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'maskBAD' - a package to detect and remove Affymetrix probes with binding affinity differences

Michael Dannemann2, Michael Lachmann2 and Anna Lorenc1*

Author Affiliations

1 Max Planck Institute for Evolutionary Biology, August–Thienemann–Str. 2, 24306, Plön, Germany

2 Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103, Leipzig, Germany

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BMC Bioinformatics 2012, 13:56  doi:10.1186/1471-2105-13-56

Published: 16 April 2012



Hybridization differences caused by target sequence differences can be a confounding factor in analyzing gene expression on microarrays, lead to false positives and reduce power to detect real expression differences. We prepared an R Bioconductor compatible package to detect, characterize and remove such probes in Affymetrix 3’IVT and exon-based arrays on the basis of correlation of signal intensities from probes within probe sets.


Using completely mouse genomes we determined type 1 (false negatives) and type 2 (false positives) errors with high accuracy and we show that our method routinely outperforms previous methods. When detecting 76.2% of known SNP/indels in mouse expression data, we obtain at most 5.5% false positives. At the same level of false positives, best previous method detected 72.6%. We also show that probes with differing binding affinity both hinder differential expression detection and introduce artifacts in cancer-healthy tissue comparison.


Detection and removal of such probes should be a routine step in Affymetrix data preprocessing. We prepared a user friendly R package, compatible with Bioconductor, that allows the filtering and improving of data from Affymetrix microarrays experiments.