Detecting Weak Signals by Combining Small P-Values in Genetic Association Studies

Combining Statistical Tests by Multiplying P-values

A general discussion on combining statistical hypothesis tests is followed by an application involving point source detection in skymaps. The traditional literature on combining statistical tests has concentrated on a regime in which p-values as large as 0.05 are still of interest, and in which it is dangerous to treat tests as truly independent. But for point source detection, very small p-val...

Very small P values.

Truncated product method for combining P-values.

We present a new procedure for combining P-values from a set of L hypothesis tests. Our procedure is to take the product of only those P-values less than some specified cut-off value and to evaluate the probability of such a product, or a smaller value, under the overall hypothesis that all L hypotheses are true. We give an explicit formulation for this P-value, and find by simulation that it c...

Estimating p-values in small microarray experiments

MOTIVATION Microarray data typically have small numbers of observations per gene, which can result in low power for statistical tests. Test statistics that borrow information from data across all of the genes can improve power, but these statistics have non-standard distributions, and their significance must be assessed using permutation analysis. When sample sizes are small, the number of dist...

Detecting Epistatic Interactions in Metagenome-Wide Association Studies by metaBOOST

MATERIAL AND METHODS We recall the definition of epistasis and extend it for metagenomic biomarkers and then we describe the overview of our method metaBOOST and provide detailed information about each step of metaBOOST. RESULTS We describe the data sources for both simulation studies and real metagenomic datasets. Then, we describe the procedure of simulation studies and provide results for ...