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Genome Biol. 2015 May 6;16:91. doi: 10.1186/s13059-015-0647-8.

Fast and scalable inference of multi-sample cancer lineages.

Author information

1
Department of Computer Science, Stanford University, Stanford, CA, USA. viq@stanford.edu.
2
Department of Computer Science, Stanford University, Stanford, CA, USA. rahelehs@cs.stanford.edu.
3
Department of Computer Science, Stanford University, Stanford, CA, USA. imanh@stanford.edu.
4
Department of Computer Science, Stanford University, Stanford, CA, USA. dkashef@stanford.edu.
5
Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA. rbwest@stanford.edu.
6
Department of Computer Science, Stanford University, Stanford, CA, USA. serafim@cs.stanford.edu.

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 .

PMID:
25944252
PMCID:
PMC4501097
DOI:
10.1186/s13059-015-0647-8
[Indexed for MEDLINE]
Free PMC Article

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