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Nat Methods. 2019 May;16(5):401-404. doi: 10.1038/s41592-019-0388-9. Epub 2019 Apr 15.

Integrated transcriptomic-genomic tool Texomer profiles cancer tissues.

Author information

1
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
2
Department of Genome Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
3
Department of Pathology and Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
4
Department of Urology and Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
5
Department of Medicine and Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.
6
Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
7
Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
8
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. kchen3@mdanderson.org.

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.

PMID:
30988467
DOI:
10.1038/s41592-019-0388-9
[Indexed for MEDLINE]

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