Nature CommunicationsBioinformaticsPeer-reviewed journal article
FinaleMe: Predicting DNA methylation by the fragmentation patterns of plasma cell-free DNA
Yaping LiuiD, Sarah C. ReediD, Christopher Lo, Atish Dipankar ChoudhuryiD, Heather Anne ParsonsiD, Daniel G. StoveriD, Gavin HaiD, Gregory Gydush, Justin RhoadesiD, Denisse RotemiD, Samuel S. FreemaniD, David KatziD, Ravi BandaruiD, Haizi ZhengiD, Hailu FuiD, Viktor A. AdalsteinssoniD, M KellisiD
Abstract
Analysis of DNA methylation in cell-free DNA (cfDNA) reveals clinically relevant biomarkers but requires specialized protocols and sufficient input material that limits its applicability. Millions of cfDNA samples have been profiled by genomic sequencing. To maximize the gene regulation information from the existing dataset, we developed FinaleMe, a non-homogeneous Hidden Markov Model (HMM), to predict DNA methylation of cfDNA and, therefore, tissues-of-origin directly from plasma whole-genome sequencing (WGS). We validated the performance with 80 pairs of deep and shallow-coverage WGS and whole-genome bisulfite sequencing (WGBS) data.
- organism: human
- assay: whole-genome sequencing
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 29
- FWCI
- 5.82
- Field percentile
- top 3%
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