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Open Access Highly Accessed Open Badges Research article

Analysis of probe level patterns in Affymetrix microarray data

Alexander C Cambon1, Abdelnaby Khalyfa23, Nigel GF Cooper3 and Caryn M Thompson1*

Author Affiliations

1 Department of Bioinformatics and Biostatistics; School of Public Health and Information Sciences, University of Louisville, Louisville, Kentucky, USA

2 Department of Pediatrics, Kosair Children's Hospital Research Institute, University of Louisville, Louisville, Kentucky, USA

3 Department of Anatomical Science & Neurobiology, University of Louisville, Louisville, Kentucky, USA

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BMC Bioinformatics 2007, 8:146  doi:10.1186/1471-2105-8-146

Published: 4 May 2007



Microarrays have been used extensively to analyze the expression profiles for thousands of genes in parallel. Most of the widely used methods for analyzing Affymetrix Genechip microarray data, including RMA, GCRMA and Model Based Expression Index (MBEI), summarize probe signal intensity data to generate a single measure of expression for each transcript on the array. In contrast, other methods are applied directly to probe intensities, negating the need for a summarization step.


In this study, we used the Affymetrix rat genome Genechip to explore variability in probe response patterns within transcripts. We considered a number of possible sources of variability in probe sets including probe location within the transcript, middle base pair of the probe sequence, probe overlap, sequence homology and affinity. Although affinity, middle base pair and probe location effects may be seen at the gross array level, these factors only account for a small proportion of the variation observed at the gene level. A BLAST search and the presence of probe by treatment interactions for selected differentially expressed genes showed high sequence homology for many probes to non-target genes.


We suggest that examination and modeling of probe level intensities can be used to guide researchers in refining their conclusions regarding differentially expressed genes. We discuss implications for probe sequence selection for confirmatory analysis using real time PCR.