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SplicerAV: a tool for mining microarray expression data for changes in RNA processing |
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| Authors: | Timothy J Robinson Michaela A Dinan Mark Dewhirst Mariano A Garcia-Blanco James L Pearson |
| Affiliation: | (1) Molecular Cancer Biology Program, Duke University Medical Center, Durham, USA;(2) Department of Health Policy and Management, University of North Carolina at Chapel Hill, Chapel Hill, USA;(3) Department of Radiation Oncology, Duke University Medical Center, Durham, USA;(4) Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, USA;(5) Department of Medicine, Duke University Medical Center, Durham, USA;(6) Center for RNA Biology, Duke University Medical Center, Durham, USA |
| Abstract: | BackgroundOver the past two decades more than fifty thousand unique clinical and biological samples have been assayed using the Affymetrix HG-U133 and HG-U95 GeneChip microarray platforms. This substantial repository has been used extensively to characterize changes in gene expression between biological samples, but has not been previously mined en masse for changes in mRNA processing. We explored the possibility of using HG-U133 microarray data to identify changes in alternative mRNA processing in several available archival datasets. |
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