TY - JOUR
T1 - A rapid method for microarray cross platform comparisons using gene expression signatures
AU - Cheadle, Chris
AU - Becker, Kevin G.
AU - Cho-Chung, Yoon S.
AU - Nesterova, Maria
AU - Watkins, Tonya
AU - Wood, William
AU - Prabhu, Vinayakumar
AU - Barnes, Kathleen C.
PY - 2007/2/1
Y1 - 2007/2/1
N2 - Microarray technology has become highly valuable for identifying complex changes in global gene expression patterns. The inevitable use of a variety of different platforms has compounded the difficulty of effectively comparing data between projects, laboratories, and public access databases. The need for consistent, believable results across platforms is fundamental and methods for comparing results across platforms should be as straightforward as possible. We present the results of a study comparing three major, commercially available, microarray platforms (Affymetrix, Agilent, and Illumina). Concordance estimates between platforms was based on mapping of probes to Human Gene Organization (HUGO) gene names. Appropriate data normalization procedures were applied to each dataset followed by the generation of lists of regulated genes using a common significance threshold for all three platforms. As expected, concordance measured by directly comparing genelists was relatively low (an average 22.8% for all platforms across all possible comparisons). However, when statistical tests (gene set enrichment analysis-GSEA, parametric analysis of gene enrichment-PAGE) which align genelists with continuous measures of differential gene expression were applied to the cross platform datasets using significant genelists to poll entire datasets, the relatedness of the results from all three platforms was specific, obvious, and profound.
AB - Microarray technology has become highly valuable for identifying complex changes in global gene expression patterns. The inevitable use of a variety of different platforms has compounded the difficulty of effectively comparing data between projects, laboratories, and public access databases. The need for consistent, believable results across platforms is fundamental and methods for comparing results across platforms should be as straightforward as possible. We present the results of a study comparing three major, commercially available, microarray platforms (Affymetrix, Agilent, and Illumina). Concordance estimates between platforms was based on mapping of probes to Human Gene Organization (HUGO) gene names. Appropriate data normalization procedures were applied to each dataset followed by the generation of lists of regulated genes using a common significance threshold for all three platforms. As expected, concordance measured by directly comparing genelists was relatively low (an average 22.8% for all platforms across all possible comparisons). However, when statistical tests (gene set enrichment analysis-GSEA, parametric analysis of gene enrichment-PAGE) which align genelists with continuous measures of differential gene expression were applied to the cross platform datasets using significant genelists to poll entire datasets, the relatedness of the results from all three platforms was specific, obvious, and profound.
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U2 - 10.1016/j.mcp.2006.07.004
DO - 10.1016/j.mcp.2006.07.004
M3 - Article
C2 - 16982174
AN - SCOPUS:33845345622
VL - 21
SP - 35
EP - 46
JO - Molecular and Cellular Probes
JF - Molecular and Cellular Probes
SN - 0890-8508
IS - 1
ER -