Sample size calculation for multiple testing in microarray data analysis

Sample size for FDR-control in microarray data analysis

We consider identifying differentially expressing genes between two patient groups using microarray experiment. We propose a sample size calculation method for a specified number of true rejections while controlling the false discovery rate at a desired level. Input parameters for the sample size calculation include the allocation proportion in each group, the number of genes in each array, the...

Optimal Sample Size for Multiple Testing :

Resampling-based Multiple Testing for Microarray Data Analysis

The burgeoning field of genomics has revived interest in multiple testing procedures by raising new methodological and computational challenges. For example, microarray experiments generate large multiplicity problems in which thousands of hypotheses are tested simultaneously. Westfall and Young (1993) propose resampling-based p-value adjustment procedures which are highly relevant to microarra...

Quick Calculation for Sample Size while Controlling False Discovery Rate with Application to Microarray Analysis

1 Summary. Sample size estimation is important in microarray or proteomic experiments since biologists can typically afford only a few repetitions. Classical procedures to calculate sample size are based on controlling type I error, e.g., family-wise error rate (FWER). In the context of microarray and other large-scale genomic data, it is more powerful and more reasonable to control false disco...

Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient.

The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to carry out one-sided tests (null hypothesis may inv...