Summary statistics software tools | Genome-wide association study data analysis
Imputation of individual level genotypes at untyped markers using an external reference panel of genotyped or sequenced individuals has become standard practice in genetic association studies. Direct imputation of summary statistics can also be valuable, for example in meta-analyses where individual level genotype data are not available.
Provides a method for partitioning heritability from genome-wide association studies (GWAS) summary statistics while accounting for linked markers. LD SCore regression identified strong enrichment for conserved regions across all traits, and immunological disease-specific enrichment for FANTOM5 enhancers. It is computationally tractable at very large sample sizes. It also includes a tool for applying the method to sets of specifically expressed genes for identifying disease relevant tissues and cell types.
Produces descriptive statistics, graphics and quality assessment for gene mapping data. PEDSTATS is a program that can be used for summarizing salient features and performing basic quality checks on different types of gene-mapping data. This tool is able to report basic statistics like heterozygosity and genotyping completeness. It can also furnish graphical summaries of allele and genotype frequencies.
Performs approximate bayesian computations (ABC). ABCtoolbox is a series of computer programs that can be pipelined to estimate parameters of complex models. The software incorporates several ABC algorithms and handles various types of data by interacting with external simulation programs. It enables users to perform all the necessary steps of a full ABC analysis, like parameter sampling from prior distributions, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.
Performs approximate Bayesian computation (ABC) model choice and parameter inference via random forests. abcrf is a package that permits users to estimate posterior expectations, quantiles, variances and covariances of parameters. It includes commands that plot the posterior density given a new summary statistic or to calculate and plot for different numbers of tree, the out-of-bag errors associated with an ABC-RF object.
Identifies associations between gene expression and complex traits using summary data from genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL). Then, a heterogeneity test to distinguish pleiotropy from linkage can be realized. The SMR tool allows to search the most functionally relevant genes at the loci identified in GWAS data for complex traits. It provides a useful tool to prioritize genes underlying GWAS hits for follow up functional studies.
Assess whether two association signals which are consistent with a shared causal variant. The COLOC method is appropriate for associations detected by GWAS (genome-wide association study). It is able to derive the output statistics from single single nucleotide polymorphism (SNP) summary statistics and to produce systematic meta-analysis type comparisons across multiple GWAS datasets. This tool gives several informations concerning candidate causal genes in associated intervals, and work in the understanding of complex diseases.
Determines the percentage explained by variants and/or interactions of interest. VarExp uses meta-analysis summary statistics from genome wide association study GWAS to proceed. It was tested on a simulation study comparing the adjusted coefficients of determination from regressions and the estimates across 1 000 replicates. This tool makes estimation straightforward in large-scale consortia where pooling individual genotype data can be extremely challenging.