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A mixture model for signature discovery from sparse mutation data
2021
Genome Medicine
AbstractMutational signatures are key to understanding the processes that shape cancer genomes, yet their analysis requires relatively rich whole-genome or whole-exome mutation data. Recently, orders-of-magnitude sparser gene-panel-sequencing data have become increasingly available in the clinic. To deal with such sparse data, we suggest a novel mixture model, . In application to simulated and real gene-panel sequences, is shown to outperform current approaches and yield mutational signatures
doi:10.1186/s13073-021-00988-7
pmid:34724984
pmcid:PMC8559697
fatcat:b2xtgngi6ffdbpmdq4leyelp5e