JUMP: replicability analysis of high-throughput experiments with applications to spatial transcriptomic studies.

ABSTRACT:

Motivation

Replicability is the cornerstone of scientific research. The current statistical method for high-dimensional replicability analysis either cannot control the false discovery rate (FDR) or is too conservative.

Results

We propose a statistical method, JUMP, for the high-dimensional replicability analysis of two studies. The input is a high-dimensional paired sequence of p-values from two studies and the test statistic is the maximum of p-values of the pair. JUMP uses four states of the p-value pairs to indicate whether they are null or non-null. Conditional on the hidden states, JUMP computes the cumulative distribution function of the maximum of p-values for each state to conservatively approximate the probability of rejection under the composite null of replicabil

SUBMITTER: Lyu P 

PROVIDER: S-EPMC10279524 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature