Provides functionality for designing and analysing two-phase
genetic association studies. Phase 1 data usually come from
genome-wide association study (GWAS) results and we assume phase 2 data
will be part of a targeted genome sequencing or fine-mapping study.
At design stage, the package assists in selecting a subset of individuals
that will be sequenced for phase 2 via alternative approaches, including a
flexible genetic algorithm (GA) for near-optimal designs. Once phase 2 data
have been collected, the package implements methods to analyse phase 1 and
phase 2 data together using semi-parametric regression models via the
expectation-maximization (EM) algorithm. For more details see
Espin-Garcia, Craiu and Bull (2018)
Two-Phase Genetic Association Study design and analysis with missing covariates by design
Provides functionality for selecting and analyzing individuals in two-phase genetic association studies. Phase 1 data usually come from GWAS results and we assume phase 2 genetic data will be part of a targeted genome sequencing/fine-mapping study. The package assists in selecting a subset of individuals that will be sequenced for phase 2. Once phase 2 data have been collected, the package implements methods to analyze phase 1 and 2 data together using semi-parametric regression models.
You can install the current version of twoPhaseGAS from
GitHub using (devtools required):
devtools::install_github("egosv/twoPhaseGAS", ref="main")