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http://www.stat.washington.edu/thompson/Genepi/Albert/albert.shtml

Software application that estimates genotype relative risks, genotyping error rates and population risk allele frequencies from marker genotype data in case-parent trios. ALBERT uses the distribution of trio marker genotypes to compute maximum likelihood estimates for the parameters. (entry from Genetic Analysis Software)

Proper citation: ALBERT (RRID:SCR_009037) Copy   

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http://genome.sph.umich.edu/wiki/ExomePicks

Software application that suggests individuals to be sequenced in a large pedigree. ExomePicks assumes that a genotyping chip or another cost effective means will be used to determine IBD sharing in the pedigree and that, subsequently, one would like to sequence a minimal number of individuals and use their sequences together with IBD information to deduce the sequence of other individuals in the pedigree. We are currently using it in the context of whole exome and whole genome sequencing studies to pick individuals to be sequenced from large family collections. (entry from Genetic Analysis Software)

Proper citation: EXOMEPICKS (RRID:SCR_009174) Copy   

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http://kumasakanatsuhiko.jp/projects/disentangler/

Software application that is a visualization technique for linkage disequilibrium mapping and haplotype analysis of multiple multi-allelic genetic markers. (entry from Genetic Analysis Software)

Proper citation: DISENTANGLER (RRID:SCR_009161) Copy   

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http://gmc.mdc-berlin.de/alohomora/

Software application designed to facilitate genome-wide linkage studies performed with high-density single nucleotide polymorphism (SNP) marker panels such as the Affymetrix GeneChip(R) Human Mapping 10K Array. (entry from Genetic Analysis Software)

Proper citation: ALOHOMORA (RRID:SCR_009117) Copy   

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

Software application who''s main novel feature is conditional linkage analyses, in which the population can be subdivided according to criteria at some loci and analyzed for linkage at other loci. CASPAR uses simulation to overcome the problems inherent in such multiple testing. (entry from Genetic Analysis Software)

Proper citation: CASPAR (RRID:SCR_009074) Copy   

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http://www.helmholtz-muenchen.de/en/ige/service/software-download/genehunter-imprinting/index.html#c63682

Resource no longer in service. Documented on February 23,2021.Software tool as modification of GENEHUNTER software package . Allows for parametric multi-marker linkage analysis of dichotomous traits caused by imprinted genes. By specification of two heterozygote penetrance parameters, paternal and maternal origin of the disease allele can be treated differently in terms of probability of expression of the trait.

Proper citation: genehunter-imprinting (RRID:SCR_009104) Copy   

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http://www.stat.auckland.ac.nz/~browning/ccrel/ccrel.htm

Software program for case-control genetic analysis that takes relatedness between individuals into account. It will perform single-marker and haplotypic tests, however it will only work with SNP or other biallelic markers. (entry from Genetic Analysis Software)

Proper citation: CCREL (RRID:SCR_009142) Copy   

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http://www.math.mtu.edu/~shuzhang/software.html

Software application for testing association using tightly linked markers in nuclear pedigrees (entry from Genetic Analysis Software)

Proper citation: HS-TDT (RRID:SCR_009240) Copy   

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http://research.nhgri.nih.gov/ROMPrev/

Software tool for testing for association between polymorphisms and quantitative traits, as well as estimating trait heritability and locus-specific heritability using family data. (entry from Genetic Analysis Software)

Proper citation: ROMPREV (RRID:SCR_009361) Copy   

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http://www.jurgott.org/linkage/simulate.html

Software program to simulate genotypes in family members for a map of linked markers unlinked to a given affection status locus. the output is ready for analysis with UNKNOWN, ISIM, LSIM, or MSIM of the SLINK package. (entry from Genetic Analysis Software)

Proper citation: SIMULATE (RRID:SCR_009391) Copy   

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http://www.unc.edu/~yunmli/MaCH-Admix/

A genotype imputation software that is an extension to MaCH for faster and more flexible imputaiton, especially in admixed populations. It has incorporated a novel piecewise reference selection method to create reference panels tailored for target individual(s). This reference selection method generates better imputation quality in shorter running time. MaCH-Admix also separates model parameter estimation from imputation. The separation allows users to perform imputation with standard reference panels + pre-calibrated parameters in a data independent fashion. Alternatively, if one works with study-specific reference panels, or isolated target population, one has the option to simultaneously estimate these model parameters while performing imputation. MaCH-Admix has included many other useful options and supports VCF input files. All existing MaCH documentation applies to MaCH-Admix.

Proper citation: MaCH-Admix (RRID:SCR_009598) Copy   

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http://www.openbioinformatics.org/annovar/

An efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes (including human genome hg18, hg19, as well as mouse, worm, fly, yeast and many others). Given a list of variants with chromosome, start position, end position, reference nucleotide and observed nucleotides, ANNOVAR can perform: 1. gene-based annotation. 2. region-based annotation. 3. filter-based annotation. 4. other functionalities. (entry from Genetic Analysis Software)

Proper citation: ANNOVAR (RRID:SCR_012821) Copy   

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http://cuke.hort.ncsu.edu/cucurbit/wehner/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. SAS software program to estimate genetic effects and heritabilities of quantitative traits in breeding populations consisting of six related generations (entry from Genetic Analysis Software)

Proper citation: SASQUANT (RRID:SCR_013122) Copy   

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http://www.aps.uoguelph.ca/~msargol/qmsim/

Software application designed to simulate a wide range of genetic architectures and population structures in livestock. Large scale genotyping data and complex pedigrees can be efficiently simulated. QMSim is a family based simulator, which can also take into account predefined evolutionary features, such as LD, mutation, bottlenecks and expansions. The simulation is basically carried out in two steps: In the first step, a historical population is simulated to establish mutation-drift equilibrium and, in the second step, recent population structures are generated, which can be complex. QMSim allows for a wide range of parameters to be incorporated in the simulation models in order to produce appropriate simulated data. (entry from Genetic Analysis Software)

Proper citation: QMSIM (RRID:SCR_013123) Copy   

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https://github.com/Gregor-Mendel-Institute/poolhap

Software tool for inferring haplotypes from pooled sequencing. Enables to infer strain numbers and haplotype frequencies in silico from sequences of pooled samples.

Proper citation: PoolHap (RRID:SCR_012129) Copy   

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http://www.tassdb.info/

TassDB stores extensive data about alternative splice events at GYNGYN donors and NAGNAG acceptors. Currently, 114,554 tandem splice sites of eight species are contained in the database, 5,209 of which have EST/mRNA evidence for alternative splicing. Users can search by Transcript Accession Number and Gene Symbol, SQL Query, and Tandem Donor/Tandem Acceptor pairs.

Proper citation: TAndem Splice Site DataBase (RRID:SCR_007961) Copy   

•   Source: SciCrunch Registry

http://sisyphus.mrc-cpe.cam.ac.uk

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. A collection of manually curated protein structural alignments and their interrelationships. Each multiple alignment within the SISYPHUS database consists of structurally similar regions common to a group of proteins. These regions range from oligomeric biological units, or individual domains to fragments of different size representing either internal structural repeats or motifs common to structurally distinct proteins. The SISYPHUS multiple alignments are displayed with SPICE, a browser that provides an integrated view of protein sequences, structures and their annotations.

Proper citation: SISYPHUS (RRID:SCR_007930) Copy   

•   Source: SciCrunch Registry

http://silkworm.genomics.org.cn/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 20,2019.A database of integrated genome resources for the silkworm, Bombyx mori. This database provides access to not only genomic data including functional annotation of genes, gene products and chromosomal mapping, but also extensive biological information such as microarray expression data, ESTs and corresponding references. SilkDB will be useful for the silkworm research community as well as comparative genomics. Recently, an international collaboration has been launched to assemble a complete silkworm genome sequence, which is based on the 6� and 3� draft genome sequences created by Chinese group and Japanese group in 2004 (Mita et al., 2004; Xia et al., 2004), respectively. The genome assembly quality has been greatly improved. Base on a high density SNP genetic map, over 80% of genome sequence could be mapped on 28 chromosomes of the silkworm. The first version of SilkDB was released in 2004. Since that time, the silkworm has become a focus in insect research community and the study of silkworm has been greatly accelerated. Now, we are happy to announce the release of a new version of SilkDB, which updated all of the data, added new information of genome sequence and genes, and provides new tools to facilitate use of the genome database.

Proper citation: SilkDB (RRID:SCR_007926) Copy   

•   Source: SciCrunch Registry

http://www.bioinformatics2.wsu.edu/cgi-bin/Athena/cgi/home.pl

Athena is a web-based application that warehouses disparate datatypes related to the control of gene expression. Athena provides several features to enable exploration of the regulatory mechanisms of Arabidopsis gene control. The first main tool we provide is visualization of promoter domains of selected genes. Database crossreference for these transcription factors is provided as well as a statistical test for enrichment of binding activity within the set of selected promoters. The data mining tools in Athena allow for selection of sets of genes based on two different factors. -Genes can be select by specifying a set of binding factors whose putative sites must be present within all of those genes'' promoter regions. -Alternatively, genes can be selected using Gene Ontology annotations. Both GO (Gene Ontology) Slim terms and Gene Ontology terms are available. One can select a set of genes by either choosing a union of the genes annotated by a selected set of Slim terms or Gene Ontology terms. The selected gene''s putative binding factors are listed, including enrichment data. Furthermore, enriched presence of Gene Ontology terms is given. The analysis suite provides both enhanced data mining tools for selecting genes as well as several data displays., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Athena (RRID:SCR_008110) Copy   

•   Source: SciCrunch Registry

http://andromeda.gsf.de/litminer

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The LitMiner software is a literature data-mining tool that facilitates the identification of major gene regulation key players related to a user-defined field of interest in PubMed abstracts. The prediction of gene-regulatory relationships is based on co-occurrence analysis of key terms within the abstracts. LitMiner predicts relationships between key terms from the biomedical domain in four categories (genes, chemical compounds, diseases and tissues). The usefulness of the LitMiner system has been demonstrated recently in a study that reconstructed disease-related regulatory networks by promoter modeling that was initiated by a LitMiner generated primary gene list. To overcome the limitations and to verify and improve the data, we developed WikiGene, a Wiki-based curation tool that allows revision of the data by expert users over the Internet. It is based on the annotation of key terms in article abstracts followed by statistical co-citation analysis of annotated key terms in order to predict relationships. Key terms belonging to four different categories are used for the annotation process: -Genes: Names of genes and gene products. Gene name recognition is based on Ensembl . Synonyms and aliases are resolved. -Chemical Compounds: Names of chemical compounds and their respective aliases. -Diseases and Phenotypes: Names of diseases and phenotypes -Tissues and Organs: Names of tissues and organs LitMiner uses a database of disease and phenotype terms for literature annotation. Currently, there are 2225 diseases or phenotypes, 801 tissues and organs, and 10477 compounds in the database.

Proper citation: LitMiner (RRID:SCR_008200) Copy   

•   Source: SciCrunch Registry