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Nucleic Acids Res. 2014 Aug;42(14):e113. doi: 10.1093/nar/gku521. Epub 2014 Jul 16.

SigFuge: single gene clustering of RNA-seq reveals differential isoform usage among cancer samples.

Author information

1
Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
2
Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA The Genome Institute, Washington University School of Medicine, St. Louis, MO 63108, USA Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63108, USA.
3
Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
4
Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
5
Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
6
Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
7
The Genome Institute, Washington University School of Medicine, St. Louis, MO 63108, USA Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63108, USA.
8
Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
9
Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
10
Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Multidisciplinary Thoracic Oncology Program, Division of Medical Oncology, Department of Internal Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA hayes@med.unc.edu.

Abstract

High-throughput sequencing technologies, including RNA-seq, have made it possible to move beyond gene expression analysis to study transcriptional events including alternative splicing and gene fusions. Furthermore, recent studies in cancer have suggested the importance of identifying transcriptionally altered loci as biomarkers for improved prognosis and therapy. While many statistical methods have been proposed for identifying novel transcriptional events with RNA-seq, nearly all rely on contrasting known classes of samples, such as tumor and normal. Few tools exist for the unsupervised discovery of such events without class labels. In this paper, we present SigFuge for identifying genomic loci exhibiting differential transcription patterns across many RNA-seq samples. SigFuge combines clustering with hypothesis testing to identify genes exhibiting alternative splicing, or differences in isoform expression. We apply SigFuge to RNA-seq cohorts of 177 lung and 279 head and neck squamous cell carcinoma samples from the Cancer Genome Atlas, and identify several cases of differential isoform usage including CDKN2A, a tumor suppressor gene known to be inactivated in a majority of lung squamous cell tumors. By not restricting attention to known sample stratifications, SigFuge offers a novel approach to unsupervised screening of genetic loci across RNA-seq cohorts. SigFuge is available as an R package through Bioconductor.

PMID:
25030904
PMCID:
PMC4132703
DOI:
10.1093/nar/gku521
[Indexed for MEDLINE]
Free PMC Article

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