Metasubtract: an R-package to analytically produce leave-one-out meta-analysis GWAS summary statistics.

Bioinformatics
Ilja M Nolte

Abstract

statistics from a meta-analysis of genome-wide association studies (meta-GWAS) can be used for many follow-up analyses. One valuable application is the creation of polygenic scores. However, if polygenic scores are calculated in a validation cohort that was part of the meta-GWAS consortium, this cohort is not independent and analyses will therefore yield inflated results. The R package 'MetaSubtract' was developed to subtract the results of the validation cohort from meta-GWAS summary statistics analytically. The statistical formulas for a meta-analysis were inverted to compute corrected summary statistics of a meta-GWAS leaving one (or more) cohort(s) out. These formulas have been implemented in MetaSubtract for different meta-analyses methods (fixed effects inverse variance or square root sample size weighted z-score) accounting for no, single or double genomic control correction. Results obtained by MetaSubtract correlate very well to those calculated using the traditional way, i.e. by performing a meta-analysis leaving out the validation cohort. In conclusion, MetaSubtract allows researchers to compute meta-GWAS summary statistics that are independent of the GWAS results of the validation cohort without requiring access to ...Continue Reading

References

Jul 10, 2010·Bioinformatics·Cristen J WillerGonçalo R Abecasis
Jun 19, 2013·Nature Reviews. Genetics·Naomi R WrayPeter M Visscher
Jun 15, 2017·Nature Communications·Ilja M NolteEco J C de Geus

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Software Mentioned

R package MetaSubtract
R Development Core Team
METAL
R
MetaSubtract
TRAILS
R package ‘ MetaSubtract ’

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