Multivariate analysis software tools | Genome-wide association study
Joint association analysis of multiple traits in a genome-wide association study offers several advantages over analyzing each trait in a separate GWAS. Several methods that have been developed to perform multiple trait analysis.
A program for the analysis of single SNP association in genome-wide studies. The tests implemented include 1) binary (case-control) phenotypes, single and multiple quantitative phenotypes, 2) Bayesian and Frequentist tests, 3) ability to condition upon an arbitrary set of covariates and/or SNPs and 4) various different methods for the dealing with imputed SNPs.
Enables structural equation modeling (SEM) with continuous data. lavaan is an R package providing a collection of tools that can be used to explore, estimate, and understand a wide family of latent variable models, including factor analysis, structural equation, longitudinal, multilevel, latent class, item response, and missing data models. The software can serve for estimating multiple multivariate statistical models, such as path analysis, confirmatory factor analysis, structural equation modeling and growth curve models.
A free, open-source whole genome association analysis toolset, designed to perform a range of basic, large-scale analyses in a computationally efficient manner. The focus of PLINK is purely on analysis of genotype/phenotype data, so there is no support for steps prior to this (e.g. study design and planning, generating genotype or CNV calls from raw data). Through integration with gPLINK and Haploview, there is some support for the subsequent visualization, annotation and storage of results.
Enables genetic association testing of multiple phenotypes. MultiPhen is a multivariate method that performs genome-wide association study (GWAS) on multiple phenotypes by identifying the linear combination of the phenotypes most associated with genotype at each single nucleotide polymorphism (SNP). The software is applicable to both quantitative - regardless of phenotype distribution - and case-control data.
Assists users in testing genotype-phenotype relations. TATES is a multivariate method for combining p-values across different, correlated phenotypes. This method allows researchers to test their genetic associations using standard genome-wide association study (GWAS) software. It deals with the high phenotypic dimensionality by combining the univariate analyses while correcting for the relatedness between phenomic dimensions.
A method of iterated sample splitting that uses one portion of the data for training and the remainder for testing. This cross-validation approach maintains the type I error control and yet utilizes the data efficiently, resulting in a powerful test for association.
Applies high-dimensional penalized regression into heterogeneous subgroups. Fuser is a package which can allow to deal with subgroup-specific sparsity patterns and parameter estimates. This application jointly estimates the regression coefficients that induce global sparsity and encourage similarity between subgroup-specific coefficients. It aims to optimize pooling or subgroup-wise analysis efficiency.