Two-Phase Genetic Association Study Design and Analysis with Missing Covariates by Design
Overview
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) doi:10.1002/gepi.22099 and Espin-Garcia, Craiu and Bull (2021) doi:10.1002/sim.9211.
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK7 OK2026-05-28
Documentation
- Help pages
- 11
- Examples that run
- 71%5 run in a plain check · 2 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 67%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
Forks over time
2 development-tooling and community-health practices detected across 2 families in the upstream repository
Checks run against github.com/egosv/twophasegas on 2026-10-18.
Dependencies
Installing twoPhaseGAS adds 10 packages (5 with compiled code, 24 MB of source tarballs). Heaviest: BH 14 MB, data.table 5.7 MB, nloptr 2.1 MB.
Code & Tests
People & History
- 1.2.5Latest2026-05-27 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-05-27
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 59 KB
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