{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Mecham BH"],"funding":["NHLBI NIH HHS","NCI NIH HHS","NINDS NIH HHS"],"pagination":["e74"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC419626"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["32(9)"],"pubmed_abstract":["Cancer derived microarray data sets are routinely produced by various platforms that are either commercially available or manufactured by academic groups. The fundamental difference in their probe selection strategies holds the promise that identical observations produced by more than one platform prove to be more robust when validated by biology. However, cross-platform comparison requires matching corresponding probe sets. We are introducing here sequence-based matching of probes instead of gene identifier-based matching. We analyzed breast cancer cell line derived RNA aliquots using Agilent cDNA and Affymetrix oligonucleotide microarray platforms to assess the advantage of this method. We show, that at different levels of the analysis, including gene expression ratios and difference calls, cross-platform consistency is significantly improved by sequence- based matching. We also present evidence that sequence-based probe matching produces more consistent results when comparing similar biological data sets obtained by different microarray platforms. This strategy allowed a more efficient transfer of classification of breast cancer samples between data sets produced by cDNA microarray and Affymetrix gene-chip platforms."],"journal":["Nucleic acids research"],"pubmed_title":["Sequence-matched probes produce increased cross-platform consistency and more reproducible biological results in microarray-based gene expression measurements."],"pmcid":["PMC419626"],"funding_grant_id":["P50 NS040828","HL66805-01","P01 CA092644","R01 HL071885","1PO1CA-092644-01","U01 HL066805","P01 NS040828","HL066582-01","HL071885","U01 HL066582","NS40828-01A1"],"pubmed_authors":["Szallasi Z","Mecham BH","Wetmore DZ","Mariani TJ","Byrne D","Klus GT","Augustus M","Bozso P","Strovel J","Kohane IS"],"additional_accession":[]},"is_claimable":false,"name":"Sequence-matched probes produce increased cross-platform consistency and more reproducible biological results in microarray-based gene expression measurements.","description":"Cancer derived microarray data sets are routinely produced by various platforms that are either commercially available or manufactured by academic groups. The fundamental difference in their probe selection strategies holds the promise that identical observations produced by more than one platform prove to be more robust when validated by biology. However, cross-platform comparison requires matching corresponding probe sets. We are introducing here sequence-based matching of probes instead of gene identifier-based matching. We analyzed breast cancer cell line derived RNA aliquots using Agilent cDNA and Affymetrix oligonucleotide microarray platforms to assess the advantage of this method. We show, that at different levels of the analysis, including gene expression ratios and difference calls, cross-platform consistency is significantly improved by sequence- based matching. We also present evidence that sequence-based probe matching produces more consistent results when comparing similar biological data sets obtained by different microarray platforms. This strategy allowed a more efficient transfer of classification of breast cancer samples between data sets produced by cDNA microarray and Affymetrix gene-chip platforms.","dates":{"release":"2004-01-01T00:00:00Z","publication":"2004 May","modification":"2024-11-06T02:42:55.913Z","creation":"2019-03-27T00:50:29Z"},"accession":"S-EPMC419626","cross_references":{"pubmed":["15161944"],"doi":["10.1093/nar/gnh071"]}}