meta.analyse.locus: Re-process locus to meta-analyse of selected phenotypes

In josefin-werme/LAVA: Local Analysis of [co]Variant Association

Re-process locus to meta-analyse of selected phenotypes

Description

Will combine all elements of the requested phenotypes using standard inverse variance weighting, allowing them to be analysed as a single phenotype via the multivariate analysis functions. Note that the univariate test cannot currently be applied to meta-analysed phenotypes, so please do that beforehand on each phenotype individually.

Usage

meta.analyse.locus(locus, meta.phenos)

Arguments

locus	Locus object defined using the process.locus function.
meta.phenos	Phenotypes you want to meta-analyse #'

Value

This function returns an object just like that process.locus function, containing general locus info, the relevant processed sumstats, and info about the input phenotypes.

• id - locus ID

• chr/start/stop - locus coordinates

• snps - list of locus SNPs

• N.snps - number of SNPs

• K - number of PCs

• delta - PC projected joint SNP effects for each phenotype

• sigma - sampling covariance matrix

• omega - genetic covariance matrix

• omega.cor - genetic correlation matrix

• N - vector of average N across locus SNPs for each phenotype

• phenos - phenotype IDs

• binary - boolean vector indicating whether phentoypes are binary

josefin-werme/LAVA documentation built on July 4, 2024, 8:11 p.m.