Abstract
Assessing chromatin profiles at single-cell resolution is now feasible thanks to recently published experimental methods such as single cell chromatin immunoprecipitation followed by sequencing (scChIP-seq) (Grosselin et al., 2019; Rotem et al., 2015) and single-cell assay for transposase-accessibility chromatin (scATAC-seq) (Buenrostro et al., 2015; Chen et al., 2018; Cusanovich et al., 2015; Lareau et al., 2019). With these methods, we can detect the heterogeneity of epigenomic profiles within complex biological samples. Yet, existing tools used to analyze bulk epigenomic experiments are not fit for the low coverage and sparsity of single-cell epigenomic datasets. Here, we present ChromSCape: a user-friendly Shiny/R application that processes single-cell epigenomic data to help the biological interpretation of epigenomic landscapes within cell populations. The user can identify different sub-populations within heterogeneous samples, find differentially enriched regions between subpopulations and identify associated genes and pathways. ChromSCape accepts multiple samples to allow comparisons of cell populations between and within samples. ChromSCape source code is written in Shiny/R, works as a stand-alone application and is freely downloadable at https://github.com/vallotlab/ChromSCape. Here, using ChromSCape on multiple H3K27me3 scChIP-seq datasets, we deconvolve chromatin landscapes within the tumor microenvironment, identifying distinct H3K27me3 landscapes associated to cell identity and tumor subtype.
Contact pacome.prompsy{at}curie.fr; celine.vallot{at}curie.fr
