DOI . ORG {
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Title[redir]:
PyClone: statistical inference of clonal population structure in cancer | Nature Methods
Description:
The hierarchical Bayesian model identifies and quantifies clonal populations in tumors from deep-sequenced somatic mutations. We introduce PyClone, a statistical model for inference of clonal population structures in cancers. PyClone is a Bayesian clustering method for grouping sets of deeply sequenced somatic mutations into putative clonal clusters while estimating their cellular prevalences and accounting for allelic imbalances introduced by segmental copy-number changes and normal-cell contamination. Single-cell sequencing validation demonstrates PyClone
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Keywords {🔍}
pubmed, article, nature, google, scholar, cas, cancer, central, methods, access, british, supplementary, cellular, columbia, clonal, research, content, cookies, data, pyclone, shah, online, genome, canada, post, burnin, trace, privacy, journal, prevalences, open, sps, information, inference, roth, aparicio, sohrab, sequencing, med, vancouver, prevalence, ids, chromosome, coordinate, advertising, analysis, subscribe, statistical, population, andrew,
Topics {✒️}
nature portfolio permissions reprints privacy policy editing canada research chair advertising method development social media author information authors single-cell sequencing health research nature 481 nature 486 nature 461 nature 467 nature stereo-seq resolve origin author correspondence springerlink instant access putative clonal clusters permissions personal data cancer andrew roth computational cancer genomics data analysis identifying karyotype heterogeneity data protection normal-cell contamination privacy article roth clonal population structure clonal population structures reconstructing clonal tree michael smith foundation competing financial interests pancreatic cancer evolution advanced prostate cancer metastatic gastric cancer samuel aparicio & sohrab allelic imbalances introduced communication published explore content subscription content clonal evolution analysis european economic area segmental copy-number institutional subscriptions read nucleic acids res copy number predictions post burnin trace
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description:The hierarchical Bayesian model identifies and quantifies clonal populations in tumors from deep-sequenced somatic mutations. We introduce PyClone, a statistical model for inference of clonal population structures in cancers. PyClone is a Bayesian clustering method for grouping sets of deeply sequenced somatic mutations into putative clonal clusters while estimating their cellular prevalences and accounting for allelic imbalances introduced by segmental copy-number changes and normal-cell contamination. Single-cell sequencing validation demonstrates PyClone's accuracy.
datePublished:2014-03-16T00:00:00Z
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headline:PyClone: statistical inference of clonal population structure in cancer
description:The hierarchical Bayesian model identifies and quantifies clonal populations in tumors from deep-sequenced somatic mutations. We introduce PyClone, a statistical model for inference of clonal population structures in cancers. PyClone is a Bayesian clustering method for grouping sets of deeply sequenced somatic mutations into putative clonal clusters while estimating their cellular prevalences and accounting for allelic imbalances introduced by segmental copy-number changes and normal-cell contamination. Single-cell sequencing validation demonstrates PyClone's accuracy.
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