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http://dlin.web.unc.edu/software/SCORE-Seq/

A command-line program for detecting disease associations with rare variants in sequencing studies. The mutation information is aggregated across multiple variant sites of a gene through a weighted linear combination and then related to disease phenotypes through appropriate regression models. The weights can be constant or dependent on allele frequencies and phenotypes. The association testing is based on score-type statistics. The allele-frequency threshold can be fixed or variable. Statistical significance can be assessed by using asymptotic normal approximation or resampling. The current release covers binary and continuous traits with arbitrary covariates under case-control and cross-sectional sampling. (entry from Genetic Analysis Software)

Proper citation: SCORE-SEQ (RRID:SCR_013121) 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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http://www.stat.washington.edu/thompson/Genepi/InSegT.shtml

Software application that constructs feasible haplotype configurations and the corresponding segregation types on pedigrees. the haplotype configuration minimizes recombinations on the pedigree. (entry from Genetic Analysis Software)

Proper citation: INSEGT (RRID:SCR_013126) Copy   

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http://www.nitrc.org/projects/se_linux/

Software tools optimized for performing univariate and multivariate imaging genetics analyses while providing practical correction strategies for multiple testing. The goal of this project is to merge two important research directions in modern science, genetics and neuroimaging. This entails combining modern statistical genetic methods and quantitative phenotyping performed with high dimensional neuroimaging modalities. So far, however, standard imaging tools are unable to deal with large-scale genetics data, and standard genetics tools, in turn, are unable to accommodate large size and binary format of the image data. Their focus is to create imaging genetics tools for classical genetic and epigenetic epidemiological analyses such as heritability, pleiotropy, quantitative trait loci (QTL) and genome-wide association (GWAS), gene expression, and methylation analyses optimized for traits derived from structural and functional brain imaging data

Proper citation: Solar Eclipse Imaging Genetics tools (RRID:SCR_009645) Copy   

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

Software application that is a GLF-based variant caller for next-generation sequencing data. It takes one/three/multiple GLF format genotype likelihood files as input and generates a VCF-format set of variant calls as output. (entry from Genetic Analysis Software)

Proper citation: GLFSINGLE/GLFTRIO/GLFMULTIPLES (RRID:SCR_013128) Copy   

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https://sourceforge.net/projects/ggsd/

Web-based, relational database driven data management software package for the management of large scale genetic studies. (entry from Genetic Analysis Software)

Proper citation: GGSD (RRID:SCR_013129) Copy   

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http://www.eurobiobank.org/en/partners/description/inncb_copy.htm#organisation

A biobank of human biological material and genetic information. It provides samples and information to researchers in order to identify new genes and clarify pathogenic mechanisms of diseases. The biobank offers biochemical and molecular diagnoses of genetic dystonias, Parkinson's disease and NBIA disorders, as well as storage of biological samples for external institutions.

Proper citation: Movement Disorders Biobank (RRID:SCR_010659) Copy   

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http://www.fruitfly.org

Database on the sequence of the euchromatic genome of Drosophila melanogaster In addition to genomic sequencing, the BDGP is 1) producing gene disruptions using P element-mediated mutagenesis on a scale unprecedented in metazoans; 2) characterizing the sequence and expression of cDNAs; and 3) developing informatics tools that support the experimental process, identify features of DNA sequence, and allow us to present up-to-date information about the annotated sequence to the research community. Resources * Universal Proteomics Resource: Search for clones for expression and tissue culture * Materials: Request genomic or cDNA clones, library filters or fly stocks * Download Sequence data sets and annotations in fasta or xml format by http or ftp * Publications: Browse or download BDGP papers * Methods: BDGP laboratory protocols and vector maps * Analysis Tools: Search sequences for CRMs, promoters, splice sites, and gene predictions * Apollo: Genome annotation viewer and editor September 15, 2009 Illumina RNA-Seq data from 30 developmental time points of D. melanogaster has been submitted to the Short Read Archive at NCBI as part of the modENCODE project. The data set currently contains 2.2 billion single-end and paired reads and over 201 billion base pairs.

Proper citation: Berkeley Drosophila Genome Project (RRID:SCR_013094) Copy   

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software application aiming at identifying haplotype blocks. The likelihood of the data is calculated minus the model complexity. The resulting blocks have very low diversity and the linkage disequilibrium with SNP's outside the blocks is low. (entry from Genetic Analysis Software)

Proper citation: ENTROPY BLOCKER (RRID:SCR_000123) Copy   

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http://www.sanger.ac.uk/cgi-bin/teams/team30/arnie

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 1,2023. Database that integrates the extracellular protein interaction network generated in our lab using AVEXIS technology with spatiotemporal expression patterns for all genes in the network. The tool allows users to browse the network by clicking on individual proteins, or by specifying the spatiotemporal parameters. Clicking on connector lines will allow users to compare stage-matched expression patterns for genes encoding interacting proteins. Additionally, users can rapidly search for their genes in the network using the BLAST server provided.

Proper citation: ARNIE (RRID:SCR_000514) Copy   

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http://lifespandb.sageweb.org/

Database that collects published lifespan data across multiple species. The entire database is available for download in various formats including XML, YAML and CSV.

Proper citation: Lifespan Observations Database (RRID:SCR_001609) Copy   

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http://www.flyprot.org/

Allows annotation of gene expression at all stages of development and tissue types (including sub cellular location) using standard Drosophila anatomy ontology. All methods of input use a controlled vocabulary to ensure data integrity.

Proper citation: Flannotator (RRID:SCR_001608) Copy   

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http://cddb.nhlbi.nih.gov/cddb/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. This database is intended to serve as a learning tool to obtain curated information for the design of microarray targets to scan collecting duct tissues (human, rat, mouse). The database focuses on regulatory and transporter proteins expressed in the collecting duct, but when collecting duct proteins are a member of a larger family of proteins, common additional members of the family are included even if they have not been demonstrated to be expressed in the collecting duct. An Internet-accessible database has been devised for major collecting duct proteins involved in transport and regulation of cellular processes. The individual proteins included in this database are those culled from literature searches and from previously published studies involving cDNA arrays and serial analysis of gene expression (SAGE). Design of microarray targets for the study of kidney collecting duct tissues is facilitated by the database, which includes links to curated base pair and amino acid sequence data, relevant literature, and related databases. Use of the database is illustrated by a search for water channel proteins, aquaporins, and by a subsequent search for vasopressin receptors. Links are shown to the literature and to sequence data for human, rat, and mouse, as well as to relevant web-based resources. Extension of the database is dynamic and is done through a maintenance interface. This permits creation of new categories, updating of existing entries, and addition of new ones. CDDB is a database that organizes lists of genes found in collecting duct tissues from three mammalian species: human, rat, and mouse. Proteins are divided into categories by family relationships and functional classification, and each category is assigned a section in the database. Each section includes links to the literature and to sequence information for genes, proteins, expressed sequence tags, and related information. The user can peruse a section or use a search engine at the bottom of the web page to search the database for a name or abbreviation or for a link to a sequence. Each entry in the database includes links to relevant papers in the kidney and collecting duct literature. It uses links to PubMed to generate MEDLINE searches for retrieval of references. In addition, each entry includes links to curated sequence data available in LocusLink. Individual links are made to sequence and protein data for human, rat, and mouse. Links are then added as curated sequences become available for proteins identified in the renal collecting duct and for proteins identified in kidney and similar in function or homologous to proteins identified in the collecting duct.

Proper citation: Collecting Duct Database (RRID:SCR_000759) Copy   

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http://cmbi.bjmu.edu.cn/mirsnp

Database of human SNPs in predicted miRNA-mRNA binding sites, based on information from dbSNP135 and mirBASE18. MirSNP is highly sensitive and covers most experiments confirmed SNPs that affect miRNA function. MirSNP may be combined with researchers' own GWAS or eQTL positive data sets to identify the putative miRNA-related SNPs from traits/diseases associated variants. They aim to update the MirSNP database as new versions of mirBASE and dbSNP database become available.

Proper citation: MirSNP (RRID:SCR_001629) 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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https://gtexportal.org/home/

Database and browser that provides a central resource to archive and display association between genetic variation and high-throughput molecular-level phenotypes. This effort originated with the NIH GTEx roadmap project: however the scope of this resource will be extended to include any available genotype/molecular phenotype datasets.

Proper citation: GTEx eQTL Browser (RRID:SCR_001618) Copy   

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http://magest.hgc.jp/

A database for maternal gene expression information for ascidia, colloquially known as sea squirts. Information available includes DNA sequences, expression patterns of ESTs, and cDNA data from uncleaved fertilized eggs. The goal is to utilize the database to understand molecular mechanisms of establishment of embryonic body plans of chordates and to understand evolution from invertebrates to vertebrates in the future.

Proper citation: MAboya Gene Expression Patterns and Sequence Tags (RRID:SCR_000763) Copy   

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https://fungi.ensembl.org/Neurospora_crassa/Info/Index

It's strategy involves Whole Genome Shotgun (WGS) sequencing, in which sequence from the entire genome is generated and reassembled. This method is standard for microbial genome sequencing, and has been successfully applied to Drosophila. Neurospora is an ideal candidate for this approach because of the low repeat content of the genome. Neurospora crassa Database has expanded the scope of its database by including a mitochondrial annotation, incorporating information from the Neurospora compendium, and assigning NCU numbers to tRNA and rRNAs. They have improved the annotation process to predict untranslated regions and to reduce the number of spurious predictions. As a result, version 3 contains 9,826 genes, 794 fewer than version 2. During the initial phase of a WGS project they sequence both ends of the 4 kb inserts from a plasmid library prepared using randomly sheared and sized-selected DNA. The shotgun reads are assembled by recognizing overlapping regions of sequence and making use of the knowledge of the orientation and distance of the paired reads from each plasmid. Obtaining deep sequence coverage though high levels of sequence redundancy assures that the majority of the genome is represented in the initial assembly and that the consensus sequence is of high quality. Their approach toward the initial assembly was conservative, meaning they would rather fail to join sequence contigs that might overlap each other than risk making false joins between two closely related but non-overlapping genomic regions. Hence, the initial assembly contains many sequence contigs and over time these contigs will increase in size and decrease in number as they are joined together. After shotgun sequencing and assembly there was a second phase of sequencing in which additional sequence was obtained from specific regions that were missing from the original assembly or are recognized to be of low quality in the consensus. The Neurospora crassa sequencing project reflects a close collaboration between the Broad Institute and the Neurospora research community. Principal investigators include Bruce Birren and Chad Nusbaum from the Broad Institute, Matt Sachs at the Oregon Graduate Institute of Science and Technology, Chuck Staben at the University of Kentucky and Jak Kinsey at the Fungal Genetics Stock Center at the University of Kansas Medical Center. In addition, we have a larger Advisory Board made up of a number of Neurospora researchers. Sponsors: They have been funded by the National Science Foundation to sequence the N. crassa genome and make the information publicly available.

Proper citation: Neurospora crassa Database (RRID:SCR_001372) Copy   

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http://umcecaruca01.extern.umcn.nl:8080/ecaruca/ecaruca.jsp

A database of cytogenetic and clinical information on rare chromosomal disorders, including microdeletions and microduplications. The database is meant to be easily accessible for all participants, to improve patient care and collaboration between genetic centers, and collect the results of research and clinical features. The acronym ECARUCA stands for "European Cytogeneticists Association Register of Unbalanced Chromosome Aberrations".

Proper citation: ECARUCA Project (RRID:SCR_000797) Copy   

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http://igenbio.com/

A web-based genome analysis platform that integrates proprietary functional genomic data, metabolic reconstructions, expression profiling, and biochemical and microbiological data with publicly available information. Focused on microbial genomics, it provides better and faster identification of gene function across all organisms. Building upon a comprehensive genomic database integrated with a collection of microbial metabolic and non-metabolic pathways and using proprietary algorithms, it assigns functions to genes, integrates genes into pathways, and identifies previously unknown or mischaracterized genes, cryptic pathways and gene products. . * Automated and manual annotation of genes and genomes * Analysis of metabolic and non-metabolic pathways to understand organism physiology * Comparison of multiple genomes to identify shared and unique features and SNPs * Functional analysis of gene expression microarray data * Data-mining for target gene discovery * In silico metabolic engineering and strain improvement

Proper citation: ERGO (RRID:SCR_001243) Copy   

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