Overview | 1. Build the GRM | 2. Estimate heritability for a single trait | 3. Batch estimation | 4. Forest plot | 5. Colour palette | 6. Realistic workflow | 7. Citation
Package: Ritable 0.2.1
Lucas França
Ritable: Pedigree-Based Heritability Estimation for Family Cohort Studies
Provides profile-likelihood and general maximum-likelihood variance-components estimation of narrow-sense heritability (h2), household/common-environment effects (c2), and bivariate genetic and environmental correlations for quantitative traits in family cohort and twin studies. Additive genetic relationship matrices are built from pedigrees via 'kinship2', including monozygotic-twin relatedness overrides. Phenotypes are inverse-normal transformed internally. Likelihood-ratio tests use a one-sided chi-squared boundary correction equivalent to SOLAR Eclipse. Ninety-five percent confidence intervals are derived from the profile likelihood rather than Wald approximations. Batch estimation over many traits or trait pairs returns tidy data frames ready for downstream visualisation (forest plots, heatmaps) and includes Benjamini-Hochberg FDR correction for bivariate correlation batches.
Authors:
Ritable_0.2.1.tar.gz
Ritable_0.2.1.zip(r-4.7-any)Ritable_0.2.1.zip(r-4.6-any)Ritable_0.2.1.zip(r-4.5-any)
Ritable_0.2.1.tgz(r-4.6-any)Ritable_0.2.1.tgz(r-4.5-any)
Ritable_0.2.1.tar.gz(r-4.7-any)Ritable_0.2.1.tar.gz(r-4.6-any)
Ritable_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
Ritable/json (API)
| # Install 'Ritable' in R: |
| install.packages('Ritable', repos = c('https://circadia-bio.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/circadia-bio/r-itable/issues
Pkgdown/docs site:https://r-itable.circadia-lab.uk
Last updated from:7392a002f8 (on v0.2.1). Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 145 | ||
| source / vignettes | OK | 307 | ||
| linux-release | OK | 133 | ||
| macos-release | OK | 112 | ||
| macos-oldrel | OK | 107 | ||
| windows-devel | OK | 108 | ||
| windows-release | OK | 99 | ||
| windows-oldrel | OK | 80 | ||
| wasm-release | OK | 98 |
Exports:build_grmbuild_householdherit_aceherit_batchherit_bivarherit_bivar_batchherit_vcint_transformplot_forestRitable_colours
Dependencies:clievaluatehighrkinship2knitrlatticeMatrixquadprogrlangxfunyaml
Getting started with R-itable
Last update: 2026-08-27
Started: 2026-05-28
Twin cohorts: MZ relatedness, household effects, and bivariate correlations
Overview | 1. Simulate a twin cohort | 2. Build the GRM with MZ relatedness | 3. A vs C identifiability: herit_ace() | Covariates and automatic screening | 4. Bivariate genetic/environmental correlation: herit_bivar() | 5. Many trait pairs at once: herit_bivar_batch() | 6. A note on validation | 7. Citation
Last update: 2026-08-27
Started: 2026-08-23
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Build an additive genetic relationship matrix from a pedigree | build_grm |
| Build a household (shared-environment) indicator matrix | build_household |
| A vs C identifiability check (ACE model comparison) | herit_ace |
| Batch heritability estimation over multiple traits | herit_batch |
| Bivariate genetic and environmental correlation between two traits | herit_bivar |
| Batch bivariate genetic/environmental correlations with FDR correction | herit_bivar_batch |
| Profile-likelihood variance-components heritability estimation | herit_vc |
| Inverse-normal (rank-based) transformation | int_transform |
| Forest plot of heritability estimates | plot_forest |
| R-itable colour palette | Ritable_colours |