MOCHA’s advanced statistical modeling of scATAC-seq data enables functional genomic inference in large human cohorts

Samir Rachid Zaim, Mark-Phillip Pebworth, Imran McGrath, Lauren Okada, Morgan Weiss, Julian Reading, Julie L. Czartoski, Troy R. Torgerson, M. Juliana McElrath, Thomas F. Bumol, Peter J. Skene and Xiao-jun Li ()
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Samir Rachid Zaim: Allen Institute for Immunology
Mark-Phillip Pebworth: Allen Institute for Immunology
Imran McGrath: Allen Institute for Immunology
Lauren Okada: Allen Institute for Immunology
Morgan Weiss: Allen Institute for Immunology
Julian Reading: Allen Institute for Immunology
Julie L. Czartoski: Fred Hutchinson Cancer Research Center
Troy R. Torgerson: Allen Institute for Immunology
M. Juliana McElrath: Fred Hutchinson Cancer Research Center
Thomas F. Bumol: Allen Institute for Immunology
Peter J. Skene: Allen Institute for Immunology
Xiao-jun Li: Allen Institute for Immunology

Nature Communications, 2024, vol. 15, issue 1, 1-24

Abstract: Abstract Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is being increasingly used to study gene regulation. However, major analytical gaps limit its utility in studying gene regulatory programs in complex diseases. In response, MOCHA (Model-based single cell Open CHromatin Analysis) presents major advances over existing analysis tools, including: 1) improving identification of sample-specific open chromatin, 2) statistical modeling 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) modules for inferring temporal gene regulatory networks from longitudinal data. These advances, in addition to open chromatin analyses, provide a robust framework after quality control and cell labeling to study gene regulatory programs in human disease. We benchmark MOCHA with four state-of-the-art tools to demonstrate its advances. We also construct 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.

Date: 2024
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DOI: 10.1038/s41467-024-50612-6

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