Title
Probe mapping across multiple microarray platforms.
Abstract
Access to gene expression data has become increasingly common in recent years; however, analysis has become more difficult as it is often desirable to integrate data from different platforms. Probe mapping across microarray platforms is the first and most crucial step for data integration. In this article, we systematically review and compare different approaches to map probes across seven platforms from different vendors: U95A, U133A and U133 Plus 2.0 from Affymetrix, Inc.; HT-12 v1, HT-12v2 and HT-12v3 from Illumina, Inc.; and 4112A from Agilent, Inc. We use a unique data set, which contains 56 lung cancer cell line samples-each of which has been measured by two different microarray platforms-to evaluate the consistency of expression measurement across platforms using different approaches. Based on the evaluation from the empirical data set, the BLAST alignment of the probe sequences to a recent revision of the Transcriptome generated better results than using annotations provided by Vendors or from Bioconductor's Annotate package. However, a combination of all three methods (deemed the 'Consensus Annotation') yielded the most consistent expression measurement across platforms. To facilitate data integration across microarray platforms for the research community, we develop a user-friendly web-based tool, an API and an R package to map data across different microarray platforms from Affymetrix, Illumina and Agilent. Information on all three can be found at ext-link-type="uri" xlink:href="http://qbrc.swmed.edu/software/probemapper/" xmlns:xlink="http://www.w3.org/1999/xlink">http://qbrc.swmed.edu/software/probemapper/.
Year
DOI
Venue
2012
10.1093/bib/bbr076
BRIEFINGS IN BIOINFORMATICS
Keywords
Field
DocType
microarray,gene expression,probe,integrated analysis,probe mapping
Data integration,Data mining,Microarray,Annotation,Computer science,Bioconductor,Software,Bioinformatics,Gene chip analysis,Microarray databases,Gene expression profiling
Journal
Volume
Issue
ISSN
13
5
1467-5463
Citations 
PageRank 
References 
1
0.35
8
Authors
7
Name
Order
Citations
PageRank
Jeffrey D. Allen110.35
Siling Wang2142.83
Min Chen3112.60
Luc Girard491.32
John D. Minna5302.67
Yang Xie6142.07
Guanghua Xiao7569.63