File S1 - Evaluation of Bias-Variance Trade-Off for Commonly Used Post-Summarizing Normalization Procedures in Large-Scale Gene Expression Studies

Supporting tables and figures. Table S1. The impact of different effect sizes on gene selection strategies when the sample size is fixed and relatively small. Mean (STD) of true positives computed from SIMU1 with 20 repetitions are reported. Sample size: . Total number of genes: 1000. Number of differentially expressed genes: 100. Number of permutations for Nstat: 10000. The significance threshold: 0.05. Table S2. The impact of different effect sizes on gene selection strategies when the sample size is fixed and relatively small. Mean (STD) of false positives computed from SIMU1 with 20 repetitions are reported. Sample size: . Total number of genes: 1000. Number of differentially expressed genes: 100. Number of permutations for Nstat: 10000. The significance threshold: 0.05. Table S3. The impact of different sample sizes on gene selection strategies when the effect size is fixed and relatively small. Mean (STD) of true positives computed from SIMU2 with 20 repetitions are reported. Effect size: . Total number of genes: 1000. Number of differentially expressed genes: 100. Number of permutations for Nstat: 10000. The significance threshold: 0.05. Table S4. The impact of different sample sizes on gene selection strategies when the effect size is fixed and relatively small. Mean (STD) of false positives computed from SIMU2 with 20 repetitions are reported. Effect size: . Total number of genes: 1000. Number of differentially expressed genes: 100. Number of permutations for Nstat: 10000. The significance threshold: 0.05. Table S5. The impact of different sample sizes on gene selection strategies when the effect size is fixed and relatively large. Mean (STD) of true positives computed from SIMU2 with 20 repetitions are reported. Effect size: . Total number of genes: 1000. Number of differentially expressed genes: 100. Number of permutations for Nstat: 10000. The significance threshold: 0.05. Table S6. The impact of different sample sizes on gene selection strategies when the effect size is fixed and relatively large. Mean (STD) of false positives computed from SIMU2 with 20 repetitions are reported. Effect size: . Total number of genes: 1000. Number of differentially expressed genes: 100. Number of permutations for Nstat: 10000. The significance threshold: 0.05. Table S7. The impact of different sample sizes on gene selection strategies with simulation based on biological data. Mean (STD) of true positives computed from SIMU-BIO with 20 repetitions are reported. Total number of genes: 9005. Number of permutations for Nstat: 100000. The significance threshold: 0.05. Table S8. The impact of different sample sizes on gene selection strategies with simulation based on biological data. Mean (STD) of false positives computed from SIMU-BIO with 20 repetitions are reported. Total number of genes: 9005. Number of permutations for Nstat: 100000. The significance threshold: 0.05. Table S9. The numbers of differentially expressed genes detected by different selection strategies. Total number of genes: 9005. Number of permutations for Nstat: 100000. The significance threshold: 0.05. Figure S1. Histogram of pairwise Pearson correlation coefficients between genes computed from HYPERDIP without normalization. Number of genes: 9005. Number of arrays: 88.
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