Tools   Select Another Resource Report Type

http://www.nisc.nih.gov/projects/comp_seq.html

Generates data for use in developing and refining computational tools for comparing genomic sequence from multiple species. The NISC Comparative Sequencing Program's goal is to establish a data resource consisting of sequences for the same set of targeted genomic regions derived from multiple animal species. The broader program includes plans for a diverse set of analytical studies using the generated sequence and the publication of a series of papers describing the results of those analysis in peer-reviewed journals in a timely fashion. Experimentally, this project involves the shotgun sequencing of mapped BAC clones. For each BAC, an assembly is first performed when a sufficient number of sequence reads have been generated to provide full shotgun coverage of the clone. At that time, the assembled sequence is submitted to the HTGS division of GenBank. Subsequent refinements of the sequence, including the generation of higher-accuracy finished sequence, results in the updating of the sequence record in GenBank. By immediately submitting our BAC-derived sequences to GenBank, it makes their data available as a public service to allow colleagues to speed up their research, consistent with the now well-established routine of sequencing centers participating in the Human Genome Project. However, at the same time, it has made considerable investment in acquiring these mapping and sequence data, including sizable efforts of graduate students, postdoctoral fellows, and other trainees. Furthermore, in most cases, large data sets involving multiple BAC sequences from multiple species must first be generated, often taking many months to accumulate, before the planned analysis can be performed and the resulting papers written and submitted for publication.

Proper citation: Comparative Vertebrate Sequencing (RRID:SCR_008213) Copy   

•   Source: SciCrunch Registry

http://www.peroxisomedb.org/

The aim of the PEROXISOME database (PeroxisomeDB) is to gather, organize and integrate curated information on peroxisomal genes, their encoded proteins, their molecular function and metabolic pathway they belong to, and their related disorders. PeroxisomeDB contains the complete peroxisomal proteome of Homo sapiens (encoded by 85 genes) and Saccharomyces cerevisiae (encoded by 61 genes). Now, we have included 34 new organism genomes with the acquisition of 2426 new peroxisomal homolog proteins. PeroxisomeDB 2.0 integrates the peroxisomal metabolome of whole microbody family by the new incorporation of the glycosome proteomes of trypanosomatids and the glyoxysome proteome of Arabidopsis thaliana. The site also provides a Peroxisome Metabolome of peroxisomal genes and proteins, their molecular interactions and metabolic pathways, tools for comparative genomics, predictive tools. Sponsors: Preoxisome Database is funded by Institut de Gntique et deBiologie Molculaire et Cellulaire.

Proper citation: Peroxisome Database (RRID:SCR_008352) Copy   

•   Source: SciCrunch Registry

http://cgap.nci.nih.gov/Chromosomes/Mitelman

The web site includes genomic data for humans and mice, including transcript sequence, gene expression patterns, single-nucleotide polymorphisms, clone resources, and cytogenetic information. Descriptions of the methods and reagents used in deriving the CGAP datasets are also provided. An extensive suite of informatics tools facilitates queries and analysis of the CGAP data by the community. One of the newest features of the CGAP web site is an electronic version of the Mitelman Database of Chromosome Aberrations in Cancer. The data in the Mitelman Database is manually culled from the literature and subsequently organized into three distinct sub-databases, as follows: -The sub-database of cases contains the data that relates chromosomal aberrations to specific tumor characteristics in individual patient cases. It can be searched using either the Cases Quick Searcher or the Cases Full Searcher. -The sub-database of molecular biology and clinical associations contains no data from individual patient cases. Instead, the data is pulled from studies with distinct information about: -Molecular biology associations that relate chromosomal aberrations and tumor histologies to genomic sequence data, typically genes rearranged as a consequence of structural chromosome changes. -Clinical associations that relate chromosomal aberrations and/or gene rearrangements and tumor histologies to clinical variables, such as prognosis, tumor grade, and patient characteristics. It can be searched using the Molecular Biology and Clinical (MBC) Associations Searcher -The reference sub-database contains all the references culled from the literature i.e., the sum of the references from the cases and the molecular biology and clinical associations. It can be searched using the Reference Searcher. CGAP has developed six web search tools to help you analyze the information within the Mitelman Database: -The Cases Quick Searcher allows you to query the individual patient cases using the four major fields: aberration, breakpoint, morphology, and topography. -The Cases Full Searcher permits a more detailed search of the same individual patient cases as above, by including more cytogenetic field choices and adding search fields for patient characteristics and references. -The Molecular Biology Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to gene rearrangements as a consequence of cytogenetic aberrations. -The Clinical Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to clinical associations of cytogenetic aberrations and/or gene rearrangements. -The Recurrent Chromosome Aberrations Searcher provides a way to search for structural and numerical abnormalities that are recurrent, i.e., present in two or more cases with the same morphology and topography. -The Reference Searcher queries only the references themselves, i.e., the references from the individual cases and the molecular biology and clinical associations. Sponsors: This database is sponsored by the University of Lund, Sweden and have support from the Swedish Cancer Society and the Swedish Children''s Cancer Foundation

Proper citation: Mitelman Database of Chromosome Aberrations in Cancer (RRID:SCR_012877) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/

Community model organism database for laboratory mouse and authoritative source for phenotype and functional annotations of mouse genes. MGD includes complete catalog of mouse genes and genome features with integrated access to genetic, genomic and phenotypic information, all serving to further the use of the mouse as a model system for studying human biology and disease. MGD is a major component of the Mouse Genome Informatics.Contains standardized descriptions of mouse phenotypes, associations between mouse models and human genetic diseases, extensive integration of DNA and protein sequence data, normalized representation of genome and genome variant information. Data are obtained and integrated via manual curation of the biomedical literature, direct contributions from individual investigators and downloads from major informatics resource centers. MGD collaborates with the bioinformatics community on the development and use of biomedical ontologies such as the Gene Ontology (GO) and the Mammalian Phenotype (MP) Ontology.

Proper citation: Mouse Genome Database (RRID:SCR_012953) Copy   

•   Source: SciCrunch Registry

http://cello.life.nctu.edu.tw/

A subCELlular LOcalization predictor based on a multi-class support vector machine (SVM) classification system. CELLO uses 4 types of sequence coding schemes: the amino acid composition, the di-peptide composition, the partitioned amino acid composition and the sequence composition based on the physico-chemical properties of amino acids. They combine votes from these classifiers and use the jury votes to determine the final assignment.

Proper citation: CELLO (RRID:SCR_011968) Copy   

•   Source: SciCrunch Registry

http://ftp://morgan.med.utah.edu/pub/Mim

Software application using multipoint IBD method for partitioning genetic variance of quantitative traits to specific chromosome regions using data on nuclear families. (entry from Genetic Analysis Software)

Proper citation: Multipoint Identical-by-descent Method (RRID:SCR_004676) Copy   

•   Source: SciCrunch Registry

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

Software tool that allows scripting of simple modifications to pedigree files. (entry from Genetic Analysis Software)

Proper citation: PEDSCRIPT (RRID:SCR_004571) Copy   

•   Source: SciCrunch Registry

http://www.chg.duke.edu/software/pedplot.html

Pedigree Plotting Program for the Pedfile Format (entry from Genetic Analysis Software)

Proper citation: PEDPLOT (RRID:SCR_003843) Copy   

•   Source: SciCrunch Registry

http://www.homepages.ed.ac.uk/pmckeigu/hapmixmap/hapmixmap_manual.html

Software application for modelling extended haplotypes in genetic association studies, similar to the FASTPHASE program. (entry from Genetic Analysis Software)

Proper citation: HAPMIXMAP (RRID:SCR_006066) Copy   

•   Source: SciCrunch Registry

http://www2.ujf-grenoble.fr/leca/membres/manel.html

Software application for parentage inference using molecular data from diploid codominant markers (entry from Genetic Analysis Software)

Proper citation: PARENTE (RRID:SCR_004717) Copy   

•   Source: SciCrunch Registry

http://www.mds.qmw.ac.uk/statgen/dcurtis/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. A pedigree drawing program using LINKAGE data files (entry from Genetic Analysis Software)

Proper citation: PEDRAW/WPEDRAW (RRID:SCR_004797) Copy   

•   Source: SciCrunch Registry

http://biostatistics.mdanderson.org/SoftwareDownload/

Software application for power and sample-size calculations for the TDT and ASP tests under a wide variety of ascertainment schemes. Uses the flexible genetic model of McGinnis. Most calculations are exact rather than asymptotic. (entry from Genetic Analysis Software)

Proper citation: TDTASP (RRID:SCR_004943) Copy   

•   Source: SciCrunch Registry

http://genomics.med.upenn.edu/spielman/TDT.htm

Software program that provides separate results for TDT, S-TDT, and the combined (overall) test, as appropriate. (entry from Genetic Analysis Software)

Proper citation: TDT/S-TDT (RRID:SCR_005548) Copy   

•   Source: SciCrunch Registry

http://cgi.uc.edu/cgi-bin/kzhang/haploBlockFinder.cgi

Software package for haplotype block identification, visualization and htSNP selection. It can also compare the haplotype block structure with local LD pattern. The program can be either run as a web service, or standalone executables on local machine. (entry from Genetic Analysis Software)

Proper citation: HAPLOBLOCKFINDER (RRID:SCR_005844) Copy   

•   Source: SciCrunch Registry

http://courses.jax.org/2012/addiction.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. This course emphasizes genetic applications and approaches to drug addiction research through methodological instruction based on literature, data sets and informatics resources drawn from studies of addiction related phenotypes. The course includes plenary sessions on major progress in addiction genetics, and discussion sessions in which students present their work for discussion on applications of genetic methods. Students will leave the course able to design and interpret genetic and genomic studies of addiction as they relate to their specific research question, and will be able to make use of current bioinformatics resources to identify research resources and make use of public data sources in their own research.

Proper citation: Short Course on the Genetics of Addiction (RRID:SCR_005560) Copy   

•   Source: SciCrunch Registry

http://www.stats.ox.ac.uk/%7Emarchini/software.html

An R package that specifically focuses on statistical and population genetics methods. The motivation behind the package is to produce an easy to use interface to many of the commonly used methods and models used in statistical and population genetics and an alternative interface for some of the methodology produced by our group. (entry from Genetic Analysis Software)

Proper citation: POPGEN (RRID:SCR_007315) Copy   

•   Source: SciCrunch Registry

https://www.nugene.org/

Collects and stores genetic (DNA) samples along with associated healthcare information from patients of Northwestern-affiliated hospitals and clinics. This resource is available to scientists to conduct groundbreaking genetic research. The information and blood samples provided will be used by researchers to examine the role genes play in the development and treatment of common diseases. The NUgene Project seeks to increase the understanding of genetic mechanisms underlying common diseases, assist in the development of DNA-based technology for diagnosis and treatment of disease, and aid physicians and other healthcare providers in the application of genetics to the practice of medicine. NUgene participants are recruited throughout the Northwestern-affiliated healthcare community in order to create an ethnically and medically diverse population for research. Participants must be 18 years of age or older and receive their medical care from a Northwestern-affiliated provider, regardless of health status. Consenting individuals complete all aspects of enrollment in a single meeting with a research coordinator. The enrollment process includes the donation of a single sample of blood and the completion of a self-administered questionnaire. Participants also sign a consent form during this encounter. The NUgene Project is an interdisciplinary project that relies on the expertise of individuals working in a variety of fields, including science, medicine, clinical research, statistics, epidemiology, and computational biology. NUgene''s multidisciplinary approach has spurred collaborations within Northwestern-affiliated institutions and with other outside institutions. This collaboration of ideas is the future of genetics and genomic research., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NUgene Project (RRID:SCR_007426) Copy   

•   Source: SciCrunch Registry

http://www.stats.ox.ac.uk/~mcvean/LDhat/

Software package for the analysis of recombination rates from population genetic data (entry from Genetic Analysis Software)

Proper citation: LDHAT (RRID:SCR_006298) Copy   

•   Source: SciCrunch Registry

https://varscan.sourceforge.net/

Platform-independent, technology-independent software tool for identifying SNPs and indels in massively parallel sequencing of individual and pooled samples. Given data for a single sample, VarScan identifies and filters germline variants based on read counts, base quality, and allele frequency. Given data for a tumor-normal pair, VarScan also determines the somatic status of each variant (Germline, Somatic, or LOH) by comparing read counts between samples. (entry from Genetic Analysis Software).

Proper citation: VarScan (RRID:SCR_006849) Copy   

•   Source: SciCrunch Registry

The record is no longer available at this source.

Software application that is part of the LINKAGE auxiliary programs (entry from Genetic Analysis Software)

Proper citation: LSP (RRID:SCR_007059) Copy   

•   Source: SciCrunch Registry