sipPair_relatednessData

A sample-by-variable data frame with IDs
and identity-by-descent data between samples.

datasets

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

sipPair_relatednessData function

A data frame with 9886 rows and 4 variables:<dl>
 <dt>IID1</dt>
<dd>Individual ID for one sample.</dd> <dt>IID2</dt>
<dd>Iindividual ID for a second sample.</dd> <dt>PropIBD</dt>
<dd>Identity-by-descent proportion of genome shared
 between the two samples.</dd>
</dl>

Format

Single-iteration paired permutation relatedness data — sipPair_relatednessData

A data frame with 9886 rows and 4 variables:<dl>
 <dt>IID1</dt>
<dd>Individual ID for one sample.</dd>

 <dt>IID2</dt>
<dd>Iindividual ID for a second sample.</dd>

 <dt>PropIBD</dt>
<dd>Identity-by-descent proportion of genome shared
 between the two samples.</dd>


</dl>

sipPair_relatednessData: Single-iteration paired permutation relatedness data

Description

Usage

Arguments

Format