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
