1. Discovering single nucleotide variants and indels from bulk and single-cell ATAC-seq.
- Author
-
Massarat AR, Sen A, Jaureguy J, Tyndale ST, Fu Y, Erikson G, and McVicker G
- Subjects
- Animals, Cell Line, Cell Line, Tumor, Genome, Human genetics, Humans, Jurkat Cells, Mice, Reproducibility of Results, Chromatin Immunoprecipitation Sequencing methods, Genome genetics, INDEL Mutation, Polymorphism, Single Nucleotide, Regulatory Sequences, Nucleic Acid genetics, Single-Cell Analysis methods
- Abstract
Genetic variants and de novo mutations in regulatory regions of the genome are typically discovered by whole-genome sequencing (WGS), however WGS is expensive and most WGS reads come from non-regulatory regions. The Assay for Transposase-Accessible Chromatin (ATAC-seq) generates reads from regulatory sequences and could potentially be used as a low-cost 'capture' method for regulatory variant discovery, but its use for this purpose has not been systematically evaluated. Here we apply seven variant callers to bulk and single-cell ATAC-seq data and evaluate their ability to identify single nucleotide variants (SNVs) and insertions/deletions (indels). In addition, we develop an ensemble classifier, VarCA, which combines features from individual variant callers to predict variants. The Genome Analysis Toolkit (GATK) is the best-performing individual caller with precision/recall on a bulk ATAC test dataset of 0.92/0.97 for SNVs and 0.87/0.82 for indels within ATAC-seq peak regions with at least 10 reads. On bulk ATAC-seq reads, VarCA achieves superior performance with precision/recall of 0.99/0.95 for SNVs and 0.93/0.80 for indels. On single-cell ATAC-seq reads, VarCA attains precision/recall of 0.98/0.94 for SNVs and 0.82/0.82 for indels. In summary, ATAC-seq reads can be used to accurately discover non-coding regulatory variants in the absence of whole-genome sequencing data and our ensemble method, VarCA, has the best overall performance., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)
- Published
- 2021
- Full Text
- View/download PDF