MOTIVATION: [corrected] The existence of several technologies for measuring gene expression makes the question of cross-technology agreement of measurements an important issue. Cross-platform utilization of data from different technologies has the potential to reduce the need to duplicate experiments but requires corresponding measurements to be comparable. METHODS: A comparison of mRNA measurements of 2895 sequence-matched genes in 56 cell lines from the standard panel of 60 cancer cell lines from the National Cancer Institute (NCI 60) was carried out by calculating correlation between matched measurements and calculating concordance between cluster from two high-throughput DNA microarray technologies, Stanford type cDNA microarrays and Affymetrix oligonucleotide microarrays. RESULTS: In general, corresponding measurements from the two platforms showed poor correlation. Clusters of genes and cell lines were discordant between the two technologies, suggesting that relative intra-technology relationships were not preserved. GC-content, sequence length, average signal intensity, and an estimator of cross-hybridization were found to be associated with the degree of correlation. This suggests gene-specific, or more correctly probe-specific, factors influencing measurements differently in the two platforms, implying a poor prognosis for a broad utilization of gene expression measurements across platforms.
MOTIVATION: [corrected] The existence of several technologies for measuring gene expression makes the question of cross-technology agreement of measurements an important issue. Cross-platform utilization of data from different technologies has the potential to reduce the need to duplicate experiments but requires corresponding measurements to be comparable. METHODS: A comparison of mRNA measurements of 2895 sequence-matched genes in 56 cell lines from the standard panel of 60 cancer cell lines from the National Cancer Institute (NCI 60) was carried out by calculating correlation between matched measurements and calculating concordance between cluster from two high-throughput DNA microarray technologies, Stanford type cDNA microarrays and Affymetrix oligonucleotide microarrays. RESULTS: In general, corresponding measurements from the two platforms showed poor correlation. Clusters of genes and cell lines were discordant between the two technologies, suggesting that relative intra-technology relationships were not preserved. GC-content, sequence length, average signal intensity, and an estimator of cross-hybridization were found to be associated with the degree of correlation. This suggests gene-specific, or more correctly probe-specific, factors influencing measurements differently in the two platforms, implying a poor prognosis for a broad utilization of gene expression measurements across platforms.
Authors: Andrea Barczak; Madeleine Willkom Rodriguez; Kristina Hanspers; Laura L Koth; Yu Chuan Tai; Benjamin M Bolstad; Terence P Speed; David J Erle Journal: Genome Res Date: 2003-06-12 Impact factor: 9.043
Authors: Kerstin Korn; Paola Gardellin; Bohao Liao; Mario Amacker; Asa Bergström; Henrik Björkman; Agnès Camacho; Sabine Dörhöfer; Klaus Dörre; Johanna Enström; Thomas Ericson; Tatiana Favez; Michael Gösch; Adrian Honegger; Sandra Jaccoud; Markus Lapczyna; Erik Litborn; Per Thyberg; Holger Winter; Rudolf Rigler Journal: Nucleic Acids Res Date: 2003-08-15 Impact factor: 16.971
Authors: Paul K Tan; Thomas J Downey; Edward L Spitznagel; Pin Xu; Dadin Fu; Dimiter S Dimitrov; Richard A Lempicki; Bruce M Raaka; Margaret C Cam Journal: Nucleic Acids Res Date: 2003-10-01 Impact factor: 16.971
Authors: Brigham H Mecham; Gregory T Klus; Jeffrey Strovel; Meena Augustus; David Byrne; Peter Bozso; Daniel Z Wetmore; Thomas J Mariani; Isaac S Kohane; Zoltan Szallasi Journal: Nucleic Acids Res Date: 2004-05-25 Impact factor: 16.971