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Quantification of subclonal selection in cancer from bulk sequencing data
[article]
2016
bioRxiv
pre-print
Recent studies have identified prevalent subclonal architectures within many cancer types. However, the temporal evolutionary dynamics that produce these subclonal architectures remain unknown. Here we measure evolutionary dynamics in primary human cancers using computational modelling of clonal selection applied to high throughput sequencing data. Our approach simultaneously determines the subclonal architecture of a tumour sample, and measures the mutation rate, the selective advantage, and
doi:10.1101/096305
fatcat:xxmhrhkkivci7lyd5mgc4xcgii