SURVIV for survival analysis of mRNA isoform variation

Shihao Shen; Yuanyuan Wang; Chengyang Wang; Ying Nian Wu; Yi Xing

doi:10.1038/ncomms11548

Nature Communications (Jun 2016)

SURVIV for survival analysis of mRNA isoform variation

Shihao Shen,
Yuanyuan Wang,
Chengyang Wang,
Ying Nian Wu,
Yi Xing

Affiliations

Shihao Shen: Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles
Yuanyuan Wang: Department of Molecular and Medical Pharmacology, University of California, Los Angeles
Chengyang Wang: Bioinformatics Interdepartmental Graduate Program, University of California, Los Angeles
Ying Nian Wu: Department of Statistics, University of California, Los Angeles
Yi Xing: Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles

DOI: https://doi.org/10.1038/ncomms11548
Journal volume & issue: Vol. 7, no. 1
pp. 1 – 11

Abstract

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Clinical RNA-seq datasets can predict clinical outcomes. Here, Shen et al. report a statistical method for survival analysis of mRNA isoform variation using clinical RNA-seq datasets, and the identified isoform based survival predictors outperform gene expression based survival predictors using TCGA data on six cancer types.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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