Package index • simxQTL

Genotype Simulation

Functions for simulating genotype data

Functions for simulating effect sizes and phenotypes

parse_num_causal_snps(): Parse Number of Causal SNPs
sim_beta(): Simulate QTL Effects
sim_beta_fix_variant(): Simulate Multiple Traits from Genotype and Assigned Causal Index Vector
simulate_polygenic_trait(): Simulate a Polygenic Trait
sim_multi_traits(): Simulate Multiple Traits from Genotype and Effect Sizes
sim_single_trait_simple(): Simulate Single Trait with Simple Linear Model
simulate_phenotype(): Simulate Phenotype with Controllable Per-SNP Heritability

Functions for simulating and calculating summary statistics

sim_sumstats(): Simulate GWAS Summary Statistics
calculate_sumstat(): Calculate Summary Statistics from Genotype and Phenotype
get_correlation(): Calculate LD (Correlation) Matrix

Functions for simulating cis-eQTL data, originally developed for the “susieR 2.0” manuscript, McCreight et al (2025)

generate_cis_qtl_data(): Generate eQTL Data with Multiple Genetic Architecture Components

Functions for simulating trans-QTL and gene regulatory networks, originally developed for the “transBoost” manuscript, Cao et al (2026)

simulate_trans_expression(): Simulate trans gene expression for different simulation scenarios
simulate_trans_mixture_celltype(): Simulate trans gene expression for a mixture of cell types
get_random_A(): Generate random adjacency matrices for trans gene associations
gene_data(): Generate gene expression data for trans-QTL analysis
gene_data_null1(): Generate null data by random shuffling of genotypes
gene_data_null2(): Generate null data by removing cis-to-trans effects
gene_data_null3(): Generate null data using ARCHIE setting

Functions for simulating causal enrichment

Helper functions for calculations