Purityest: Estimating purity of human tumor samples using next-generation sequencing data

Xiaoping Su; Li Zhang; Jianping Zhang; Funda Meric-bernstam; John N. Weinstein

doi:10.1093/bioinformatics/bts365

Purityest: Estimating purity of human tumor samples using next-generation sequencing data

Xiaoping Su, Li Zhang, Jianping Zhang, Funda Meric-bernstam, John N. Weinstein

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

54 Scopus citations

Abstract

We developed a novel algorithm, PurityEst, to infer the tumor purity level from the allelic differential representation of heterozygous loci with somatic mutations in a human tumor sample with a matched normal tissue using next-generation sequencing data. We applied our tool to a whole cancer genome sequencing datasets and demonstrated the accuracy of PurityEst compared with DNA copy number-based estimation.

Original language	English (US)
Article number	bts365
Pages (from-to)	2265-2266
Number of pages	2
Journal	Bioinformatics
Volume	28
Issue number	17
DOIs	https://doi.org/10.1093/bioinformatics/bts365
State	Published - Sep 2012

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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title = "Purityest: Estimating purity of human tumor samples using next-generation sequencing data",

abstract = "We developed a novel algorithm, PurityEst, to infer the tumor purity level from the allelic differential representation of heterozygous loci with somatic mutations in a human tumor sample with a matched normal tissue using next-generation sequencing data. We applied our tool to a whole cancer genome sequencing datasets and demonstrated the accuracy of PurityEst compared with DNA copy number-based estimation.",

author = "Xiaoping Su and Li Zhang and Jianping Zhang and Funda Meric-bernstam and Weinstein, {John N.}",

note = "Funding Information: Funding: National Cancer Institute (U24CA143883, in part); and National Center for Research Resources (3UL1RR024148 and ULTR000371, in part and a grant in part from the H.A. and Mary K. Chapman Foundation and the Michael & Susan Dell Foundation).",

year = "2012",

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AU - Su, Xiaoping

AU - Zhang, Li

AU - Zhang, Jianping

AU - Meric-bernstam, Funda

AU - Weinstein, John N.

N1 - Funding Information: Funding: National Cancer Institute (U24CA143883, in part); and National Center for Research Resources (3UL1RR024148 and ULTR000371, in part and a grant in part from the H.A. and Mary K. Chapman Foundation and the Michael & Susan Dell Foundation).

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N2 - We developed a novel algorithm, PurityEst, to infer the tumor purity level from the allelic differential representation of heterozygous loci with somatic mutations in a human tumor sample with a matched normal tissue using next-generation sequencing data. We applied our tool to a whole cancer genome sequencing datasets and demonstrated the accuracy of PurityEst compared with DNA copy number-based estimation.

AB - We developed a novel algorithm, PurityEst, to infer the tumor purity level from the allelic differential representation of heterozygous loci with somatic mutations in a human tumor sample with a matched normal tissue using next-generation sequencing data. We applied our tool to a whole cancer genome sequencing datasets and demonstrated the accuracy of PurityEst compared with DNA copy number-based estimation.

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Purityest: Estimating purity of human tumor samples using next-generation sequencing data

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ASJC Scopus subject areas

MD Anderson CCSG core facilities

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