Tools   Select Another Resource Report Type

http://www.sph.umich.edu/csg/abecasis/LAMP/

Software for linkage and association modeling in pedigrees that uses a maximum likelihood model to extract information on genetic linkage and association from samples of unrelated individuals, sib pairs, trios and larger pedigrees (Li et al, 2005; Li et al, 2006). It provides estimates of genetic model parameters and powerful tests of association in settings where population stratification is not a concern.

Proper citation: LAMP (RRID:SCR_001740) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/software/syzygy/

A targeted sequencing post processing analysis software tool that allows: 1. SNP and indel detection; 2. Allele frequency estimation; 3. Single-marker association test; 4. Group-wise marker test association; 5. Experimental QC summary (%dbSNP, Ts/Tv, Ns/S); 6. Power to detect variant. (entry from Genetic Analysis Software)

Proper citation: SYZYGY (RRID:SCR_002157) Copy   

•   Source: SciCrunch Registry

http://mayoresearch.mayo.edu/mayo/research/schaid_lab/software.cfm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software application that calculates an exact stratified test for HWE for diallelic markers, such as single nucleotide polymorphisms (SNPs), and an exact test for homogeneity of Hardy Weinberg disequilbrium. In addition, exact tests for HWE are calculated for each stratum. (entry from Genetic Analysis Software)

Proper citation: HWESTRATA (RRID:SCR_001097) Copy   

•   Source: SciCrunch Registry

http://www.bios.unc.edu/~lin/software/GAS2/

Software application for evaluating Statistical Significance in Two-Stage Genomewide Association Studies (entry from Genetic Analysis Software)

Proper citation: GAS2 (RRID:SCR_001126) Copy   

•   Source: SciCrunch Registry

http://web.bioinformatics.ic.ac.uk/eqtlexplorer/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. An eQTL visualization tool that allows users to mine and understand data from a repository of genetical genomics experiments (entry from Genetic Analysis Software)

Proper citation: EQTL EXPLORER (RRID:SCR_001123) Copy   

•   Source: SciCrunch Registry

http://people.virginia.edu/~wc9c/TDTPC/Download.htm

Software program to compute the statistical power of the Transmission/Disequilibrium Test (TDT) analytically, based on the most accurate asymptotic algorithms up to date, and is applicable in very general situations, where different parental disease status, multiple children, mixed family type and recombination events are considered. Routine algorithms for Monte Carlo simulations with significant improvements are also implemented in this program. (entry from Genetic Analysis Software)

Proper citation: TDT-PC (RRID:SCR_001116) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/targetgene/

MATLAB tool to effectively identify potential therapeutic targets and drugs in cancer using genetic network-based approaches. It can rapidly extract genetic interactions from a precompiled database stored as a MATLAB MAT-file without the need to interrogate remote SQL databases. Millions of interactions involving thousands of candidate genes can be mapped to the genetic network within minutes. While TARGETgene is currently based on the gene network reported in (Wu et al.,Bioinformatics 26:807-813, 2010), it can be easily extended to allow the optional use of other developed gene networks. The simple graphical user interface also enables rapid, intuitive mapping and analysis of therapeutic targets at the systems level. By mapping predictions to drug-target information, TARGETgene may be used as an initial drug screening tool that identifies compounds for further evaluation. In addition, TARGETgene is expected to be applicable to identify potential therapeutic targets for any type or subtype of cancers, even those rare cancers that are not genetically recognized. Identification of Potential Therapeutic Targets * Prioritize potential therapeutic targets from thousands of candidate genes generated from high-throughput experiments using network-based metrics * Validate predictions (prioritization) using user-defined benchmark genes and curated cancer genes * Explore biologic information of selected targets through external databases (e.g., NCBI Entrez Gene) and gene function enrichment analysis Initial Drug Screening * Identify for further evaluation existing drugs and compounds that may act on the potential therapeutic targets identified by TARGETgene * Explore general information on identified drugs of interest through several external links Operating System: Windows XP / Vista / 7

Proper citation: TARGETgene (RRID:SCR_001392) Copy   

•   Source: SciCrunch Registry

http://faculty.washington.edu/browning/beagle/beagle.html

Software package for analysis of large-scale genetic data sets with hundreds of thousands of markers genotyped on thousands of samples. BEAGLE can * phase genotype data (i.e. infer haplotypes) for unrelated individuals, parent-offspring pairs, and parent-offspring trios. * infer sporadic missing genotype data. * impute ungenotyped markers that have been genotyped in a reference panel. * perform single marker and haplotypic association analysis. * detect genetic regions that are homozygous-by-descent in an individual or identical-by-descent in pairs of individuals. Beagle can also be used in conjunction with PRESTO, a program for fast and flexible permutation testing. PRESTO can compute empirical distributions of order statistics, analyze stratified data, and determine significance levels for one-stage and two-stage genetic association studies. BEAGLE is written in Java and runs on any computing platform with a Java version 1.6 interpreter (e.g. Windows, Unix, Linux, Solaris, Mac).

Proper citation: BEAGLE (RRID:SCR_001789) Copy   

•   Source: SciCrunch Registry

https://www.apbenson.com/cyrillic-downloads

Software application for pedigree drawing with fully integrated risk analysis and support for industry standard databases (MS Access and Corel Paradox). It is designed for genetic counselors and others who work with patients. Cyrillic 2 draws pedigrees, works with genetic marker data, lets you do haplotyping and allows exports to a range of linkage analysis packages.

Proper citation: CYRILLIC (RRID:SCR_001823) Copy   

•   Source: SciCrunch Registry

http://www.math.hkbu.edu.hk/~mng/CLUSTAG/CLUSTAG.html

Software application that uses hierarchical clustering and graph methods for selecting tag SNPs (single nucleotide polymorphisms). Cluster and set-cover algorithms are developed to obtain a set of tag SNPs that can represent all the known SNPs in a chromosomal region, subject to the constraint that all SNPs must have a squared correlation R2 > C with at least one tag SNP, where C is specified by the user. The program is implemented with Java, and it can run in Windows platform as well as the Unix environment.

Proper citation: CLUSTAG (RRID:SCR_001816) Copy   

•   Source: SciCrunch Registry

http://www.preger.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Sample collection of oocytes obtained from various sized antral follicles, and embryos obtained through a variety of different protocols. The PREGER makes it possible to undertake quantitative gene-expression studies in rhesus monkey oocytes and embryos through simple and cost-effective hybridization-based methods.

Proper citation: Primate Embryo Gene Expression Resource (RRID:SCR_002765) Copy   

•   Source: SciCrunch Registry

http://portal.ncibi.org/gateway/saga.html

SAGA (Substructure Index-based Approximate Graph Alignment) is a tool for querying a biological graph database to retrieve matches between subgraphs of molecular interactions and biological networks. SAGA implements an efficient approximate subgraph matching algorithm that can be used for a variety of biological graph matching problems such as the pathway matching SAGA uses to compare pathways in KEGG and Reactome. You can also use SAGA to find matches in literature databases that have been parsed into semantic graphs. In this use of SAGA, portions of PubMed have been parsed into graphs that have nodes representing gene names. A link is drawn between two genes if they are discussed in the same sentence (indicating there is potential association between the two genes). SAGA lets you match graphs between different databases even though the content is distinct and the databases organize pathways in different ways. This cross-database matching is achieved by SAGA's flexible approximate subgraph matching model that computes graph similarity, and allows for node gaps, node mismatches, and graph structural differences. Comparing pathways from different databases can be a useful precursor to pathway data integration. SAGA is very efficient for querying relatively small graphs, but becomes prohibitory expensive for querying large graphs. Large graph data sets are common in many emerging database applications, and most notably in large-scale scientific applications. To fully exploit the wealth of information encoded in graphs, effective and efficient graph matching tools are critical. Due to the noisy and incomplete nature of real graph datasets, approximate, rather than exact, graph matching is required. Furthermore, many modern applications need to query large graphs, each of which has hundreds to thousands of nodes and edges. TALE is an approximate subgraph matching tool for matching graph queries with a large number of nodes and edges. TALE employs a novel indexing technique that achieves a high pruning power and scales linearly with the database size.

Proper citation: Substructure Index-based Approximate Graph Alignment (RRID:SCR_003434) Copy   

•   Source: SciCrunch Registry

http://www.genomeutwin.org/index.htm

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Study of genetic and life-style risk factors associated with common diseases based on analysis of European twins. The population cohorts used in the Genomeutwin study consist of Danish, Finnish, Italian, Dutch, English, Australian and Swedish twins and the MORGAM population cohort. This project will apply and develop new molecular and statistical strategies to analyze unique European twin and other population cohorts to define and characterize the genetic, environmental and life-style components in the background of health problems like obesity, migraine, coronary heart disease and stroke, representing major health care problems worldwide. The participating 8 twin cohorts form a collection of over 0.6 million pairs of twins. Tens of thousands of DNA samples with informed consents for genetic studies of common diseases have already been stored from these population-based twin cohorts. Studies targeted to cardiovascular traits are now being undertaken in MORGAM, a prospective case-cohort study. MORGAM cohorts include approximately 6000 individuals, drawn from population-based cohorts consisting of more than 80 000 participants who have donated DNA samples.

Proper citation: GenomEUtwin (RRID:SCR_002843) Copy   

•   Source: SciCrunch Registry

http://www.geneticepi.com/Research/software/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 16,2023. Software application (entry from Genetic Analysis Software).

Proper citation: MILD (RRID:SCR_003335) Copy   

•   Source: SciCrunch Registry

http://linkage.rockefeller.edu/pawe3d/

Software application (entry from Genetic Analysis Software)

Proper citation: PAWE-3D (RRID:SCR_003326) Copy   

•   Source: SciCrunch Registry

http://microarray.ym.edu.tw:8080/tools/module/set/index.jsp?mode=home

A Java tool to evaluate and visualize the sample discrimination abilities of gene expression signatures. This tool provides a filtration function for signature identification and lies between clinical analyses and class prediction (or feature selection) tools.

Proper citation: SET (RRID:SCR_003605) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/Tools/

The European Bioinformatics Institute (EBI) toolbox area provides a comprehensive range of tools for the field of bioinformatics. These are subdivided into categories in the left menu for convenience. EBI has developed a large number of very useful bioinformatics tools. A few examples include: - Similarity & Homology - the BLAST or FASTA programs can be used to look for sequence similarity and infer homology. - Protein Functional Analysis - InterProScan can be used to search for motifs in your protein sequence. - Proteomic Services NEW - UniProt DAS server allows researchers to show their research results in the context of UniProtKB/Swiss-Prot annotation. - Sequence Analysis - ClustalW2 a sequence alignment tool. - Structural Analysis - MSDfold can be used to query your protein structure and compare it to those in the Protein Data Bank (PDB). - Web Services - provide programmatic access to the various databases and retrieval/analysis services EBI provides. - Tools Miscellaneous - Expression Profiler a set of tools for clustering, analysis and visualization of gene expression and other genomic data. Sponsors: This resource is sponsored by EBI.

Proper citation: Toolbox at the European Bioinformatics Institute (RRID:SCR_002872) Copy   

•   Source: SciCrunch Registry

http://www.people.fas.harvard.edu/~junliu/genotype/

Software application (entry from Genetic Analysis Software)

Proper citation: GS-EM (RRID:SCR_003992) Copy   

•   Source: SciCrunch Registry

http://www.geenivaramu.ee/en/

The Estonian Biobank is the population-based biobank of the EGCUT. The project is conducted in accordance with the Estonian Genes Research Act and all participants have signed a broad informed consent form (www.biobank.ee and Metspalu 2004, Drug Dev. Res.). As of December 2011, the biobank contains 51,515 participants (gene donors). The database of genotypic, phenotypic, health and genealogical information represents about 5% of Estonia''s adult population, and is the largest cohort ever gathered in Estonia. The age, sex and geographical distribution of this cohort reflect the structure of the adult population in Estonia. The database enables to conduct research in order to find links between genes, environmental factors, lifestyles and complex diseases or other traits. Active use of the biobank has started and although the first users are researchers all over the world with hundreds of different projects currently underway, industry is also interested. At the international level, the EGCUT will join the BBMRI follow-up program (ERIC) and through this channel provide service (biobanking, genotyping, sequencing and data analysis) for the centers in Europe who need it. Currently, the first follow-up study is underway and the molecular information of the cohort will be increased. For example, we have over 12 000 DNA samples analyzed by high density genotyping arrays and over 10 000 plasma samples analyzed by NMR scans, over 1000 individuals with RNA expression arrays, 2000 individuals with clinical laboratory analysis (over 40 tests) and over 60 full genomes are under deep sequencing. The infrastructure of the EGCUT includes a laboratory for DNA genotyping and next generation sequencing all based on Illumina platforms (HiScanSQ, HiSeq2000 and robotics), an IT unit (databases) with required computing power and storage space (1.2PB), data analysis team (bioinformatics and statistical genetics) and last but not least, a patient recruitment unit (health records, lifestyle and environmental information and biological samples ����?����������?? DNA, plasma and WBC from all 51515 gene donors). This is all located on 1000m2 in a brand new laboratory building, Riia str 23, Tartu, Estonia.

Proper citation: Estonian Genome Center (RRID:SCR_004467) Copy   

•   Source: SciCrunch Registry

http://www3.marshfieldclinic.org/chg/pages/default.aspx?page=chg_pers_med_res_prj

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. A large collection of biological samples and health information collected for the Personalized Medicine Research Project (PMRP) for use in biological research. Genetic information from 20,000 participants forms a database enabling scientists to study which genes cause disease, which genes predict reactions to drugs, and how environment and genes work together to cause disease. The goal of this project is to learn how to apply genetic science to human health. This knowledge will help researchers develop new medications and diagnostic tests, and will enable physicians to prescribe medications that work best for a particular person. Marshfield Clinic Personalized Medicine Research Project (PMRP) resources currently available: DNA, plasma, serum, questionnaire, electronic medical records to construct phenotypes; ability to recontact subjects for additional information (where they have given consent for recontact); stored pathology specimens collected for clinical purposes; 51 clinically relevant polymorphisms; Illumina 660 quad for ~4200 subjects aged 50+.

Proper citation: Marshfield Clinic Biobank (RRID:SCR_004368) Copy   

•   Source: SciCrunch Registry