The Annals of Applied Statistics

Latent rank change detection for analysis of splice-junction microarrays with nonlinear effects

Jonathan Gelfond, Lee Ann Zarzabal, Tarea Burton, Suzanne Burns, Mari Sogayar, and Luiz O. F. Penalva

Full-text: Open access

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.

Article information

Source
Ann. Appl. Stat., Volume 5, Number 1 (2011), 364-380.

Dates
First available in Project Euclid: 21 March 2011

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1300715194

Digital Object Identifier
doi:10.1214/10-AOAS389

Mathematical Reviews number (MathSciNet)
MR2810401

Zentralblatt MATH identifier
1220.62134

Keywords
Alternative splicing gene expression analysis microarray

Citation

Gelfond, Jonathan; Zarzabal, Lee Ann; Burton, Tarea; Burns, Suzanne; Sogayar, Mari; Penalva, Luiz O. F. Latent rank change detection for analysis of splice-junction microarrays with nonlinear effects. Ann. Appl. Stat. 5 (2011), no. 1, 364--380. doi:10.1214/10-AOAS389. https://projecteuclid.org/euclid.aoas/1300715194


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Supplemental materials

  • Supplemental Figures and Tables. Supplemental Table 1. Experimental layout that describes the number of samples, arrays, and dye orientation. Supplemental Table 2. Enrichment ratio describing the proportion of known differential splicing events detected by ANOSVA. Supplemental Table 3. Enrichment ratio describing the proportion of known differential splicing events detected by RCD. Supplemental Figure 1. Graphic describing the common forms of alternative splicing. Supplemental Figure 2. Power comparison of ANOSVA and RCD for different effect sizes, sample sizes, and degree of nonlinearity.