Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2023.06.23.544827v1?rss=1
Authors: Rachid Zaim, S., Pebworth, M.-P., McGrath, I., Okada, L., Weiss, M., Reading, J., Czartoski, J. L., Torgerson, T., McElrath, M. J., Bumol, T. F., Skene, P. J., Li, X.-j.
Abstract:
Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) has been increasingly used to study gene regulation. However, major analytical gaps limit its utility in studying gene regulatory programs in complex diseases. We developed MOCHA (Model-based single cell Open CHromatin Analysis) with major advances over existing analysis tools, including: 1) improved identification of sample-specific open chromatin, 2) proper handling of technical drop-out with zero-inflated methods, 3) mitigation of false positives in single cell analysis, 4) identification of alternative transcription-starting-site regulation, and 5) transcription factor-gene network construction from longitudinal scATAC-seq data. These advances provide a robust framework to study gene regulatory programs in human disease. We benchmarked MOCHA with four state-of-the-art tools to demonstrate its advances. We also constructed cross-sectional and longitudinal gene regulatory networks, identifying potential mechanisms of COVID-19 response. MOCHA provides researchers with a robust analytical tool for functional genomic inference from scATAC-seq data.
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