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https://github.com/ZSI-Bio/bdg-sequila
Software tool for genomic intervals querying and processing built on top of Apache Spark. Elastic, fast and scalable SQL oriented solution for processing and querying genomic intervals.
Proper citation: SeQuiLa (RRID:SCR_017220) Copy
https://www.bmh.manchester.ac.uk/research/facilities/bioinformatics/
Core provides assistance in integrative analysis of genomic datasets to support faculty.
Proper citation: University of Manchester Bioinformatics Core Facility (RRID:SCR_017171) Copy
Consortium to bring together clinicians, pathologists, researchers, and biotech innovators to create scalable network of stakeholders interested in helping patients with glomerular kidney disease. Makes collective expertise of its members available for discussion of individual cases, provides infrastructure for biomarker studies, enables genomic research, and facilitates clinical trials.
Proper citation: Glomerular Disease Study & Trial Consortium (RRID:SCR_017264) Copy
Portal to facilitate integration and computing on and across large datasets generated by NHGRI programs, as well as initiatives funded by National Institutes of Health or by other agencies that support human genomics research. Resource for genomic scientific community, that leverages cloud based infrastructure for democratizing genomic data access, sharing and computing across large genomic, and genomic related data sets. Component of federated data ecosystem, and is expected to collaborate and integrate with other genomic data resources through adoption of FAIR (Findable, Accessible, Interoperable, Reusable) principles, as their specifications emerge from scientific community. Will provide collaborative environment, where datasets and analysis workflows can be shared within consortium and be prepared for public release to broad scientific community through AnVIL user interfaces.
Proper citation: Analysis, Visualization, and Informatics Lab-space (AnVIL) (RRID:SCR_017469) Copy
https://bioconductor.org/packages/TCGAbiolinks/
Software R Bioconductor package for integrative analysis with TCGA data.TCGAbiolinks is able to access National Cancer Institute Genomic Data Commons thorough its GDC Application Programming Interface to search, download and prepare relevant data for analysis in R.
Proper citation: TCGAbiolinks (RRID:SCR_017683) Copy
https://github.com/esctrionsit/snphub
Web Shiny-based server framework for retrieving, analyzing and visualizing large genomic variations data.
Proper citation: SnpHub (RRID:SCR_018177) Copy
http://www.imperial.ac.uk/research/animallectins
Resource presents information about animal lectins involved in various sugar recognition processes.
Proper citation: genomics resource for animal lectins (RRID:SCR_018122) Copy
Software application as an integrated web resource of marmoset biological data. Used to find genomic, expression and alternative splicing data to facilitate the study of animal model for neuropsychiatric and social behavior research and to support biological analyses such as functional (ontology) enrichment analysis and protein-protein-network.
Proper citation: CajaDB (RRID:SCR_016506) Copy
https://genome.jgi.doe.gov/programs/fungi/1000fungalgenomes.jsf
Web application to provide genomic information for fungi. Includes sequenced fungal genomes, those in progress, and selected nominations. Nomination of new species for genome sequencing in the families or only one reference genome possible after providing DNA/RNA samples for their sequencing. Used to explore the diversity of fungi important for energy and the environment.
Proper citation: 1000 Fungal Genome Project (RRID:SCR_016463) Copy
Database and information retrieval, analysis, and visualization system for microbial resources to help culture collections to manage, disseminate and share the information related to their holdings. Provides an interface for the scientific and industrial communities to access the microbial resource information.
Proper citation: Global Catalogue of Microorganisms (RRID:SCR_016460) Copy
Collection of curated papillomavirus genomic sequences, accompanied by web-based sequence analysis tools. Database and web applications support the storage, annotation, analysis, and exchange of information.
Proper citation: PaVE (RRID:SCR_016599) Copy
https://github.com/INTABiotechMJ/MITE-Tracker
Open source software tool for identifying miniature inverted repeat transposable elements in large genomes. Used to process large scale genomes, to find and classify MITEs using an efficient alignment strategy to retrieve nearby inverted repeat sequences.
Proper citation: MITE-Tracker (RRID:SCR_017030) Copy
http://www.chargeconsortium.com/
Consortium formed to facilitate genome-wide association study meta-analyses and replication opportunities among multiple large and well-phenotyped longitudinal cohort studies. A bibliography of CHARGE publications is available. Its founding member cohorts include: * Age, Gene, Environment, Susceptibility Study -- Reykjavik * Atherosclerosis Risk in Communities Study * Cardiovascular Health Study * Framingham Heart Study * Rotterdam Study Additional core cohorts include: * Coronary Artery Risk Development in Young Adults * Family Heart Study * Health, Aging, and Body Composition Study * Jackson Heart Study * Multi-Ethnic Study of Atherosclerosis
Proper citation: Cohorts for Heart and Aging Research in Genomic Epidemiology (RRID:SCR_004034) Copy
Consortium conducting meta-analyses of genome-wide genetic data for psychiatric disease. Focused on autism, attention-deficit hyperactivity disorder, bipolar disorder, major depressive disorder, schizophrenia, anorexia nervosa (AN), Tourette syndrome (TS), and obsessive-compulsive disorder (OCD). Used to investigate common single nucleotide polymorphisms (SNPs) genotyped on commercial arrays, structural variation (copy number variation) and uncommon or rare genetic variation. To participate you are asked to upload data from your study to central computer used by this consortium. Genetic Cluster Computer serves as data warehouse and analytical platform for this study . When data from your study have been incorporated, account will be provided on central server and access to all GWAS genotypes, phenotypes, and meta-analytic results relevant to deposited data and participation aims. NHGRI GWAS Catalog contains updated information about all GWAS in biomedicine, and is usually excellent starting point to find comprehensive list of studies. Files can be obtained by any PGC member for any disease to which they contributed data. These files can also be obtained by application to NIMH Genetics Repository. Individual-level genotype and phenotype data requires application, material transfer agreement, and informed consent consideration. Some datasets are also in controlled-access dbGaP and Wellcome Trust Case-Control Consortium repositories. PGC members can also receive back cleaned and imputed data and results for samples they contributed to PGC analyses.
Proper citation: Psychiatric Genomics Consortium (RRID:SCR_004495) Copy
http://www.broadinstitute.org/cancer/software/genepattern
A powerful genomic analysis platform that provides access to hundreds of tools for gene expression analysis, proteomics, SNP analysis, flow cytometry, RNA-seq analysis, and common data processing tasks. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research.
Proper citation: GenePattern (RRID:SCR_003201) Copy
http://www.loni.usc.edu/BIRN/Projects/Mouse/
Animal model data primarily focused on mice including high resolution MRI, light and electron microscopic data from normal and genetically modified mice. It also has atlases, and the Mouse BIRN Atlasing Toolkit (MBAT) which provides a 3D visual interface to spatially registered distributed brain data acquired across scales. The goal of the Mouse BIRN is to help scientists utilize model organism databases for analyzing experimental data. Mouse BIRN has ended. The next phase of this project is the Mouse Connectome Project (https://www.nitrc.org/projects/mcp/). The Mouse BIRN testbeds initially focused on mouse models of neurodegenerative diseases. Mouse BIRN testbed partners provide multi-modal, multi-scale reference image data of the mouse brain as well as genetic and genomic information linking genotype and brain phenotype. Researchers across six groups are pooling and analyzing multi-scale structural and functional data and integrating it with genomic and gene expression data acquired from the mouse brain. These correlated multi-scale analyses of data are providing a comprehensive basis upon which to interpret signals from the whole brain relative to the tissue and cellular alterations characteristic of the modeled disorder. BIRN's infrastructure is providing the collaborative tools to enable researchers with unique expertise and knowledge of the mouse an opportunity to work together on research relevant to pre-clinical mouse models of neurological disease. The Mouse BIRN also maintains a collaborative Web Wiki, which contains announcements, an FAQ, and much more.
Proper citation: Mouse Biomedical Informatics Research Network (RRID:SCR_003392) Copy
Commercial organization that discovers, validates & analyzes genomic biomarkers with a focus on body fluid samples. Take advantage of their proven expertise in biomarker signature development and speed up your biomarker studies.
Proper citation: Comprehensive Biomarker Center (RRID:SCR_003901) Copy
http://www.europeanlung.org/en/projects-and-research/projects/airprom/
Consortium focused on developing computer and physical models of the airway system for patients with asthma and chronic obstructive pulmonary disease (COPD). Developing accurate models will better predict how asthma and COPD develop, since current methods can only assess the severity of disease. They aim to bridge the gaps in clinical management of airways-based disease by providing reliable models that predict disease progression and the response to treatment for each person with asthma or COPD. A data management platform provides a secure and sustainable infrastructure that semantically integrates the clinical, physiological, genetic, and experimental data produced with existing biomedical knowledge from allied consortia and public databases. This resource will be available for analysis and modeling, and will facilitate sharing, collaboration and publication within AirPROM and with the broader community. Currently the AirPROM knowledge portal is only accessible by AirPROM partners.
Proper citation: AirPROM (RRID:SCR_003827) Copy
http://www.genome.jp/kegg/expression/
Database for mapping gene expression profiles to pathways and genomes. Repository of microarray gene expression profile data for Synechocystis PCC6803 (syn), Bacillus subtilis (bsu), Escherichia coli W3110 (ecj), Anabaena PCC7120 (ana), and other species contributed by the Japanese research community.
Proper citation: Kyoto Encyclopedia of Genes and Genomes Expression Database (RRID:SCR_001120) Copy
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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