TreeQTL: hierarchical error control for eQTL findings

C B Peterson; M Bogomolov; Y Benjamini; C Sabatti

doi:10.1093/bioinformatics/btw198

TreeQTL: hierarchical error control for eQTL findings

Bioinformatics. 2016 Aug 15;32(16):2556-8. doi: 10.1093/bioinformatics/btw198. Epub 2016 Apr 19.

Authors

C B Peterson¹, M Bogomolov², Y Benjamini³, C Sabatti⁴

Affiliations

¹ Department of Health Research and Policy, Stanford University, Stanford, CA 94305, USA.
² Faculty of Industrial Engineering and Management, Technion, Haifa 32000, Israel.
³ Department of Statistics and Operations Research, Tel Aviv University, Tel Aviv 6997801, Israel.
⁴ Departments of Biomedical Data Science and Statistics, Stanford University, Stanford, CA 94305, USA.

Abstract

: Commonly used multiplicity adjustments fail to control the error rate for reported findings in many expression quantitative trait loci (eQTL) studies. TreeQTL implements a hierarchical multiple testing procedure which allows control of appropriate error rates defined relative to a grouping of the eQTL hypotheses.

Availability and implementation: The R package TreeQTL is available for download at http://bioinformatics.org/treeqtl

Contact: [email protected]

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

Humans
Quantitative Trait Loci*
Software*