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

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 c

SUBMITTER: Kimes PK 

PROVIDER: S-EPMC4132703 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature