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http://gusevlab.org/projects/germline/

Software application for discovering long shared segments of Identity by Descent (IBD) between pairs of individuals in a large population. It takes as input genotype or haplotype marker data for individuals (as well as an optional known pedigree) and generates a list of all pairwise segmental sharing., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GERMLINE (RRID:SCR_001720) Copy   

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http://www.sanger.ac.uk/science/tools/olorin

An interactive filtering tool for next generation sequencing data coming from the study of large complex disease pedigrees. It integrates gene flow output from Merlin and next generation sequencing data. Users can interactively filter and prioritize variants based on haplotype sharing across different sets of selected individuals and allele frequency in reference datasets. (entry from Genetic Analysis Software)

Proper citation: OLORIN (RRID:SCR_002015) Copy   

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https://sites.pitt.edu/~weeks/docs/SimIBD.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software application (entry from Genetic Analysis Software)

Proper citation: SIMIBD (RRID:SCR_002094) Copy   

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http://gmt.genome.wustl.edu/packages/breakdancer/

A Perl/C++ software package that provides genome-wide detection of structural variants from next generation paired-end sequencing reads. BreakDancerMax predicts five types of structural variants: insertions, deletions, inversions, inter- and intra-chromosomal translocations from next-generation short paired-end sequencing reads using read pairs that are mapped with unexpected separation distances or orientation. (entry from Genetic Analysis Software)

Proper citation: BREAKDANCER (RRID:SCR_001799) Copy   

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http://haplopainter.sourceforge.net/

A pedigree drawing program, suitable in processing haplotype outputs from GENEHUNTER, ALLEGRO, MERLIN, and SIMWALK (entry from Genetic Analysis Software)

Proper citation: HAPLOPAINTER (RRID:SCR_001710) Copy   

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http://lgsun.grc.nia.nih.gov/cDNA/cDNA.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Project portal housing NIA Mouse EST Project, NIA Mouse cDNA Clone Sets, a NIA Mouse Gene Index, NIA Mouse cDNA Database, and NIA Mouse Microarrays. Characteristics of NIA 15K Mouse cDNA Clone Set * ~15,000 unique cDNA clones were rearrayed among 52,374 ESTs from pre- and periimplantation embryos, E12.5 female gonad/mesonephros, and newborn ovary. * Up to 50% are derived from novel genes. * ~1.5 kb average insert size. * Clones were sequenced from 5' and 3' termini to obtain longer reads and verify sequence. Sequence information is available at this Web Site. Clone names are from H3001A01 to H3159G07. * Handling of NIA 15k cDNA Clone Set(June3, 2000) Characteristics of NIA mouse 7.4K cDNA Clone Set * ~7407 cDNA clones with no redundancy within the set or with NIA Mouse 15K. * ~1.5 kb average insert size for short insert clones and ~2.5-3.0 kb average insert size for long-insert enriched clones.. * Clones were sequenced from 5' and 3' termini to obtain longer reads and verify sequence. Sequence information is available at this Web Site. Clone names are from H4001A01 to H4079G07. * Handling of NIA mouse 7.4k cDNA Clone Set (similar to handling of NIA mouse 15K, to be updated) Individual Clones are available from ATCC and MRC geneservice, UK. To obtain Clone, search the database using either the rearrayed clone name or GenBank accession number at the Key Word Search page. Follow the link to the sequence information page for the rearrayed clone to obtain source clone ATCC number. Clicking the ATCC number will bring up the ATCC ordering page for the source clone. There is essentially no overlap between the two clone sets (7.4K and 15K) said Minoru S.H. Ko, M.D., Ph.D., head of the Developmental Genomics and Aging Section in the NIA's Laboratory of Genetics. In addition, all cDNA clones in the NIA 7.4K set were purified by single colony isolation and sequence-verified, and more than half were prepared by a new procedure that yields long full-length cDNAs (average size 3-4 kb). The NIA Mouse 15k and 7.4k Clone Set Data and Published Microarray Data are available for download. NIA Mouse Microarrays *Microarray Data Download * 60-mer Oligo Array Platform ** (A) NIA 22k Oligo Microarray Gene List (21939 gene features) ( Carter et al 2003 ) ** (B) Agilent Mouse Development Oligo Microarray Gene List ** ( Subset of Microarray (A): 20,280 gene features ) * Data Analysis Tools

Proper citation: NIA Mouse cDNA Project Home Page (RRID:SCR_001472) Copy   

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http://www.ncbi.nlm.nih.gov/CBBresearch/Schaffer/pedhunter.html

Software package that facilitates creation and verification of pedigrees within large genealogies. The pedigrees are produced as files in LINKAGE format ready for linkage analysis and for drawing with a variety of drawing programs, such as PEDDRAW and cranefoot.

Proper citation: PEDHUNTER (RRID:SCR_002031) Copy   

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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   

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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   

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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   

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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   

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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   

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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   

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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   

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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   

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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   

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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   

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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   

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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   

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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