Evaluation of Microarray Preprocessing Algorithms Based on Concordance with RT-PCR in Clinical Samples

• Published in: PloS one Vol. 4; no. 5; p. e5645
• Main Authors: Gyorffy, Balazs, Molnar, Bela, Lage, Hermann, Szallasi, Zoltan, Eklund, Aron C.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 21.05.2009; Public Library of Science (PLoS)
• Subjects: Accuracy; Algorithms; Arrays; Bias; Bioinformatics; Cancer; Cell Line, Tumor; Clinical trials; Colon; Colorectal cancer; Comparative analysis; Correlation analysis; Databases, Nucleic Acid; Datasets; Discordance; DNA microarrays; Gene expression; Genes; Genetic aspects; Genetics and Genomics/Gene Expression; Genomes; Humans; Oligonucleotide Array Sequence Analysis - methods; Oncology; Pathology/Molecular Pathology; Platforms; Polymerase chain reaction; Preprocessing; Reverse Transcriptase Polymerase Chain Reaction; Statistical analysis; Statistical methods; Studies; Tumor cell lines; Denmark; Hungary; United States > US; Massachusetts
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0005645

Several preprocessing algorithms for Affymetrix gene expression microarrays have been developed, and their performance on spike-in data sets has been evaluated previously. However, a comprehensive comparison of preprocessing algorithms on samples taken under research conditions has not been performed. We used TaqMan RT-PCR arrays as a reference to evaluate the accuracy of expression values from Affymetrix microarrays in two experimental data sets: one comprising 84 genes in 36 colon biopsies, and the other comprising 75 genes in 29 cancer cell lines. We evaluated consistency using the Pearson correlation between measurements obtained on the two platforms. Also, we introduce the log-ratio discrepancy as a more relevant measure of discordance between gene expression platforms. Of nine preprocessing algorithms tested, PLIER+16 produced expression values that were most consistent with RT-PCR measurements, although the difference in performance between most of the algorithms was not statistically significant. Our results support the choice of PLIER+16 for the preprocessing of clinical Affymetrix microarray data. However, other algorithms performed similarly and are probably also good choices.