GRAB.SimuPheno

Generates various types of phenotypes (quantitative, binary, ordinal,
time-to-event) from linear predictors using appropriate link functions.

Provides a comprehensive suite of genome-wide association study (GWAS) methods
specifically designed for biobank-scale data, including but not limited to, robust approaches
for time-to-event traits (Li et al., 2025 <doi:10.1038/s43588-025-00864-z>) and ordinal
categorical traits (Bi et al., 2021 <doi:10.1016/j.ajhg.2021.03.019>). The package also offers
general frameworks for GWAS of any trait type (Bi et al., 2020 <doi:10.1016/j.ajhg.2020.06.003>),
while accounting for sample relatedness (Xu et al., 2025 <doi:10.1038/s41467-025-56669-1>) or
population structure (Ma et al., 2025 <doi:10.1186/s13059-025-03827-9>). By accurately
approximating score statistic distributions using saddlepoint approximation (SPA), these
methods can effectively control type I error rates for rare variants and in the presence of
unbalanced phenotype distributions. Additionally, the package includes functions for simulating
genotype and phenotype data to support research and method development.

Woody Miao

GRAB

Genome-Wide Robust Analysis for Biobank Data (GRAB)

Wenjian Bi

Wei Zhou

Rounak Dey

Zhangchen Zhao

Seunggeun Lee

GRAB.SimuPheno function

<dl><dt>eta</dt>
<dd>Vector of linear predictors (typically covariates×beta + genotypes×beta).</dd>
<dt>traitType</dt>
<dd>Type of phenotype: "quantitative", "binary", "ordinal", or "time-to-event".</dd>
<dt>control</dt>
<dd>List of simulation parameters specific to each trait type:<dl>
<dt>pCase</dt>
<dd>Proportion of cases (binary traits).</dd></dl></dd><dt>sdError</dt>
<dd>Error term standard deviation (quantitative traits).</dd><dt>pEachGroup</dt>
<dd>Group proportions (ordinal traits).</dd><dt>eventRate</dt>
<dd>Event rate (time-to-event traits).</dd>
</dl>
<dt>seed</dt>
<dd>Random seed for reproducibility (optional).</dd>

Arguments

Simulate phenotypes from linear predictors — GRAB.SimuPheno

<dl>

<dt>eta</dt>
<dd>Vector of linear predictors (typically covariates×beta + genotypes×beta).</dd>


<dt>traitType</dt>
<dd>Type of phenotype: "quantitative", "binary", "ordinal", or "time-to-event".</dd>


<dt>control</dt>
<dd>List of simulation parameters specific to each trait type:<dl>
<dt>pCase</dt>
<dd>Proportion of cases (binary traits).</dd>

<dt>sdError</dt>
<dd>Error term standard deviation (quantitative traits).</dd>

<dt>pEachGroup</dt>
<dd>Group proportions (ordinal traits).</dd>

<dt>eventRate</dt>
<dd>Event rate (time-to-event traits).</dd>


</dl></dd>


<dt>seed</dt>
<dd>Random seed for reproducibility (optional).</dd>

</dl>

GRAB.SimuPheno: Simulate phenotypes from linear predictors

Description

Usage

Value

Arguments

Details