genio - Genetics Input/Output Functions

Implements readers and writers for file formats associated with genetics data. Reading and writing Plink BED/BIM/FAM and GCTA binary GRM formats is fully supported, including a lightning-fast BED reader and writer implementations. Other functions are 'readr' wrappers that are more constrained, user-friendly, and efficient for these particular applications; handles Plink and Eigenstrat tables (FAM, BIM, IND, and SNP files). There are also make functions for FAM and BIM tables with default values to go with simulated genotype data.

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7.93 score 18 stars 6 dependents 412 scripts 1.3k downloads

simtrait - Simulate Complex Traits from Genotypes

Simulate complex traits given a SNP genotype matrix and model parameters (the desired heritability, optional environment group effects, number of causal loci, and either the true ancestral allele frequencies used to generate the genotypes or the mean kinship for a real dataset). Emphasis is on avoiding common biases due to the use of estimated allele frequencies. The code selects random loci to be causal, constructs coefficients for these loci and random independent non-genetic effects, and can optionally generate random group effects. Traits can follow three models: random coefficients, fixed effect sizes, and infinitesimal (multivariate normal). GWAS method benchmarking functions are also provided. Described in Yao and Ochoa (2023) <doi:10.7554/eLife.79238>.

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5.35 score 6 stars 37 scripts 189 downloads

simfam - Simulate and Model Family Pedigrees with Structured Founders

The focus is on simulating and modeling families with founders drawn from a structured population (for example, with different ancestries or other potentially non-family relatedness), in contrast to traditional pedigree analysis that treats all founders as equally unrelated. Main function simulates a random pedigree for many generations, avoiding close relatives, pairing closest individuals according to a 1D geography and their randomly-drawn sex, and with variable children sizes to result in a target population size per generation. Auxiliary functions calculate kinship matrices, admixture matrices, and draw random genotypes across arbitrary pedigree structures starting from the corresponding founder values. The code is built around the plink FAM table format for pedigrees. There are functions that simulate independent loci and also functions that use an explicit recombination model to simulate linkage disequilibrium (LD) in the pedigree, as well as population analogs resembling the Li-Stephens model. Described in Yao and Ochoa (2023) <doi:10.7554/eLife.79238>.

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4.43 score 3 stars 18 scripts 220 downloads

metalcor - Meta-Analysis of Correlated Genetic Association Studies

The main function performs meta-analysis of genetic association study summary statistics that may be correlated due to cryptic relatedness or other confounders, generalizing inverse variance weighted methods. The function that estimates the correlation structure is also provided standalone. Another key innovation, the estimation of the correlation parameter from the median product of correlated standard normal variables, is provided, as well as a complete set of functions for their underlying distribution: density, cumulative, quantile, and random deviates. Described in Tu and Ochoa (2025) <doi:10.1101/2025.05.10.653279>.

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3.90 score 1 stars 16 scripts

metalcor - Meta-Analysis of Correlated Genetic Association Studies

The main function performs meta-analysis of genetic association study summary statistics that may be correlated due to cryptic relatedness or other confounders, generalizing inverse variance weighted methods. The function that estimates the correlation structure is also provided standalone. Another key innovation, the estimation of the correlation parameter from the median product of correlated standard normal variables, is provided, as well as a complete set of functions for their underlying distribution: density, cumulative, quantile, and random deviates. Described in Tu and Ochoa (2025) <doi:10.1101/2025.05.10.653279>.

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2.90 score 16 scripts