Dec 24, 2015

GWIS: Genome Wide Inferred Statistics for non-linear functions of multiple phenotypes

BioRxiv : the Preprint Server for Biology
Harold A NieuwboerMichel G Nivard

Abstract

Here we present a method of genome wide inferred study (GWIS) that provides an approximation of genome wide association study (GWAS) summary statistics for a variable that is a function of phenotypes for which GWAS summary statistics, phenotypic means and covariances are available. GWIS can be performed regardless of sample overlap between the GWAS of the phenotypes on which the function depends. As GWIS provides association estimates and their standard errors for each SNP, GWIS can form the basis for polygenic risk scoring, LD score regression, Mendelian randomization studies, biological annotation and other analyses. Here, we replicate a body mass index (BMI) GWAS using GWIS based on a height GWAS and a weight GWAS. We proceed to use a GWIS to further our understanding of the genetic architecture of schizophrenia and bipolar disorder.

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Mentioned in this Paper

Genome-Wide Association Study
Study
Mendelian Randomization Analysis
Scientific Study
Genome
Schizophrenia
Bipolar Disorder
Body Mass Index Procedure
Analysis
Body Mass Index

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