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http://www.qgene.org/

A free, open-source, computationally efficient Java program for comparative analyses of QTL mapping data and population simulation that runs on any computer operating system. (entry from Genetic Analysis Software) It is written with a plug-in architecture for ready extensibility. The software accommodates line-cross mating designs consisting of any arbitrary sequence of selfing, backcrossing, intercrossing and haploid-doubling steps that includes map, population, and trait simulators; and is scriptable. Source code is available on request.

Proper citation: QGene (RRID:SCR_003209) Copy   

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http://www.alz.org/research/funding/alzheimers_research_roundtable.asp

A consortium aiming to facilitate the development and implementation of new treatments for Alzheimer's disease by collectively addressing obstacles to research and development, clinical care and public health education. The Roundtable convenes twice each year for a two-day presentation and discussion of specific topics within Alzheimer's research. Topics are selected from a list proposed and voted on by members. Roundtable members explore a broad range of Alzheimer's science topics, including: * New data and technologies that may improve the diagnosis of Alzheimer's disease, especially in its earliest and mildest stages. * Neuropsychological testing, genetic factors, and biochemical and neuroimaging biomarkers that could contribute to an earlier and more accurate Alzheimer's diagnosis. * Lessons learned about clinical trial design that may help shape future clinical trials of drugs aimed at slowing or stopping the progression of Alzheimer's. * The pros and cons of various scales as outcomes measures of clinical trials. The outputs of Roundtable meetings are published as articles in the Alzheimer's Association's journal, Alzheimer's & Dementia. The Research Roundtable also sponsors Alzheimer's Association grants. The chosen project is named Research Roundtable Sponsored Grant and the principal investigator of the project is invited to give a progress report at a Roundtable meeting.

Proper citation: Alzheimers Association Research Roundtable (RRID:SCR_004007) Copy   

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http://sandberg.cmb.ki.se/media/data/rnaseq/rpkmforgenes.py

Python script which calculates gene expression for RNA-Sequencing data. It analyzes files in formats such as BED, BAM, and SAM to output data about RNA.

Proper citation: rpkmforgenes.py (RRID:SCR_014938) Copy   

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http://wwwn.cdc.gov/dls/genetics/rmmaterials/default.aspx

The goal of the Genetic Testing Reference Materials Coordination Program (GeT-RM) is to coordinate a self-sustaining community process to improve the availability of appropriate and characterized reference materials for: Quality control (QC), Proficiency testing (PT), Test development & validation, Research. The purpose of this program is: - To help the genetic testing community obtain appropriate and characterized reference materials - To facilitate and coordinate information exchange between users and providers of QC and reference materials - To coordinate efforts for contribution, development, characterization and distribution of reference materials for genetic testing Get-RM provides information about cell lines, DNA, and other kinds of materials that could be used as reference materials for molecular genetic testing. Some of these materials have been characterized by the GeT-RM program and can be divided into three categories: - Genetic Inherited Disease & Pharmacogenetics This section includes information about cell lines, DNA, and other samples that can be used as reference materials for various inherited diseases (including cystic fibrosis, fragile X, Huntington disease, and Ashkenazi Jewish-related diseases), pharmacogenetic loci, and biochemical genetics. The GeT-RM program has confirmed the genotype of many of the genomic DNA samples through testing in multiple clinical genetic laboratories. - Molecular Oncology This section includes information about commercially available cell lines, DNA, and other kinds of materials that could be used as reference materials for various types of cancers, including leukemia/lymphoma and solid tumors. - Infectious Disease This section includes information about commercially available cell lines, DNA, and other kinds of materials that could be used as reference materials for various infectious disease pathogens including viruses, bacteria, and protozoa.

Proper citation: Center for Disease Control and Prevention: Genetic Testing Reference Materials Coordination Program (RRID:SCR_013029) Copy   

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http://www.ornl.gov/sci/techresources/Human_Genome/home.shtml

This resource gives information about the U.S. Human Genome Project, which was was a 13-year effort to to discover all the estimated 20,000-25,000 human genes and make them accessible for further biological study. The primary project goals were to: - identify all the approximately 20,000-25,000 genes in human DNA, - determine the sequences of the 3 billion chemical base pairs that make up human DNA, - store this information in databases, - improve tools for data analysis, - transfer related technologies to the private sector, and - address the ethical, legal, and social issues (ELSI) that may arise from the project. To help achieve these goals, researchers also studied the genetic makeup of several nonhuman organisms. These include the common human gut bacterium Escherichia coli, the fruit fly, and the laboratory mouse. These parallel studies helped to develop technology and interpret human gene function. Sponsors: The DOE Human Genome Program and the NIH National Human Genome Research Institute (NHGRI) together sponsored the U.S. Human Genome Project.

Proper citation: Human Genome Project Information (RRID:SCR_013028) Copy   

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 4th,2023. Listing of computer software for the gene mapping community on the following topics: genetic linkage analysis for human pedigree data, QTL analysis for animal/plant breeding data, genetic marker ordering, genetic association analysis, haplotype construction, pedigree drawing, and population genetics. The inclusion of a program should not be interpreted as an endorsement to that program from us. In the last few years, new technology produces new types of genetic data, and the scope of genetic analyses change dramatically. It is no longer obvious whether a program should be included or excluded from this list. Topics such as next-generation-sequencing (NGS), gene expression, genomics annotation, etc. can all be relevant to a genetic study, yet be specialized topics by themselves. Though programs on variance calling from NSG can be in, those can sequence alignment might be out; programs on eQTL can be in, those on differential expression might be out. This page was created by Dr. Wentian Li, when he was at Columbia University (1995-1996). It was later moved to Rockefeller University (1996-2002), and now takes its new home at North Shore LIJ Research Institute (2002-now). The present copy is maintained by Jurg Ott as a single file. More than 240 programs have been listed by December 2004, more than 350 programs by August 2005, close to 400 programs by December 2006, and close to 480 programs by November 2008, and over 600 programs by October 2012. A version of the searchable database was developed by Zhiliang Hu of Iowa State University, and a recent round of updating was assisted by Wei JIANG of Harbin Medical School. Some earlier software can be downloaded from EBI: ftp://ftp.ebi.ac.uk/pub/software/linkage_and_mapping/ (Linkage and Mapping Software Repository), and http://genamics.com/software/index.htm may contain archived copy of some programs.

Proper citation: Genetic Analysis Software (RRID:SCR_013155) 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 simultaneously estimates a trait-locus position and its genetic effects for affected relative pairs (ARP) by one of two methods. Either allow a different trait-locus effect for each ARP type, or constrain the trait-locus effects according to the marginal effect of a single susceptibility locus. We include a goodness of fit statistic for the constrained model. (entry from Genetic Analysis Software)

Proper citation: ARP.GEE (RRID:SCR_013134) Copy   

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http://genetics.bwh.harvard.edu/pph2/

Software tool which predicts possible impact of amino acid substitution on structure and function of human protein using straightforward physical and comparative considerations. PolyPhen-2 is new development of PolyPhen tool for annotating coding nonsynonymous SNPs.

Proper citation: PolyPhen: Polymorphism Phenotyping (RRID:SCR_013189) Copy   

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http://sift.bii.a-star.edu.sg/

Data analysis service to predict whether an amino acid substitution affects protein function based on sequence homology and the physical properties of amino acids. SIFT can be applied to naturally occurring nonsynonymous polymorphisms and laboratory-induced missense mutations. (entry from Genetic Analysis Software) Web service is also available.

Proper citation: SIFT (RRID:SCR_012813) Copy   

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 1,2023. eQTL Explorer was developed as a computational resource to visualize and explore data from combined genome-wide expression and linkage studies is essential for the development of testable hypotheses. This visualization tool stores expression profiles, linkage data and information from external sources in a relational database and enables simultaneous visualization and intuitive interpretation of the combined data via a Java graphical interface. eQTL Explorer also provides a new and powerful tool to interrogate these very large and complex datasets. eQTLexplorer allows users to mine and understand data from a repository of genetical genomics experiments. It will graphically display eQTL information based on a certain number of selection criteria, including: tissue type, p-value, cis/trans, probeset Affymetrix id and PQTL type. Sponsors: This work was funded by the MRC Clinical Sciences Centre and the Wellcome Trust programme for Cardiovascular Functional Genomics.

Proper citation: eQTL Visualization Tool (RRID:SCR_013413) Copy   

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http://depts.washington.edu/adrcweb/

Research center investigating the basic mechanisms underlying the development of Alzheimer's disease and related disorders, directing particular attention to biomarkers and experimental new treatments. They also continue to search for genetic risk factors underlying Alzheimer's disease (AD). Their main priorities are to find causes, effective treatments, and prevention strategies. Their investigators also are partnering with other Alzheimer's Centers across the country to evaluate promising new medications and other treatments for AD. The ultimate goal of their basic and clinical studies is to improve patient care and function, and improve the quality of life for both the patient and the caregiver. ADRC Cores: * Administration * Clinical Core * Satellite Core * Data Management & Biostatistics * Neuropathology Core * Education & Information Transfer * Genetics

Proper citation: University of Washington Alzheimers Disease Research Center (RRID:SCR_008814) Copy   

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http://www.allelix.net

THIS RESOURCE IS NO LONGER IN SERVICE, documented on September 23, 2013. Software application / data analysis service where one can enter the alleles of commonly used STR by clicking the mouse. The algorithm calculates the paternity index and the Essen-Moeller probability of kinship for the deficiency- and the trio case. Everybody can use the network-software online after registering. The usage on the internet is free. Academic users can ask me to unlock an option to display the details (formulas/frequencies etc.) and to have an export-funktion to MS Word. The program is in German and (non-professional) English. An expansion to other languages is easy, if somebody helps us with the translation. For those who are interested to have the software running on their own intranet (for database security reasons) an individual agreement can be found. (entry from Genetic Analysis Software) (German version is: http://www.allelix.de)

Proper citation: ALLELIX (RRID:SCR_009115) Copy   

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https://gmod.org/wiki/CMap.1

Web-based tool that allows users to view comparisons of genetic and physical maps. The package also includes tools for curating map data. (entry from Genetic Analysis Software)

Proper citation: CMAP (RRID:SCR_009034) Copy   

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http://rgd.mcw.edu

Database for genetic, genomic, phenotype, and disease data generated from rat research. Centralized database that collects, manages, and distributes data generated from rat genetic and genomic research and makes these data available to scientific community. Curation of mapped positions for quantitative trait loci, known mutations and other phenotypic data is provided. Facilitates investigators research efforts by providing tools to search, mine, and analyze this data. Strain reports include description of strain origin, disease, phenotype, genetics, immunology, behavior with links to related genes, QTLs, sub-strains, and strain sources.

Proper citation: Rat Genome Database (RGD) (RRID:SCR_006444) Copy   

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http://www.mirecc.va.gov/visn6/

The VISN 6 MIRECC is organized as a translational medicine multi-site center focused on post deployment mental health issues. The overarching goals are improving clinical assessment and treatment and development of novel interventions through basic and clinical research. This MIRECC aims: (1) To determine whether early intervention in post-deployment mental health is effective in forestalling the development or decreasing the severity of post-deployment mental illness, (2) To determine what neuroimaging, genetic, neurocognitive, or other characteristics predict the development of post-deployment mental illness, and (3) To assess the longitudinal course of post-deployment mental illness.

Proper citation: Mid-Atlantic (VISN 6) Mental Illness Research, Education and Clinical Center (RRID:SCR_008077) Copy   

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http://www.dnaftb.org/dnaftb/

An animated primer on the basics of DNA, genes, and heredity organized around three key concepts: Classical Genetics, Molecules of Genetics, and Genetic Organization and Control. The science behind each concept is explained by: animation, image gallery, video interviews, problem, biographies, and links.

Proper citation: DNA From The Beginning: AN Animated Primer on the Basics of DNA, Genes, and Heredity (RRID:SCR_008028) Copy   

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http://www.projects.roslin.ac.uk/cdiv/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. The objective of the project is the standardization of micro-satellite markers used within participating laboratories, use of DNA markers to define genetic diversity and to enable monitoring of breeds to promote conservation programs where required, and the determination of diversity present in rare and local breeds across Europe. The blood typing laboratories are now beginning to use micro-satellite markers as an alternative to serology for parentage verification, and are selecting a common set to be used from the several hundred micro-satellite markers available that cover the bovine genome, produced as part of the Bovine genome mapping project (See BovMaP). Work with micro-satellite markers has shown that they are valuable tools for examining genetic diversity and phylogeny in many species. However, for work carried out in different laboratories to be comparable, it is essential that the same markers are used. To maintain the compatibility of data generated by the various typing labs, it is essential that all laboratories adopt the same markers and typing protocols. It is therefore of paramount importance that the blood typing laboratories and research labs that are examining the genetic structure of the cattle populations adopt a common panel of the best micro-satellite markers available. Some pilot comparative work has been undertaken through the International Society for Animal Genetics, but so far this has only involved the blood typing laboratories. One objective of this project is to facilitate the comparison of the micro-satellite markers currently in use in the different types of laboratory and determine the efficiency of the markers available in revealing genetic differences within and among breeds. It will also be important to compare the use of markers in different laboratories to determine how robust they are and how easily results can be compared. From comparison of the markers, those that are most suitable will be selected to form a panel which will be recommended for pedigree validation and genetic surveys. Cattle are an important source of food in Europe, and intense selection has resulted in the development of specialized breeds. Selection for high-producing dairy cattle has been successful, but one associated drawback is that the cattle population, both in Europe and North America, has been skewed dramatically towards one breed, the Holstein/Friesian. So there has been a decline in the number of individuals of other breeds, and hence a general erosion of the genetic base of the cattle population. The progressive move towards the North American-type Holstein animals has also resulted in the requirement for high input/high output farming and intensive management schemes. The impact of this on the environment has been significant, e.g. pollution problems arising from the need for high nitrogen fertilizers to produce sufficient high quality fodder, and disposal problems associated with slurry waste. Poorer areas of the community have been unable to compete with such farming systems, and are more suited to low input/low output farming using traditional stock. It is however the future perspective that is of greatest concern. It is impossible to predict requirements for cattle production - quality, production type, management systems, etc. The ability to switch rapidly to alternative production will be dependent on the genetic base of the population available to selection programs. It is therefore essential to maintain the greatest genetic diversity possible in the cattle population. Whilst current farming practices are perceived to be both efficient and acceptable, the breeds less favored by commercial farmers will dwindle. It is therefore important that on an European scale efficient management of these breeds maintains the widest genetic base possible. This project aims to carry out a survey of the current genetic base of the European cattle population and to provide the tools to assist breeding programs to maintain a broad base. The blood typing laboratories are now beginning to use micro-satellite markers as an alternative to serology for parentage verification, and are selecting a common set to be used from the several hundred micro-satellite markers available that cover the bovine genome, produced as part of the Bovine genome mapping project. Early work to measure genetic diversity used blood groups to show differences between breeds and the diversity present. Unfortunately, the number of loci available are limited, with only the B system being sufficiently polymorphic to be really useful. However, since there is a wealth of information available from such typing, this information can be used to estimate changes in the genetic structure of cattle populations across Europe over the past twenty years. More recently mini-satellite probes have been used to generate ''genetic fingerprints'' which have been used to show differences between individuals. Such fingerprints have been used to estimate genetic diversity - the greater the number of bands revealed by the fingerprint being equated with greater diversity. This is valid within limits. The main disadvantage of the fingerprint approach is that the chromosomal location and number of loci being sampled, and so the proportion of the genome examined, is unknown. The allelic bands on the gel cannot be easily identified, so allele inheritance cannot be addressed making it impossible to trace ancestry. Through the EC funded BovMaP project, large numbers of highly polymorphic micro-satellite markers have become available, which are being mapped on the bovine genome. These markers are particularly suited to measuring genetic diversity, and markers can be selected to cover the entire genome.

Proper citation: CaDBase: Genetic diversity in cattle (RRID:SCR_008146) Copy   

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http://locus.jouy.inra.fr/cgi-bin/bovmap/intro.pl

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Database containing information on the cattle genome comprising loci list, phenes list, homology query, cattle maps, gene list, and chromosome homology. The objective of BovMap is to develop a set of anchored loci for the cattle genome map. In total, 58 clones were hybridized with chromosomes and identified loci on 22 of the 31 different bovine chromosomes. Three clones contained satellite DNA. Two or more markers were placed on 12 chromosomes. Sequencing of the microsatellites and flanking regions was performed directly from 43 cosmids, as previously reported. Primers were developed for 39 markers and used to describe the polymorphism associated with the corresponding loci. Users are also allowed to summit their own data for Bovmap. An integrated cytogenetic and meiotic map of the bovine genome has also been developed around the Bovmap database. One objective that Bovmap uses as the mapping strategy for the bovine genome uses large insert clones as a tool for physical mapping and as a source of highly polymorphic microsatellites for genetic typing.

Proper citation: BovMap Database (RRID:SCR_008145) Copy   

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https://www.bi.mpg.de/borst

Merger of the Max Planck Institute of Neurobiology and the Max Planck Institute of Ornithology and has been renamed to Circuits - Computation – Models. Department devoted to the study of how the brain computes to understand neural information processing at the level of individual neurons and small neural circuits.

Proper citation: Max Planck Institute for Biological Intelligence Circuits - Computation – Models (RRID:SCR_008048) Copy   

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http://www.scripps.edu/np/inia/index.html

Consortium set out to identify the molecular, cellular, and behavioral neuroadaptations that occur in the brain reward circuits associated with the extended amygdala and its connections. It is hypothesized that genetic differences and/or neuroadaptations in this circuitry are responsible for the individual differences in vulnerability to the excessive consumption of alcohol. Chronic exposure to alcohol results in neuroadaptive phenomena, including tolerance, sensitization, dependence, withdrawal, loss of control of drinking, and relapse that contribute to the development of excessive alcohol consumption. The INIA has the following goals: 1) To establish animal models to study specific neurobiological targets for vulnerability that lead to excessive consumption of alcohol at the molecular, cellular and neural circuit level of analysis, 2) To identify specific clusters of genes whose expression is regulated by alcohol and which are responsible for any given model of excessive alcohol consumption using gene expression arrays, differential display, mutagenesis directed at specific brain areas, and the development of new informatics tools to analyze and interpret gene expression, cellular circuitry and brain circuitry data with the use of transgenic and knockout approaches, and 3) To attract new and innovative investigators to the field of alcohol research by recruiting individuals for development of U01 grants and pilot projects and by developing online interactive capacity among INIA scientists and others, and by making the neuroinformatics integrated data sets accessible, searchable and interactive with other databases for all scientists interested in alcoholism research. The structure of INIA is envisioned as two domains, Dependence-induced drinking and Binge drinking, comprised of multiple U01 research grants. The flow of information within each domain moves from molecular, to cellular, to neurocircuitry levels of analysis. These U01s share information with the core facilities, which act as data depositories. The Administrative Core coordinates the flow of information among the Domains and Cores and disseminates the information back to the U01s. A Pilot Project program will identify exciting new areas for research and the continual recruitment of new investigators to the alcohol field. The INIA program is directed by an Administrative Core in close cooperation with the Animal Models, Gene Array and Neurocircuitry Cores via a Steering Committee and with the continual advice of the Scientific Advisory Committee.

Proper citation: Integrative Neuroscience Initiative on Alcoholism (RRID:SCR_008042) Copy   

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