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http://discover.nci.nih.gov/gominer/

GoMiner is a tool for biological interpretation of "omic" data including data from gene expression microarrays. Omic experiments often generate lists of dozens or hundreds of genes that differ in expression between samples, raising the question, What does it all mean biologically? To answer this question, GoMiner leverages the Gene Ontology (GO) to identify the biological processes, functions and components represented in these lists. Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. The insights gained through GoMiner can generate hypotheses to guide additional research. GoMiner displays the genes within the framework of the Gene Ontology hierarchy in two ways: * In the form of a tree, similar to that in AmiGO * In the form of a "Directed Acyclic Graph" (DAG) The program also provides: * Quantitative and statistical analysis * Seamless integration with important public databases GoMiner uses the databases provided by the GO Consortium. These databases combine information from a number of different consortium participants, include information from many different organisms and data sources, and are referenced using a variety of different gene product identification approaches.

Proper citation: GoMiner (RRID:SCR_002360) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/ontology-for-genetic-interval/

An ontology that formalized the genomic element by defining an upper class genetic interval using BFO as its framework. The definition of genetic interval is the spatial continuous physical entity which contains ordered genomic sets (DNA, RNA, Allele, Marker,etc.) between and including two points (Nucleic_Acid_Base_Residue) on a chromosome or RNA molecule which must have a liner primary sequence structure.

Proper citation: Ontology for Genetic Interval (RRID:SCR_003423) Copy   

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http://smd.stanford.edu/cgi-bin/source/sourceSearch

SOURCE compiles information from several publicly accessible databases, including UniGene, dbEST, UniProt Knowledgebase, GeneMap99, RHdb, GeneCards and LocusLink. GO terms associated with LocusLink entries appear in SOURCE. The mission of SOURCE is to provide a unique scientific resource that pools publicly available data commonly sought after for any clone, GenBank accession number, or gene. SOURCE is specifically designed to facilitate the analysis of large sets of data that biologists can now produce using genome-scale experimental approaches Platform: Online tool

Proper citation: SOURCE (RRID:SCR_005799) Copy   

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https://bioservices.uncc.edu

Core to assist with analyzing and interpreting data produced by genomic technologies.

Proper citation: University of North Carolina Charlotte Bioinformatics Services Division (RRID:SCR_017182) Copy   

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https://www.cityofhope.org/research/shared-resources/integrative-genomics-and-bioinformatics

Core provides genomic and bioinformatics services to City of Hope Comprehensive Cancer Center (COHCCC) investigators.

Proper citation: City of Hope National Medical Center Integrative Genomics and Bioinformatics Core Facility (RRID:SCR_017188) Copy   

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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   

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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   

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https://anvilproject.org/

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   

•   Source: SciCrunch Registry

https://glomcon.org

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   

•   Source: SciCrunch Registry

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   

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http://www.sanger.ac.uk/science/tools/ssaha2-0

A program designed for the efficient mapping of sequence reads onto genomic references. The software is capable of reading most sequencing platforms and giving a range of outputs are supported.

Proper citation: Sequence Search and Alignment by Hashing Algorithm (RRID:SCR_000544) Copy   

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http://www.doe-mbi.ucla.edu/

The UCLA-DOE Institute for Genomics and Proteomics carries out research in bioenergy, structural biology, genomics and proteomics, consistent with the research mission of the United States Department of Energy. Major interests of the 12 Principal Investigators and 9 Associate Members include systems approaches to organisms, structural biology, bioinformatics, and bioenergetic systems. The Institute sponsors 5 Core Technology Centers, for X-ray and NMR structural determination, bioinformatics and computation, protein expression and purification, and biochemical instrumentation. Services offered by this Institute: - Databases: * DIP (The Database of Interacting Proteins): The DIPTM database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. * ProLinks Database of Functional Linkages: The Prolinks database is a collection of inference methods used to predict functional linkages between proteins. These methods include the Phylogenetic Profile method which uses the presence and absence of proteins across multiple genomes to detect functional linkages; the Gene Cluster method, which uses genome proximity to predict functional linkage; Rosetta Stone, which uses a gene fusion event in a second organism to infer functional relatedness; and the Gene Neighbor method, which uses both gene proximity and phylogenetic distribution to infer linkage. - Data-to-Structure Servers: * SAVEs Structure Verification Server * Merohedral Twinning Test Server * SER Surface Entropy Reduction Server * VERIFY3D Structure Verification Server * ERRAT Structure Verification Server - Structure-to-Function Servers: * ProKnow Protein Functionator * Hot Patch Functional Site Locator

Proper citation: University of California at Los Angeles - Department of Energy Institute for Genomics and Proteomics (RRID:SCR_001921) Copy   

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

Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.

Proper citation: PLINK (RRID:SCR_001757) Copy   

•   Source: SciCrunch Registry

https://www.snpstats.net/

A web-based application designed from a genetic epidemiology point of view to analyze association studies using single nucleotide polymorphisms (SNPs). For each selected SNP, you will receive: * Allele and genotype frequencies * Test for Hardy-Weinberg equilibrium * Analysis of association with a response variable based on linear or logistic regression * Multiple inheritance models: co-dominant, dominant, recessive, over-dominant and additive * Analysis of interactions (gene-gene or gene-environment) If multiple SNPs are selected: * Linkage disequilibrium statistics * Haplotype frequency estimation * Analysis of association of haplotypes with the response * Analysis of interactions (haplotypes-covariate)

Proper citation: SNPSTATS (RRID:SCR_002142) Copy   

•   Source: SciCrunch Registry

http://www.aspgd.org/

Database of genetic and molecular biological information about the filamentous fungi of the genus Aspergillus including information about genes and proteins of Aspergillus nidulans and Aspergillus fumigatus; descriptions and classifications of their biological roles, molecular functions, and subcellular localizations; gene, protein, and chromosome sequence information; tools for analysis and comparison of sequences; and links to literature information; as well as a multispecies comparative genomics browser tool (Sybil) for exploration of orthology and synteny across multiple sequenced Sgenus species. Also available are Gene Ontology (GO) and community resources. Based on the Candida Genome Database, the Aspergillus Genome Database is a resource for genomic sequence data and gene and protein information for Aspergilli. Among its many species, the genus contains an excellent model organism (A. nidulans, or its teleomorph Emericella nidulans), an important pathogen of the immunocompromised (A. fumigatus), an agriculturally important toxin producer (A. flavus), and two species used in industrial processes (A. niger and A. oryzae). Search options allow you to: *Search AspGD database using keywords. *Find chromosomal features that match specific properties or annotations. *Find AspGD web pages using keywords located on the page. *Find information on one gene from many databases. *Search for keywords related to a phenotype (e.g., conidiation), an allele (such as veA1), or an experimental condition (e.g., light). Analysis and Tools allow you to: *Find similarities between a sequence of interest and Aspergillus DNA or protein sequences. *Display and analyze an Aspergillus sequence (or other sequence) in many ways. *Navigate the chromosomes set. View nucleotide and protein sequence. *Find short DNA/protein sequence matches in Aspergillus. *Design sequencing and PCR primers for Aspergillus or other input sequences. *Display the restriction map for a Aspergillus or other input sequence. *Find similarities between a sequence of interest and fungal nucleotide or protein sequences. AspGD welcomes data submissions.

Proper citation: ASPGD (RRID:SCR_002047) Copy   

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http://www.ncbi.nlm.nih.gov/HTGS/

Database of high-throughput genome sequences from large-scale genome sequencing centers, including unfinished and finished sequences. It was created to accommodate a growing need to make unfinished genomic sequence data rapidly available to the scientific community in a coordinated effort among the International Nucleotide Sequence databases, DDBJ, EMBL, and GenBank. Sequences are prepared for submission by using NCBI's software tools Sequin or tbl2asn. Each center has an FTP directory into which new or updated sequence files are placed. Sequence data in this division are available for BLAST homology searches against either the htgs database or the month database, which includes all new submissions for the prior month. Unfinished HTG sequences containing contigs greater than 2 kb are assigned an accession number and deposited in the HTG division. A typical HTG record might consist of all the first-pass sequence data generated from a single cosmid, BAC, YAC, or P1 clone, which together make up more than 2 kb and contain one or more gaps. A single accession number is assigned to this collection of sequences, and each record includes a clear indication of the status (phase 1 or 2) plus a prominent warning that the sequence data are unfinished and may contain errors. The accession number does not change as sequence records are updated; only the most recent version of a HTG record remains in GenBank.

Proper citation: High Throughput Genomic Sequences Division (RRID:SCR_002150) Copy   

•   Source: SciCrunch Registry

https://arvados.org/

Bioinformatics platform for storing, organizing, processing, and sharing genomic and other biomedical big data. Designed to make it easier for bioinformaticians to develop analyses, developers to create genomic web applications and IT administers to manage large-scale compute and storage genomic resources. Designed to run on top of cloud operating systems such as Amazon Web Services and OpenStack. Currently, there are implementations that work on AWS and Xen+Debian/Ubuntu. Functionally, Arvados has two major sets of capabilities: (a) data management and (b) compute management.

Proper citation: Arvados (RRID:SCR_002223) Copy   

•   Source: SciCrunch Registry

http://www.ark-genomics.org/

Portal for studies of genome structure and genetic variation, gene expression and gene function. Provides services including DNA sequencing of model and non-model genomes using both Next Generation and Sanger sequencing , Gene expression analysis using both microarrays and Next Generation Sequencing, High throughput genotyping of SNP and copy number variants, Data collection and analysis supported in-house high performance computing facilities and expertise, Extensive EST clone collections for a number of animal species, all of commercially available microarray tools from Affymetrix, Illumina, Agilent and Nimblegen, Parentage testing using microsatellites and smaller SNP panels. ARK-Genomics has developed network of researchers whom they support through each stage of their genomics research, from grant application, experimental design and technology selection, performing wet laboratory protocols, through to analysis of data often in conjunction with commercial partners.

Proper citation: ARK-Genomics: Centre for Functional Genomics (RRID:SCR_002214) Copy   

•   Source: SciCrunch Registry

http://htslib.org/

Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.

Proper citation: SAMTOOLS (RRID:SCR_002105) Copy   

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http://sourceforge.net/projects/gmato/files/?source=navbar

A software tool used for simple sequence repeats (SSR) or microsatellite characterization. It also facilitates SSR marker design on a genomic scale, microsatellite mining at any length, and comprehensive statistical analysis for DNA sequences in any genome at any size. Analysis parameters are customizable.

Proper citation: GMATo (RRID:SCR_000165) Copy   

•   Source: SciCrunch Registry