Efficiently quantifying DNA methylation for bulk- and single-cell bisulfite data

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Abstract

Motivation: DNA CpG methylation (CpGm) has proven to be a crucial epigenetic factor in the mammalian gene regulatory system. Assessment of DNA CpG methylation values via whole-genome bisulfite sequencing (WGBS) is, however, computationally extremely demanding. Results: We present FAst MEthylation calling (FAME), the first approach to quantify CpGm values directly from bulk or single-cell WGBS reads without intermediate output files. FAME is very fast but as accurate as standard methods, which first produce BS alignment files before computing CpGm values. We present experiments on bulk and single-cell bisulfite datasets in which we show that data analysis can be significantly sped-up and help addressing the current WGBS analysis bottleneck for large-scale datasets without compromising accuracy. Availability and implementation: An implementation of FAME is open source and licensed under GPL-3.0 at https://github.com/FischerJo/ FAME.

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APA

Fischer, J., & Schulz, M. H. (2023). Efficiently quantifying DNA methylation for bulk- and single-cell bisulfite data. Bioinformatics, 39(6). https://doi.org/10.1093/bioinformatics/btad386

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