Biological Validation of Differentially Expressed Genes in Chronic Lymphocytic Leukemia Identified by Applying Multiple Statistical Methods to Oligonucleotide.

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Biological Validation of Differentially Expressed Genes in Chronic Lymphocytic Leukemia Identified by Applying Multiple Statistical Methods to Oligonucleotide Microarrays Lynne V. Abruzzo, Jing Wang, Mini Kapoor, L. Jeffrey Medeiros, Michael J. Keating, W. Edward Highsmith, Lynn L. Barron, Candy C. Cromwell, Kevin R. Coombes The Journal of Molecular Diagnostics Volume 7, Issue 3, Pages 337-345 (August 2005) DOI: 10.1016/S1525-1578(10)60562-4 Copyright © 2005 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions

Figure 1 Histogram of the number of times a probe set was called present in 19 microarray experiments. About one-fourth of the genes were never present, and about one-fourth were present in all samples. The Journal of Molecular Diagnostics 2005 7, 337-345DOI: (10.1016/S1525-1578(10)60562-4) Copyright © 2005 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions

Figure 2 Analysis of the P values arising from 16,733 t-tests as a β-uniform mixture. Top left: Histogram of the observed P values, with overlaid curves representing the division into uniform and β contributions. Top right: Relationship between cutoff for P values and the false discovery rate. Bottom left: Relation between cutoff for P values and the posterior probability of differential expression. Bottom right: Receiver operating characteristics curve associated with selecting different P value cutoffs. The Journal of Molecular Diagnostics 2005 7, 337-345DOI: (10.1016/S1525-1578(10)60562-4) Copyright © 2005 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions

Figure 3 Analysis of the Wilcoxon rank-sum statistics of 16,733 probe sets using an empirical Bayes method. Top: Histogram of the empirically observed distribution of rank-sum statistics, with an overlaid curve representing the theoretical distribution. Bottom: Posterior probability that an observed rank sum represents a differentially expressed gene. The Journal of Molecular Diagnostics 2005 7, 337-345DOI: (10.1016/S1525-1578(10)60562-4) Copyright © 2005 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions

Figure 4 Venn diagram showing the level of agreement between three different statistical methods for selecting differentially expressed genes from the same data set. The Journal of Molecular Diagnostics 2005 7, 337-345DOI: (10.1016/S1525-1578(10)60562-4) Copyright © 2005 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions

Figure 5 Results of two-way clustering of 28 samples using the genes found to be differentially expressed using three different statistical methods. The samples include 8 mutated samples (blue), 11 unmutated samples (orange), and 9 samples whose status was unknown (gray). Each row contains standardized log expression values for one gene. The Journal of Molecular Diagnostics 2005 7, 337-345DOI: (10.1016/S1525-1578(10)60562-4) Copyright © 2005 American Society for Investigative Pathology and Association for Molecular Pathology Terms and Conditions