Complex trait prediction software tools | Genome-wide association study data analysis
The success of genome-wide association studies (GWASs) has led to increasing interest in making predictions of complex trait phenotypes, including disease, from genotype data. Rigorous assessment of the value of predictors is crucial before implementation.
Estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation.
Supplies a method to compute exact values of standard test statistics in linear mixed models. GEMMA is a program built on EMMA software. The application fits three types of models: univariate and multivariate linear mixed model as well as Bayesian sparse linear mixed model. In addition, it estimates variance component and chip heritability. This tool provides a mean to make exact calculations for large genome wide association studies (GWAS).
Allows users to perform mixed model analysis for genome wide association studies (GWAS). rrBLUP aims to assist users in genomic selection. It provides predictions based on maximum likelihood (ML) or restricted maximum likelihood (REML) approach to ridge regression (RR) and other kernels. It also includes features dedicated to the resolution of marker-based and kinship-based versions of the genomic prediction problem as well as several genetic models such as the nonadditive Gaussian kernel.
Identifies gene-by-gene and gene-by-environment interactions. GMDR allows users to perform analyses for detection of multifactor interactions with large-scale data. The software implements a set of methods on the analysis of interactions with diverse study designs such as case-control design, family based design or a combination of both. GMDR also provides features such as large-scale data management and preprocessing. It can assist in revealing genetic architecture in terms of gene-gene interactions underlying complex traits.
Allows users to capture current standard practices in polygenic risk score (PRS) studies and the different applications of PRS. PRSice performs a simulation study to estimate a P-value significance threshold for high-resolution PRS studies and produces plots for inspection of results. One of the function of this software is to automate PRS analyses. It is able to calculate PRS at any number of P-value thresholds (PT) and can thus identify the most predictive threshold.
Facilitates the use of G-BLUP and P-BLUP analyses on complex traits. GenoMatrix provides a collection of applications that assists users to generate, modify and compare necessary relationship matrices. Starting from input data, users are assisted from assessing data quality to obtain pedigree- and marker-based additive, dominance, and epistatic relationship matrices of interest and their inverses.
Assists users with the problem of detecting rare variant associations in the presence of misclassification and gene interaction. KBAC combines variant classification and association testing in a coherent framework. The effect of this method can be affected by the inclusion of non-causal mutations or the exclusion of causal variants in the sample, to varying degrees.