epiAneufinder: identifying copy number variations from single-cell ATAC-seq data

Abstract

Single-cell open chromatin profiling via the single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) assay has become a mainstream measurement of open chromatin in single-cells. Here we present a novel algorithm, epiAneufinder, that exploits the read count information from scATAC-seq data to extract genome-wide copy number variations (CNVs) for individual cells, allowing to explore the CNV heterogeneity present in a sample at the single-cell level. Using different cancer scATAC-seq datasets, we show how epiAneufinder can identify intratumor clonal heterogeneity in populations of single cells based on their CNV profiles. These profiles are concordant with the ones inferred from single-cell whole genome sequencing data for the same samples. epiAneufinder allows the addition of single-cell CNV information to scATAC-seq data, without the need of additional experiments, unlocking a layer of genomic variation which is otherwise unexplored.