title: Fast and scalable inference of multi-sample cancer lineages.
abstract: Somatic variants can be used as lineage markers for the phylogenetic reconstruction of cancer evolution. Since somatic phylogenetics is complicated by sample heterogeneity, novel specialized tree-building methods are required for cancer phylogeny reconstruction. We present LICHeE (Lineage Inference for Cancer Heterogeneity and Evolution), a novel method that automates the phylogenetic inference of cancer progression from multiple somatic samples. LICHeE uses variant allele frequencies of somatic single nucleotide variants obtained by deep sequencing to reconstruct multi-sample cell lineage trees and infer the subclonal composition of the samples. LICHeE is open source and available at http://viq854.github.io/lichee .
authors.affiliation: Department of Computer Science, Stanford University, Stanford, CA, USA. viq@stanford.edu.
authors.forename: Victoria
authors.initials: V
authors.lastname: Popic
authors.affiliation: Department of Computer Science, Stanford University, Stanford, CA, USA. rahelehs@cs.stanford.edu.
authors.forename: Raheleh
authors.initials: R
authors.lastname: Salari
authors.affiliation: Department of Computer Science, Stanford University, Stanford, CA, USA. imanh@stanford.edu.
authors.forename: Iman
authors.initials: I
authors.lastname: Hajirasouliha
authors.affiliation: Department of Computer Science, Stanford University, Stanford, CA, USA. dkashef@stanford.edu.
authors.forename: Dorna
authors.initials: D
authors.lastname: Kashef-Haghighi
authors.affiliation: Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA. rbwest@stanford.edu.
authors.forename: Robert B
authors.initials: RB
authors.lastname: West
authors.affiliation: Department of Computer Science, Stanford University, Stanford, CA, USA. serafim@cs.stanford.edu.
authors.forename: Serafim
authors.initials: S
authors.lastname: Batzoglou
mesh_terms: D000465:Algorithms; D002292:Carcinoma, Renal Cell / Q000235:genetics; D019070:Cell Lineage / Q000235:genetics*; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D018450:Disease Progression; D005260:Female; D014644:Genetic Variation; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D007680:Kidney Neoplasms / Q000235:genetics; D009369:Neoplasms / Q000235:genetics*; D010051:Ovarian Neoplasms / Q000235:genetics; D010802:Phylogeny; D012984:Software; D023041:Xenograft Model Antitumor Assays