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Cancer Inform. 2015 Sep 20;14:109-12. doi: 10.4137/CIN.S31363. eCollection 2015.

TIN: An R Package for Transcriptome Instability Analysis.

Author information

1
Department of Molecular Oncology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway ; Centre for Cancer Biomedicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
2
Department of Molecular Oncology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway ; Centre for Cancer Biomedicine, Faculty of Medicine, University of Oslo, Oslo, Norway. ; Department of Informatics, Faculty of Natural Sciences and Mathematics, University of Oslo, Norway.

Abstract

Alternative splicing is a key regulatory mechanism for gene expression, vital for the proper functioning of eukaryotic cells. Disruption of normal pre-mRNA splicing has the potential to cause and reinforce human disease. Owing to rapid advances in high-throughput technologies, it is now possible to identify novel mRNA isoforms and detect aberrant splicing patterns on a genome scale, across large data sets. Analogous to the genomic types of instability describing cancer genomes (eg, chromosomal instability and microsatellite instability), transcriptome instability (TIN) has recently been proposed as a splicing-related genome-wide characteristic of certain solid cancers. We present the R package TIN, available from Bioconductor, which implements a set of methods for TIN analysis based on exon-level microarray expression profiles. TIN provides tools for estimating aberrant exon usage across samples and for analyzing correlation patterns between TIN and splicing factor expression levels.

KEYWORDS:

R software; alternative splicing; exon microarray; splicing factor; transcriptome instability

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