Fast and scalable inference of multi-sample cancer lineages.

Victoria Popic; Raheleh Salari; Iman Hajirasouliha; Dorna Kashef-Haghighi; Robert B West; Serafim Batzoglou

doi:10.1186/s13059-015-0647-8

Fast and scalable inference of multi-sample cancer lineages.

Victoria Popic, Raheleh Salari, Iman Hajirasouliha, Dorna Kashef-Haghighi, Robert B West, Serafim Batzoglou

Research output: Contribution to journal › Article › peer-review

160 Scopus citations

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 .

Original language	English (US)
Journal	Genome Biology
Volume	16
Issue number	1
DOIs	https://doi.org/10.1186/s13059-015-0647-8
State	Published - May 6 2015
Externally published	Yes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Authors would like to thank Arend Sidow for valuable discussions and Aaron C. Abajian for contributing to the simulation studies. VP was supported by the Stanford-KAUST grant. RS and IH were also supported by Natural Sciences and Engineering Research Council of Canada (NSERC) Postdoctoral Fellowships. DK was supported by an STMicroelectronics Stanford Graduate Fellowship. This work was funded by a grant from KAUST to SB.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1186/s13059-015-0647-8

https://repository.kaust.edu.sa/bitstream/10754/596784/1/PMC4501097.pdf

Cite this

@article{b73e38dcfa6e496eb449cb71ca65c452,

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 .",

author = "Victoria Popic and Raheleh Salari and Iman Hajirasouliha and Dorna Kashef-Haghighi and West, {Robert B} and Serafim Batzoglou",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: Authors would like to thank Arend Sidow for valuable discussions and Aaron C. Abajian for contributing to the simulation studies. VP was supported by the Stanford-KAUST grant. RS and IH were also supported by Natural Sciences and Engineering Research Council of Canada (NSERC) Postdoctoral Fellowships. DK was supported by an STMicroelectronics Stanford Graduate Fellowship. This work was funded by a grant from KAUST to SB. This publication acknowledges KAUST support, but has no KAUST affiliated authors.",

year = "2015",

month = may,

day = "6",

doi = "10.1186/s13059-015-0647-8",

language = "English (US)",

volume = "16",

journal = "Genome Biology",

issn = "1465-6906",

publisher = "Springer Verlag",

number = "1",

}

TY - JOUR

T1 - Fast and scalable inference of multi-sample cancer lineages.

AU - Popic, Victoria

AU - Salari, Raheleh

AU - Hajirasouliha, Iman

AU - Kashef-Haghighi, Dorna

AU - West, Robert B

AU - Batzoglou, Serafim

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: Authors would like to thank Arend Sidow for valuable discussions and Aaron C. Abajian for contributing to the simulation studies. VP was supported by the Stanford-KAUST grant. RS and IH were also supported by Natural Sciences and Engineering Research Council of Canada (NSERC) Postdoctoral Fellowships. DK was supported by an STMicroelectronics Stanford Graduate Fellowship. This work was funded by a grant from KAUST to SB. This publication acknowledges KAUST support, but has no KAUST affiliated authors.

PY - 2015/5/6

Y1 - 2015/5/6

N2 - 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 .

AB - 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 .

UR - http://hdl.handle.net/10754/596784

UR - https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0647-8

UR - http://www.scopus.com/inward/record.url?scp=84937046175&partnerID=8YFLogxK

U2 - 10.1186/s13059-015-0647-8

DO - 10.1186/s13059-015-0647-8

M3 - Article

C2 - 25944252

SN - 1465-6906

VL - 16

JO - Genome Biology

JF - Genome Biology

IS - 1

ER -

Fast and scalable inference of multi-sample cancer lineages.

Abstract

Bibliographical note

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this