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PLINK

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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.

LinkImpute

Performs both genotype calling and imputation. LinkImpute uses sequence read information. It permits to investigate the effects of missingness and read depth thresholds on the size and accuracy of the resulting genotype table. The tool offers a way for researchers to investigate a range of quality thresholds prior to imputation and determine what set of parameters best suit their research needs. It can be useful for generating large, high-quality genome-wide genotype data, especially from non-model organisms.

genipe / GENome-wide Imputation PipelinE

A complete genome-wide imputation pipeline which includes automatic reporting, imputed data indexing and management, and a suite of statistical tests for imputed data commonly used in genetic epidemiology (sequence kernel association test (SKAT), Cox proportional hazards for survival analysis, and linear mixed models for repeated measurements in longitudinal studies). The genipe pipeline can be efficiently executed on a local high-performance computing server or on a single desktop computer.

Sanger Imputation Service

Provides genotype imputation and phasing service. Sanger Imputation Service is a web application which allows to upload genome-wide association study (GWAS) data and receive imputed and phased genomes back. Optional pre-phasing is with EAGLE2 or SHAPEIT2 and imputation is with Positional Burrows-Wheeler Transform (PBWT) into a choice of reference panels including 1000 Genomes Phase 3, UK10K, and the Haplotype Reference Consortium. The software is aimed at researchers wanting to impute many thousands of GWAS samples against a consistent reference in a consistent manner.

SNP and indel Imputability

A publicly available SNP and indel imputability database, aiming to provide direct access to imputation accuracy information for markers identified by the 1000 Genomes Project across four major populations and covering multiple GWAS genotyping platforms. SNP and indel imputability information can be retrieved through a user-friendly interface by providing the ID(s) of the desired variant(s) or by specifying the desired genomic region. The query results can be refined by selecting relevant GWAS genotyping platform(s).

BIMBAM / Bayesian IMputation-Based Association Mapping

A framework for the analysis of association studies. Bim-Bam is designed to allow untyped variants to be more effectively and directly tested for association with a phenotype. Compared with standard single-single nucleotide polymorphism (SNP) tests, this approach results in increased power to detect association, even in cases in which the causal variant is typed, with the greatest gain occurring when multiple causal variants are present. It provides more interpretable explanations for observed associations, including assessing, for each SNP, the strength of the evidence that it (rather than another correlated SNP) is causal.

fastPHASE

A statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. fastPHASE is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. For imputing missing genotypes, methods based on this model are as accurate or more accurate than existing methods. For haplotype estimation, the point estimates are slightly less accurate than those from the best existing methods but require a small fraction of the computational cost.

GIGI-Quick

Offers a method for optimizing the rapidity of the imputation results produced by the GIGI software. GIGI-Quick is an open source application including two approaches to memory constrained scenarios: a queue-based and a method using cgroups. The program first divides GIGI input files into different chunks, runs GIGI on the split input files in parallel, and then merges all chunks. The application allows users to perform imputation on a specified region of interest, including on large pedigrees.

Siccuracy

Assists users in handling files processed through the AlphaImpute software. Siccuracy is a package dedicated to work with single-nucleotide-permutation (SNP) files recorded in the format used by AlphaSuite. The application recovers different steps belonging to genotype imputation including the preparation of the files or the evaluation of the resulting imputed genotypes. The program also provides features that allow users to calculate hetereozygosity as well as functions for writing or converting files.

fcGENE

Simplifies and automates the use of different existing analysis packages, especially during the workflow of genotype imputations and corresponding analyses. fcGENE transforms SNP data and imputation results into different formats required for a large variety of analysis packages such as PLINK, SNPTEST, HAPLOVIEW, EIGENSOFT, GenABEL and tools used for genotype imputation such as MaCH, IMPUTE, BEAGLE and others. Data Management tasks like merging, splitting, extracting SNP and pedigree information can be performed. fcGENE also supports a number of bio-statistical quality control processes and quality based filtering processes at SNP- and sample-wise level. The tool also generates templates of commands required to run specific software packages, especially those required for genotype imputation.

ASGSCA

Provides tools to model and test the association between multiple genotypes and multiple traits, taking into account the prior biological knowledge. ASGSCA is an Association Studies for multiple single nucleotide polymorphisms (SNPs) and multiple traits based on Generalized Structured Component Analysis (GSCA). Genes, and clinical pathways are incorporated in the model as latent variables. It offers matrix indicating connections between the latent variables for QCAHS data, dataset to test GSCAestim and GSCA functions and many other.

MOLGENIS-impute

Gives priority to the ease of setting up, configuring and running an imputation. MOLGENIS-impute is an ‘imputation in a box’ solution that seamlessly and transparently automates the set up and running of all the steps of the imputation process. These steps include genome build liftover (liftovering), genotype phasing with SHAPEIT2, quality control, sample and chromosomal chunking/merging, and imputation with IMPUTE2. MOLGENIS-impute is intended for bioinformaticians and geneticists who want to minimize the time and effort needed to set up and configure an imputation pipeline that includes all the necessary quality check and data management steps.

1000G Marker Imputability

A publicly available SNP and indel imputability database, aiming to provide direct access to imputation accuracy information for markers identified by the 1000 Genomes Project across four major populations and covering multiple GWAS genotyping platforms. SNP and indel imputability information can be retrieved through a user-friendly interface by providing the ID(s) of the desired variant(s) or by specifying the desired genomic region. The query results can be refined by selecting relevant GWAS genotyping platform(s). This is the first database providing variant imputability information specific to each continental group and to each genotyping platform.

SVS / SNP and Variation Suite

Allows to perform complex analyses and visualizations on genomic and phenotypic data. SVS provides a set of tools to (1) empower quickly and easily perform quality-assurance and statistical tests for genetic association studies, (2) perform genetic prediction including various means of defining the relationship between samples, (3) validate models and visualize the results, (4) identify regions of copy number variability, (5) perform statistical tests on the copy number results and others.

TUNA / Testing UNtyped Alleles

Obsolete
Implements a fast and efficient algorithm for testing association of genotyped and ungenotyped variants in genome-wide case-control studies. TUNA uses Linkage Disequilibrium (LD) information from existing comprehensive variation datasets such as HapMap to construct databases of frequency predictors using linear combination of haplotype frequencies of genotyped SNPs. The predictors are used to estimate untyped allele frequencies, and to perform association tests. The methods incorporated in TUNA achieve great accuracy in estimation, and the software tool is computationally efficient and does not demand a lot of system memory and CPU resources.