Integrated transcriptomic–genomic tool Texomer profiles cancer tissues

Fang Wang; Shaojun Zhang; Tae Beom Kim; Yu yu Lin; Ramiz Iqbal; Zixing Wang; Vakul Mohanty; Kanishka Sircar; Jose A. Karam; Michael C. Wendl; Funda Meric-Bernstam; John N. Weinstein; Li Ding; Gordon B. Mills; Ken Chen

doi:10.1038/s41592-019-0388-9

Integrated transcriptomic–genomic tool Texomer profiles cancer tissues

Fang Wang, Shaojun Zhang, Tae Beom Kim, Yu yu Lin, Ramiz Iqbal, Zixing Wang, Vakul Mohanty, Kanishka Sircar, Jose A. Karam, Michael C. Wendl, Funda Meric-Bernstam, John N. Weinstein, Li Ding, Gordon B. Mills, Ken Chen

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

6 Scopus citations

Abstract

Profiling of both the genome and the transcriptome promises a comprehensive, functional readout of a tissue sample, yet analytical approaches are required to translate the increased data dimensionality, heterogeneity and complexity into patient benefits. We developed a statistical approach called Texomer (https://github.com/KChen-lab/Texomer) that performs allele-specific, tumor-deconvoluted transcriptome–exome integration of autologous bulk whole-exome and transcriptome sequencing data. Texomer results in substantially improved accuracy in sample categorization and functional variant prioritization.

Original language	English (US)
Pages (from-to)	401-404
Number of pages	4
Journal	Nature Methods
Volume	16
Issue number	5
DOIs	https://doi.org/10.1038/s41592-019-0388-9
State	Published - May 1 2019

ASJC Scopus subject areas

Biotechnology
Biochemistry
Molecular Biology
Cell Biology

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10.1038/s41592-019-0388-9

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title = "Integrated transcriptomic–genomic tool Texomer profiles cancer tissues",

abstract = "Profiling of both the genome and the transcriptome promises a comprehensive, functional readout of a tissue sample, yet analytical approaches are required to translate the increased data dimensionality, heterogeneity and complexity into patient benefits. We developed a statistical approach called Texomer (https://github.com/KChen-lab/Texomer) that performs allele-specific, tumor-deconvoluted transcriptome–exome integration of autologous bulk whole-exome and transcriptome sequencing data. Texomer results in substantially improved accuracy in sample categorization and functional variant prioritization.",

author = "Fang Wang and Shaojun Zhang and Kim, {Tae Beom} and Lin, {Yu yu} and Ramiz Iqbal and Zixing Wang and Vakul Mohanty and Kanishka Sircar and Karam, {Jose A.} and Wendl, {Michael C.} and Funda Meric-Bernstam and Weinstein, {John N.} and Li Ding and Mills, {Gordon B.} and Ken Chen",

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doi = "10.1038/s41592-019-0388-9",

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T1 - Integrated transcriptomic–genomic tool Texomer profiles cancer tissues

AU - Wang, Fang

AU - Zhang, Shaojun

AU - Kim, Tae Beom

AU - Lin, Yu yu

AU - Iqbal, Ramiz

AU - Wang, Zixing

AU - Mohanty, Vakul

AU - Sircar, Kanishka

AU - Karam, Jose A.

AU - Wendl, Michael C.

AU - Meric-Bernstam, Funda

AU - Weinstein, John N.

AU - Ding, Li

AU - Mills, Gordon B.

AU - Chen, Ken

PY - 2019/5/1

Y1 - 2019/5/1

N2 - Profiling of both the genome and the transcriptome promises a comprehensive, functional readout of a tissue sample, yet analytical approaches are required to translate the increased data dimensionality, heterogeneity and complexity into patient benefits. We developed a statistical approach called Texomer (https://github.com/KChen-lab/Texomer) that performs allele-specific, tumor-deconvoluted transcriptome–exome integration of autologous bulk whole-exome and transcriptome sequencing data. Texomer results in substantially improved accuracy in sample categorization and functional variant prioritization.

AB - Profiling of both the genome and the transcriptome promises a comprehensive, functional readout of a tissue sample, yet analytical approaches are required to translate the increased data dimensionality, heterogeneity and complexity into patient benefits. We developed a statistical approach called Texomer (https://github.com/KChen-lab/Texomer) that performs allele-specific, tumor-deconvoluted transcriptome–exome integration of autologous bulk whole-exome and transcriptome sequencing data. Texomer results in substantially improved accuracy in sample categorization and functional variant prioritization.

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Integrated transcriptomic–genomic tool Texomer profiles cancer tissues

Abstract

ASJC Scopus subject areas

MD Anderson CCSG core facilities

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