Related Experiment Video
Updated: Jul 5, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
Published on: July 29, 2022
The multiplicity problem in linkage analysis of gene expression data - the power of differentiating cis- and
Baisong Huang1, Jagadish Rangrej, Andrew D Paterson
1Research Institute, Hospital for Sick Children, 555 University Avenue, Toronto, Ontario, M5G 1X8, Canada. baisong@stat.toronto.edu
Abstract:
In this report, we focused on the multiplicity issue in Problem 1 of Genetic Analysis Workshop 15. We investigated and compared the performance of the stratified false-discovery rate control method with the traditional aggregated approach, in an application to genome-wide linkage analyses of single-nucleotide polymorphism-to-gene expression data. We showed the importance of utilizing the available map information and demonstrated the power gained by conducting false-discovery rate control separately for cis and trans regulators under three different frameworks: fixed rejection region, fixed false-discovery rate, and fixed number of rejections.
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