get_singSamp

This function checks for uneven numbers of individuals within relatedness
category and creates a data set for permuting single samples that will not
be pair permuted (sip_pair.R).

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_singSamp function

<dl><dt>df</dt>
<dd>Data frame</dd>
<dt>deglst</dt>
<dd>List of data frames</dd>
<dt>id.var</dt>
<dd>String</dd></dl>

Arguments

This function checks for uneven numbers of individuals within relatedness
category and creates a data set for permuting single samples that will not
be pair permuted (sip_pair.R). — get_singSamp

<dl>

<dt>df</dt>
<dd>Data frame</dd>


<dt>deglst</dt>
<dd>List of data frames</dd>


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

</dl>

This function checks for uneven numbers of individuals within relatedness
category and creates a data set for permuting single samples that will not
be pair permuted (sip_pair.R).

get_singSamp: This function checks for uneven numbers of individuals within relatedness category and creates a data set for permuting single samples that will not be pair permuted (sip_pair.R).

Description

Usage

Value

Arguments