title: LATENT RANK CHANGE DETECTION FOR ANALYSIS OF SPLICE-JUNCTION MICROARRAYS WITH NONLINEAR EFFECTS.
abstract: Alternative splicing of gene transcripts greatly expands the functional capacity of the genome, and certain splice isoforms may indicate specific disease states such as cancer. Splice junction microarrays interrogate thousands of splice junctions, but data analysis is difficult and error prone because of the increased complexity compared to differential gene expression analysis. We present Rank Change Detection (RCD) as a method to identify differential splicing events based upon a straightforward probabilistic model comparing the over- or underrepresentation of two or more competing isoforms. RCD has advantages over commonly used methods because it is robust to false positive errors due to nonlinear trends in microarray measurements. Further, RCD does not depend on prior knowledge of splice isoforms, yet it takes advantage of the inherent structure of mutually exclusive junctions, and it is conceptually generalizable to other types of splicing arrays or RNA-Seq. RCD specifically identifies the biologically important cases when a splice junction becomes more or less prevalent compared to other mutually exclusive junctions. The example data is from different cell lines of glioblastoma tumors assayed with Agilent microarrays.
authors: UT Health Science Center San Antonio, UT Health Science Center San Antonio, UT Health Science Center San Antonio, UT Health Science Center San Antonio, Universidad de São Paulo and UT Health Science Center San Antonio.
authors: Jonathan
authors: J
authors: Gelfond
authors: Lee Ann
authors: LA
authors: Zarzabal
authors: Tarea
authors: T
authors: Burton
authors: Suzanne
authors: S
authors: Burns
authors: Mari
authors: M
authors: Sogayar
authors: Luiz O F
authors: LO
authors: Penalva