Journal Article

TileProbe: modeling tiling array probe effects using publicly available data

Jennifer Toolan Judy and Hongkai Ji

in Bioinformatics

Volume 25, issue 18, pages 2369-2375
Published in print September 2009 | ISSN: 1367-4803
Published online July 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp425

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Motivation: Individual probes on an Affymetrix tiling array usually behave differently. Modeling and removing these probe effects are critical for detecting signals from the array data. Current data processing techniques either require control samples or use probe sequences to model probe-specific variability, such as with MAT. Although the MAT approach can be applied without control samples, residual probe effects continue to distort the true biological signals.

Results: We propose TileProbe, a new technique that builds upon the MAT algorithm by incorporating publicly available data sets to remove tiling array probe effects. By using a large number of these readily available arrays, TileProbe robustly models the residual probe effects that MAT model cannot explain. When applied to analyzing ChIP-chip data, TileProbe performs consistently better than MAT across a variety of analytical conditions. This shows that TileProbe resolves the issue of probe-specific effects more completely.

Availability: http://www.biostat.jhsph.edu/∼hji/cisgenome/index_files/tileprobe.htm

Contact: hji@jhsph.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  5621 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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