title: PyClone: statistical inference of clonal population structure in cancer.
abstract: 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.
authors.affiliation: 1] Bioinformatics Graduate Program, University of British Columbia, Vancouver, British Columbia, Canada. [2] Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.
authors.forename: Andrew
authors.initials: A
authors.lastname: Roth
authors.affiliation: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.
authors.forename: Jaswinder
authors.initials: J
authors.lastname: Khattra
authors.affiliation: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.
authors.forename: Damian
authors.initials: D
authors.lastname: Yap
authors.affiliation: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.
authors.forename: Adrian
authors.initials: A
authors.lastname: Wan
authors.affiliation: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.
authors.forename: Emma
authors.initials: E
authors.lastname: Laks
authors.affiliation: Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.
authors.forename: Justina
authors.initials: J
authors.lastname: Biele
authors.affiliation: 1] Bioinformatics Graduate Program, University of British Columbia, Vancouver, British Columbia, Canada. [2] Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada.
authors.forename: Gavin
authors.initials: G
authors.lastname: Ha
authors.affiliation: 1] Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada. [2] Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Samuel
authors.initials: S
authors.lastname: Aparicio
authors.affiliation: Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Bouchard-Côté
authors.affiliation: 1] Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada. [2] Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Sohrab P
authors.initials: SP
authors.lastname: Shah
mesh_terms: D000465:Algorithms; D000483:Alleles; D000818:Animals; D001499:Bayes Theorem; D016000:Cluster Analysis; D004252:DNA Mutational Analysis / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D009154:Mutation; D009369:Neoplasms / Q000378:metabolism*; D015203:Reproducibility of Results; D012984:Software