Consistent Differential Expression Pattern (CDEP) on microarray to identify genes related to metastatic behavior
1 Bioinformatics Graduate Program, Department of Biochemistry and Molecular Biology, Medical University of South Carolina, 135 Cannon St. Charleston, SC 29425, USA
2 Department of Statistics, Florida State University, 117 N. Woodward Ave. Tallahassee, FL 32306, USA
3 Division of Bioinformatics, Department of Biochemistry and Molecular Biology, Medical University of South Carolina, 135 Cannon St. Charleston, SC 29425, USA
BMC Bioinformatics 2011, 12:438 doi:10.1186/1471-2105-12-438Published: 11 November 2011
Additional file 1:
Supplementary materials for the analysis. Detailed descriptions about: 1) Datasets Used (Suppl. Table 1); 2) The comparisons between p-values computed by the parametric t-test versus the non-parametric RankProd (Suppl. Figure 1); 3) The Bayesian mixture for the p-value distribution (Suppl. Figure 2, Table 2 and Table 3); 4) Comparisons of different approaches for handling genes appearing in different numbers of datasets based on simulation (Suppl. Figure 3, Figure 4, Figure 5 and 6); and 5) Comparisons of the three approaches using the 6 cancer datasets as case study (Suppl. Figure 7).
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Additional file 2:
Results from the simulation data. The statistical power and Type I error rate are compared for the three meta-analysis approaches on simulation data.
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Additional file 3:
Metastases-related genes identified by CDEP. Statistically significant genes identified by CDEP as related to metastatic behavior by using FDR = 0.05.
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Additional file 4:
Comparison of Significant Genes Identified by CDEP, Meta-Profile and Meta-RankProd. List of genes that are differentially expressed consistently in metastatic cancer cells as identified by CDEP, Meta-Profile and Meta-RankProd from six data sets used.
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