Bioinformatics Vol. 18 no. 3 2002
Pages 405-412
© 2002 Oxford University Press
Analysis of matched mRNA measurements from two different microarray technologies
1 Children’s Hospital Informatics
Program and Division of Endocrinology, Department of Medicine,
Children’s Hospital
2 Decision Systems Group, Brigham and
Women’s Hospital, Harvard Medical School, Boston, MA 02115,
USA
3 Harvard University and MIT, Division of
Health Sciences and Technology, Cambridge, MA 02139, USA
4 Department of Computer and Information
Science, Norwegian University of Science and Technology, N-7491
Trondheim, Norway
Received on April 9, 2001
; revised on September 29, 2001
; accepted on October 25, 2001
Motivation: 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.
Contact: wpkuo{at}mit.edu
* To whom correspondence should be addressed.
1 These authors contributed equally to this work.
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