Background: RNA-Seq exploits the rapid generation of gigabases of sequence data by Massively Parallel Nucleotide Sequencing, allowing for the mapping and digital quantification of whole transcriptomes. Whilst previous comparisons between RNA-Seq and microarrays have been performed at the level of gene expression, in this study we adopt a more fine-grained approach. Using RNA samples from a normal human breast epithelial cell line (MCF-10a) and a breast cancer cell line (MCF-7), we present a comprehensive comparison between RNA-Seq data generated on the Applied Biosystems SOLiD platform and data from Affymetrix Exon 1.
View Article and Find Full Text PDFMicroarray gene expression profiling of formalin-fixed paraffin-embedded (FFPE) tissues is a new and evolving technique. This report compares transcript detection rates on Affymetrix U133 Plus 2.0 and Human Exon 1.
View Article and Find Full Text PDFBackground: The number of gene expression studies in the public domain is rapidly increasing, representing a highly valuable resource. However, dataset-specific bias precludes meta-analysis at the raw transcript level, even when the RNA is from comparable sources and has been processed on the same microarray platform using similar protocols. Here, we demonstrate, using Affymetrix data, that much of this bias can be removed, allowing multiple datasets to be legitimately combined for meaningful meta-analyses.
View Article and Find Full Text PDFExon arrays aim to provide comprehensive gene expression data at the level of individual exons, similar to that provided on a per-gene basis by existing expression arrays. This report describes the performance of Affymetrix GeneChip Human Exon 1.0 ST array by using replicated RNA samples from two human cell lines, MCF7 and MCF10A, hybridized both to Exon 1.
View Article and Find Full Text PDFThe desire to perform microarray experiments with small starting amounts of RNA has led to the development of a variety of protocols for preparing and amplifying mRNA. This has consequences not only for the standardization of experimental design, but also for reproducibility and comparability between experiments. Here we investigate the differences between the Affymetrix standard and small sample protocols and address the data analysis issues that arise when comparing samples and experiments that have been processed in different ways.
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