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https://cran.r-project.org/web/packages/ibdreg/index.html

Software package in S-PLUS and R to test genetic linkage with covariates by regression methods with response IBD sharing for relative pairs. Account for correlations of IBD statistics and covariates for relative pairs within the same pedigree. (entry from Genetic Analysis Software)

Proper citation: IBDREG (RRID:SCR_013127) Copy   

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https://www.jax.org/news-and-insights/2013/february/komp2-mice-phenotyping-and-availability

Knockout Mouse Phenotyping Project, JAX information about their contributions to KOMP2 project. Project to generate and phenotype single gene KO mouse strains from KOMP ES cell lines. Strains are phenotyped using protocols in pipeline designed by International Mouse Phenotyping Consortium. There are three NIH-funded phenotyping centers in United States: JAX, BaSH Consortium (Baylor College of Medicine, the Wellcome Trust Sanger Institute and MRC Harwell), and the DTCC Consortium (University of California at Davis, the Toronto Center for Phenogenomics, Children’s Hospital Oakland Research Institute (CHORI) and Charles River ).

Proper citation: KOMP2 (RRID:SCR_017528) Copy   

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http://www.dkfz.de/en/epidemiologie-krebserkrankungen/software/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software program that performs estimation of power and sample sizes required to detect genetic and environmental main, as well as gene-environment interaction (GxE) effects in indirect matched case-control studies (1:1 matching). When the hypothesis of GxE is tested, power/sample size will be estimated for the detection of GxE, as well as for the detection of genetic and environmental marginal effects. Furthermore, power estimation is implemented for the joint test of genetic marginal and GxE effects (Kraft P et al., 2007). Power and sample size estimations are based on Gauderman''s (2002) asymptotic approach for power and sample size estimations in direct studies of GxE. Hardy-Weinberg equilibrium and independence of genotypes and environmental exposures in the population are assumed. The estimates are based on genotypic codes (G=1 (G=0) for individuals who carry a (non-) risk genotype), which depend on the mode of inheritance (dominant, recessive, or multiplicative). A conditional logistic regression approach is used, which employs a likelihood-ratio test with respect to a biallelic candidate SNP, a binary environmental factor (E=1 (E=0) in (un)exposed individuals), and the interaction between these components. (entry from Genetic Analysis Software)

Proper citation: PIAGE (RRID:SCR_013124) Copy   

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http://www-sequence.stanford.edu/group/candida/

The Stanford Genome Technology Center began a whole genome shotgun sequencing of strain SC5314 of Candida albicans. After reaching its original goal of 1.5X mean coverage of the haploid genome (16Mb) in summer, 1998, Stanford was awarded a supplemental grant to continue sequencing up to a coverage of 10X, performing as much assembly of the sequence as possible, using recognizable genes as nucleation points. Candida albicans is one of the most commonly encountered human pathogens, causing a wide variety of infections ranging from mucosal infections in generally healthy persons to life-threatening systemic infections in individuals with impaired immunity. Oral and esophogeal Candida infections are frequently seen in AIDS patients. Few classes of drugs are effective against these fungal infections, and all of them have limitations with regard to efficacy and side-effects.

Proper citation: Sequencing of Candida Albicans (RRID:SCR_013437) Copy   

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https://github.com/lufuhao/Gsnap2Augustus

Software tool to generate hints for Augustus in ab initio gene prediction using 2 step mapping by Gsnap.

Proper citation: Gsnap2Augustus (RRID:SCR_017555) Copy   

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http://www.plantcyc.org/

Collaborative project to bring together biochemical pathway databases and research communities focused on plant metabolism. Used to build broad network of plant metabolic pathway databases. Central feature of PMN is PlantCyc, comprehensive plant biochemical pathway database, containing curated information from literature and computational analyses about genes, enzymes, compounds, reactions, and pathways involved in primary and secondary metabolism.

Proper citation: Plant Metabolic Network (RRID:SCR_002888) Copy   

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https://picrust.github.io/picrust/

Software package to predict metagenome functional content from marker gene (e.g., 16S rRNA) surveys and full genomes. Used to predict which gene families are present and then combines gene families to estimate the composite metagenome.

Proper citation: PICRUSt (RRID:SCR_016855) Copy   

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http://rp-www.cs.usyd.edu.au/~yangpy/software/MFGE.html

A hybrid software system for feature selection and sample classification of high-dimensional datasets. It is designed for microarray but can be applied to any other high-dimensional datasets. It uses multiple filters to produce a normalized score for each feature. The score is an indication of the usefulness of each feature. It is then translated into a frequency map with more useful features receive a higher frequency in the map.

Proper citation: MF-GE (RRID:SCR_003509) Copy   

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http://bc02.iis.sinica.edu.tw/gobu/manual/index.html

Gene Ontology Browsing Utility (GOBU) (GOBU) is a Java-based software program for integrating biological annotation catalogs under an extendable software architecture. Users may interact with the Gene Ontology and user-defined hierarchy data of genes, and then use its plugins to (and not limited to) (1) browse the GO hierarchy with user defined data, (2) browse GO-oriented expression levels in the user data, (3) compute GO enrichment, and/or (4) customize data reporting. A set of classes and utility functions has been established so that a customized program can be made as a plugin or a command-line tool that programmically manipulate the Gene Ontology and specified user data. See the source code repository for examples. Reference Lin WD, Chen YC, Ho JM, Hsiao CD. GOBU: Toward an Integration Interface for Biological Objects. Journal of Information Science and Engineering. 2006 22(1):19-29. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Gene Ontology Browsing Utility (GOBU) (RRID:SCR_005662) Copy   

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http://www.biomed.org

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. This laboratory facilities contain core research space for monoclonal antibody production, oligonucleotide and peptide synthesis, gene cloning, DNA sequencing, high performance liquid chromatography, tissue culture, positron emission tomography, magnetic resonance spectroscopy and electron microscopy.

Proper citation: The Biomedical Research Foundation - Current Research (RRID:SCR_001564) Copy   

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https://www.hgsc.bcm.edu/content/sea-urchin-genome-project

Provides informationa about Genome of California Purple Sea Urchin, one species (Strongylocentrotus purpuratus) of which has been sequenced and annotated by Sea Urchin Genome Sequencing Consortium led by HGSC. Reports sequence and analysis of genome of sea urchin Strongylocentrotus purpuratus, a model for developmental and systems biology.

Proper citation: Sea Urchin Genome Project (RRID:SCR_001735) Copy   

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http://www-genome.stanford.edu/

This resource hyperlinks to systematic analysis projects, resources, laboratories, and departments at Stanford University.

Proper citation: Stanford Genomic Resourses (RRID:SCR_001874) Copy   

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http://www.oege.org/

Portal for researchers to locate information relevant to interpretation and follow-up of human genetic epidemiological discoveries, including: a range of population and case and family genetic epidemiological studies, relevant gene and sequence databases, genetic variation databases, trait measurement, resource labs, journals, software, general information, disease genes and genetic diversity.

Proper citation: Online Encyclopedia for Genetic Epidemiology studies (RRID:SCR_001825) Copy   

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http://bioafrica.mrc.ac.za/index.html

The BioAfrica HIV-1 Proteomics Resource is a website that contains detailed information about the HIV-1 proteome and protease cleavage sites, as well as data-mining tools that can be used to manipulate and query protein sequence data, a BLAST tool for initiating structural analyses of HIV-1 proteins, and a proteomics tools directory. HIV Proteomics Resource contains information about each HIV-1 gene product in regard to expression, post-transcriptional / post-translational modifications, localization, functional activities, and potential interactions with viral and host macromolecules. The Proteome section contains extensive data on each of 19 HIV-1 proteins, including their functional properties, a sample analysis of HIV-1HXB2, structural models and links to other online resources. The HIV-1 Protease Cleavage Sites section provides information on the position, subtype variation and genetic evolution of Gag, Gag-Pol and Nef cleavage sites.

Proper citation: BioAfrica HIV Informatics in Africa (RRID:SCR_002295) Copy   

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http://www.well.ox.ac.uk/happy/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software package for Multipoint QTL Mapping in Genetically Heterogeneous Animals (entry from Genetic Analysis Software) The method is implemented in a C-program and there is now an R version of HAPPY. You can run HAPPY remotely from their web server using your own data (or try it out on the data provided for download).

Proper citation: Happy (RRID:SCR_001395) Copy   

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https://www.hgmd.cf.ac.uk/ac/introduction.php?lang=english

Curated database of known (published) gene lesions responsible for human inherited disease.

Proper citation: Human Gene Mutation Database (RRID:SCR_001621) Copy   

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http://www.gensat.org/retina.jsp

Collection of images from cell type-specific protein expression in retina using BAC transgenic mice. Images from cell type-specific protein expression in retina using BAC transgenic mice from GENSAT project.

Proper citation: Retina Project (RRID:SCR_002884) Copy   

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http://www.rhesusbase.org/drugDisc/CAM.jsp

OKCAM (Ontology-based Knowledgebase for Cell Adhesion Molecules) is an online resource for human genes known or predicted to be related to the processes of cell adhesion. These genes include members of the cadherin, immunoglobulin/FibronectinIII (IgFn), integrin, neurexin, neuroligin, and catenin families. Totally 496 human CAM genes were compiled and annotated. We have mapped these genes onto a novel cell adhesion molecule ontology (CAMO) that provides a hierarchical description of cell adhesion molecules and their functions. It is intended to provide a means to facilitate better and better understanding of the global and specific properties of CAMs through their genomic features, regulatory modes, expression patterns and disease associations become clearer. You may browse by CAM ontology, Chromosomes and Full Gene list.

Proper citation: OKCAM: Ontology-based Knowledgebase for Cell Adhesion Molecules (RRID:SCR_010696) Copy   

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http://wpicr.wpic.pitt.edu/WPICCompGen/genomic_control/genomic_control.htm

Software application where GC implements the genomic control models. GCF implements the basic Genomic Control approach, but adjusts the p-values for uncertainty in the estimated effect of substructure. This approach is preferable if a large number of tests will be evaluated because it provides a more accurrate assessment of the significance level for small p-values. (entry from Genetic Analysis Software)

Proper citation: GC/GCF (RRID:SCR_009075) Copy   

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http://wpicr.wpic.pitt.edu/WPICCompGen/newcovibd/covibd.htm

Software application that refines linkage analysis of affected sibpairs by considering attributes or environmental exposures thought to affect disease liability. This refinement utilizes a mixture model in which a disease mutation segregates in only a fraction of the sibships, with the rest of the sibships unlinked. Covariate information is used to predict membership within the two groups corresponding to the linked and unlinked sibships. The pre-clustering model uses covariate information to first form two probabilistic clusters and then tests for excess IBD-sharing in the clusters. The Cov-IBD model determines probabilistic group membership by joint consideration of covariate and IBD values. (entry from Genetic Analysis Software)

Proper citation: COVIBD (RRID:SCR_009155) Copy   

•   Source: SciCrunch Registry