPAN can be applied to a broad range of ChIP-seq datasets of different quality and chromatin accessibility ATAC-seq, which was demonstrated on both real and simulated datasets. Simulation experiment [6] confirmed that SPAN produces good results even without semi-supervised annotation steps and can be used as a unified general-purpose peak calling method. Accelerated execution and integrated peak calling make SPAN and JBR a next-generation visualization and analysis toolkit for epigenetic data.