get_relCat

This function infers relatedness categories in the paired-permutation
function (sip_pair.R) prior to permutation.

A single, phenome-wide permutation of large-scale biobank data.
When a large number of phenotypes are analyzed in parallel, a single
permutation across all phenotypes followed by genetic association analyses
of the permuted data enables estimation of false discovery rates (FDRs)
across the phenome. These FDR estimates provide a significance criterion
for interpreting genetic associations in a biobank context. For the basic
permutation of unrelated samples, this package takes a sample-by-variable
file with ID, genotypic covariates, phenotypic covariates, and phenotypes
as input. For data with related samples, it also takes a file with
sample pair-wise identity-by-descent information.
The function outputs a permuted sample-by-variable file ready
for genome-wide association analysis. See Annis et al. (2021) <doi:10.21203/rs.3.rs-873449/v1>
for details.

Aubrey Annis

Single-Iteration Permutation for Large-Scale Biobank Data

get_relCat function

<dl><dt>pairs</dt>
<dd>Data frame</dd>
<dt>rid.vars</dt>
<dd>Character vector</dd>
<dt>ibd.var</dt>
<dd>String</dd></dl>

Arguments

This function infers relatedness categories in the paired-permutation
function (sip_pair.R) prior to permutation. — get_relCat

<dl>

<dt>pairs</dt>
<dd>Data frame</dd>


<dt>rid.vars</dt>
<dd>Character vector</dd>


<dt>ibd.var</dt>
<dd>String</dd>

</dl>

get_relCat: This function infers relatedness categories in the paired-permutation function (sip_pair.R) prior to permutation.

Description

Usage

Value

Arguments