Robust Methods for Epistasis Detection


[Up] [Top]

Documentation for package ‘epiGWAS’ version 1.0.2

Help Pages

BOOST Implements BOOST SNP-SNP interaction test
cond_prob Computes the propensity scores
epiGWAS Runs a selection of epistasis detection methods in a joint manner
fast_HMM Fits a HMM to a genotype dataset by calling fastPHASE
forward Applies the forward algorithm to a genotype dataset
forward_sample Applies the forward algorithm to a single observation
genotypes Simulated genotypes
gen_model Samples effect sizes for the disease model
maf SNP minor allele frequencies
merge_cluster Merges a number of clusters around the target
modified_outcome Implements the modified outcome approach
normalized_outcome Implements the normalized modified outcome approach
OWL Implements the outcome weighted learning approach
propensity propensity scores
robust_outcome Implements the robust modified outcome approach
sample_SNP Samples causal SNPs with different effect types
shifted_outcome Implements the shifted modified outcome approach
sim_phenotype Simulates a binary phenotype
stabilityBIG Computes the area under the stability path for all covariates
stabilityGLM Computes the area under the stability path for all covariates
subsample Creates multiple subsamples without replacement