SNPs-Based Whole Genome Association Studies
Association analysis between a single SNP and a given phenotype
Bonferroni correction of p values
Population substructure
Get gene symbol from a list of SNPs
Get Latex output
Extract significant SNPs from an object of class 'WGassociation'
Haplotype interaction with a covariate
Collapsing (or recoding) genotypes into different categories (generall...
Identify interaction term
Two-dimensional SNP analysis for association studies
Print ORs and 95% confidence intervals for an object of class 'haplo.g...
Check whether a SNP is Monomorphic
max-statistic for a 2x3 table
Create a group of locus objects from some SNPs, assign to 'model.matri...
max-statistic for a 2x3 table
Extract odds ratios, 95% CI and pvalues
Permutation test analysis
Plot of missing genotypes
Function to plot -log p values from an object of class 'WGassociation'
Functions for inspecting population substructure
Get related samples
Whole genome association analysis
Convert columns in a dataframe to class 'snp'
SNP object
Internal SNPstat functions
Sort a vector of SNPs by genomic position
Test for Hardy-Weinberg Equilibrium
Descriptive sample size, mean, and standard error
Descriptive sample size and percentage
Whole genome association analysis
Functions to perform most of the common analysis in genome association studies are implemented. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis). Permutation test and related tests (sum statistic and truncated product) are also implemented. Max-statistic and genetic risk-allele score exact distributions are also possible to be estimated. The methods are described in Gonzalez JR et al., 2007 <doi: 10.1093/bioinformatics/btm025>.