Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor

TL;DR

This paper presents a comprehensive, reproducible workflow in R/Bioconductor for analyzing Affymetrix Exon 1.0 ST array data at probe and probeset levels, facilitating consistent gene expression and splicing analysis.

Contribution

It provides a detailed, easy-to-follow workflow for reproducible probe-level analysis of exon array data using R/Bioconductor packages, enhancing methodological consistency.

Findings

Demonstrates differential splicing analysis in a public dataset

Shows differential gene expression results at probe level

Provides accessible tools for reproducible exon array analysis

Abstract

The presence of different transcripts of a gene across samples can be analysed by whole-transcriptome microarrays. Reproducing results from published microarray data represents a challenge due to the vast amounts of data and the large variety of pre-processing and filtering steps employed before the actual analysis is carried out. To guarantee a firm basis for methodological development where results with new methods are compared with previous results it is crucial to ensure that all analyses are completely reproducible for other researchers. We here give a detailed workflow on how to perform reproducible analysis of the GeneChip Human Exon 1.0 ST Array at probe and probeset level solely in R/Bioconductor, choosing packages based on their simplicity of use. To exemplify the use of the proposed workflow we analyse differential splicing and differential gene expression in a publicly available dataset using various statistical methods. We believe this study will provide other researchers with an easy way of accessing gene expression data at different annotation levels and with the sufficient details needed for developing their own tools for reproducible analysis of the GeneChip Human Exon 1.0 ST Array.