Introduction

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

Publications

  1. 'maskBAD'--a package to detect and remove Affymetrix probes with binding affinity differences.
    Cite this
    Dannemann M, Lachmann M, Lorenc A, 2012-01-01 - BMC bioinformatics

Credits

  1. Michael Dannemann
    Developer

  2. Michael Lachmann
    Developer

  3. Anna Lorenc
    Investigator

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Summary
AccessionBT002235
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Submitted ByAnna Lorenc