1. Are data from different gene expression microarray platforms comparable?
- Author
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Anna-Kaarina Järvinen, Olli-P. Kallioniemi, Sampsa Hautaniemi, Outi Monni, Henrik Edgren, Janna Saarela, and Petri Auvinen
- Subjects
Microarray ,Genomics ,Biology ,03 medical and health sciences ,0302 clinical medicine ,Breast cancer ,SDG 3 - Good Health and Well-being ,Complementary DNA ,Cell Line, Tumor ,Genetics ,Microarray databases ,Humans ,030304 developmental biology ,Gene Library ,Oligonucleotide Array Sequence Analysis ,0303 health sciences ,Microarray analysis techniques ,cDNA library ,Gene Expression Profiling ,Quality control ,Gene Expression Regulation, Neoplastic ,030220 oncology & carcinogenesis ,Data Interpretation, Statistical ,Gene chip analysis ,DNA microarray ,Oligonucleotide microarrays ,cDNA microarrays - Abstract
Many commercial and custom-made microarray formats are routinely used for large-scale gene expression surveys. Here, we sought to determine the level of concordance between microarray platforms by analyzing breast cancer cell lines with in situ synthesized oligonucleotide arrays (Affymetrix HG-U95v2), commercial cDNA microarrays (Agilent Human 1 cDNA), and custom-made cDNA microarrays from a sequence-validated 13K cDNA library. Gene expression data from the commercial platforms showed good correlations across the experiments (r = 0.78–0.86), whereas the correlations between the custom-made and either of the two commercial platforms were lower (r = 0.62–0.76). Discrepant findings were due to clone errors on the custom-made microarrays, old annotations, or unknown causes. Even within platform, there can be several ways to analyze data that may influence the correlation between platforms. Our results indicate that combining data from different microarray platforms is not straightforward. Variability of the data represents a challenge for developing future diagnostic applications of microarrays.
- Published
- 2004
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