R: Statistical Tools for Quantitative Genetic Analyses

# Statistical Tools for Quantitative Genetic Analyses

## Documentation for package ‘qgg’ version 1.1.6

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

acc | Compute prediction accuracy for a quantitative or binary trait
adjStat | Adjustment of marker summary statistics using clumping and thresholding
gbayes | Bayesian linear regression models
getG | Get elements from genotype matrix stored in PLINK bedfiles
gfilter | Filter genetic marker data based on different quality measures
glma | Single marker association analysis using linear models or linear mixed models
gmap | Finemapping using Bayesian Linear Regression Models
gprep | Prepare genotype data for all statistical analyses
greml | Genomic rescticted maximum likelihood (GREML) analysis
grm | Computing the genomic relationship matrix (GRM)
gscore | Genomic scoring based on single marker summary statistics
gsea | Gene set enrichment analysis
gsim | Genomic simulation
gsolve | Solve linear mixed model equations
ldsc | LD score regression
magma | Bayesian Multi-marker Analysis of Genomic Annotation (Bayesian MAGMA)
mtadj | Adjustment of marker effects using correlated trait information
pops | Bayesian Polygenic Prioritisation Scoring (Bayesian POPS)
vegas | Perform VEGAS Gene-Based Association Analysis