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http://isaac.bioapps.biozentrum.uni-wuerzburg.de/isaac/modules/genome/species.xhtml
Web based tool to enable the analysis of sets of genes, transcripts and proteins under different biological viewpoints and to interactively modify these sets at any point of the analysis. Detailed history and snapshot information allows tracing each action. One can switch back to previous states and perform new analyses. Sets can be viewed in the context of genomes, protein functions, protein interactions, pathways, regulation, diseases and drugs. Additionally, users can switch between species with an automatic, orthology based translation of existing gene sets. Sets as well as results of analyses can be exchanged between members of groups.
Proper citation: InterSpecies Analysing Application using Containers (RRID:SCR_006243) Copy
A comprehensive encyclopedia of genomic functional elements in the model organisms C. elegans and D. melanogaster. modENCODE is run as a Research Network and the consortium is formed by 11 primary projects, divided between worm and fly, spanning the domains of gene structure, mRNA and ncRNA expression profiling, transcription factor binding sites, histone modifications and replacement, chromatin structure, DNA replication initiation and timing, and copy number variation. The raw and interpreted data from this project is vetted by a data coordinating center (DCC) to ensure consistency and completeness. The entire modENCODE data corpus is now available on the Amazon Web Services EC2 cloud. What this means is that virtual machines and virtual compute clusters that you run within the EC2 cloud can mount the modENCODE data set in whole or in part. Your software can run analyses against the data files directly without experiencing the long waits and logistics associated with copying the datasets over to your local hardware. You may also view the data using GBrowse, Dataset Search, or download the data via FTP, as well as download pre-release datasets.
Proper citation: modENCODE (RRID:SCR_006206) Copy
A clustering and visualization tool that enables the interactive exploration of genome-wide data, with a specialization in epigenomics data. Spark is also available as a service within the Epigenome toolset of the Genboree Workbench. The approach utilizes data clusters as a high-level visual guide and supports interactive inspection of individual regions within each cluster. The cluster view links to gene ontology analysis tools and the detailed region view connects to existing genome browser displays taking advantage of their wealth of annotation and functionality.
Proper citation: Spark (RRID:SCR_006207) Copy
An open-membership International community to promote mechanisms that standardize the description of genomes and the exchange and integration of genomic data. Community-driven standards have the best chance of success if developed within the auspices of international working groups. Participants in the GSC include biologists, computer scientists, those building genomic databases and conducting large-scale comparative genomic analyses, and those with experience of building community-based standards. The mission of the GSC is to work with the wider community towards: * the implementation of new genomic standards * methods of capturing and exchanging metadata * harmonization of metadata collection and analysis efforts across the wider genomics community
Proper citation: Genomic Standards Consortium (RRID:SCR_006273) Copy
http://www.uni-koeln.de/med-fak/cgars/
Software package to dissect random from non-random patterns in copy number data and thereby to assess significantly enriched somatic copy number aberrations (SCNA) across a set of tumor specimens or cell lines.
Proper citation: CGARS (RRID:SCR_006404) Copy
http://www.clipz.unibas.ch/downloads/TSSer/index.php
A computational pipeline to analyze differential RNA sequencing (dRNA-seq) data to determine transcription start sites genome-wide.
Proper citation: TSSer (RRID:SCR_006419) Copy
Model organism database that provides organization of and access to scientific data for the fission yeast Schizosaccharomyces pombe. PomBase supports genomic sequence and features, genome-wide datasets and manual literature curation. PomBase also provides a community hub for researchers, providing genome statistics, a community curation interface, news, events, documentation, mailing lists, and welcomes data submissions.
Proper citation: PomBase (RRID:SCR_006586) Copy
http://bioinformatics.ubc.ca/ermineJ/
Data analysis software for gene sets in expression microarray data or other genome-wide data that results in rankings of genes. A typical goal is to determine whether particular biological pathways are doing something interesting in the data. The software is designed to be used by biologists with little or no informatics background. A command-line interface is available for users who wish to script the use of ermineJ. Major features include: * Implementation of multiple methods for gene set analysis: ** Over-representation analysis ** A resampling-based method that uses gene scores ** A rank-based method that uses gene scores ** A resampling-based method that uses correlation between gene expression profiles (a type of cluster-enrichment analysis). * Gene sets receive statistical scores (p-values), and multiple test correction is supported. * Support of the Gene Ontology terminology; users can choose which aspects to analyze. * User files use simple text formats. * Users can modify gene sets or create new ones. * The results can be visualized within the software. * It is simple to compare multiple analyses of the same data set with different settings. * User-definable hyperlinks are provided to external sites to allow more efficient browsing of the results. * For programmers, there is a command line interface as well as a simple application programming interface that can be used to plug ermineJ functionality into your own code Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: ErmineJ (RRID:SCR_006450) Copy
Public archive providing a comprehensive record of the world''''s nucleotide sequencing information, covering raw sequencing data, sequence assembly information and functional annotation. All submitted data, once public, will be exchanged with the NCBI and DDBJ as part of the INSDC data exchange agreement. The European Nucleotide Archive (ENA) captures and presents information relating to experimental workflows that are based around nucleotide sequencing. A typical workflow includes the isolation and preparation of material for sequencing, a run of a sequencing machine in which sequencing data are produced and a subsequent bioinformatic analysis pipeline. ENA records this information in a data model that covers input information (sample, experimental setup, machine configuration), output machine data (sequence traces, reads and quality scores) and interpreted information (assembly, mapping, functional annotation). Data arrive at ENA from a variety of sources including submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centers and routine and comprehensive exchange with their partners in the International Nucleotide Sequence Database Collaboration (INSDC). Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and to provide optimal submission systems and data access tools that work seamlessly with the published literature. ENA is made up of a number of distinct databases that includes the EMBL Nucleotide Sequence Database (Embl-Bank), the newly established Sequence Read Archive (SRA) and the Trace Archive. The main tool for downloading ENA data is the ENA Browser, which is available through REST URLs for easy programmatic use. All ENA data are available through the ENA Browser. Note: EMBL Nucleotide Sequence Database (EMBL-Bank) is entirely included within this resource.
Proper citation: European Nucleotide Archive (ENA) (RRID:SCR_006515) Copy
Set of measures intended for use in large-scale genomic studies. Facilitate replication and validation across studies. Includes links to standards and resources in effort to facilitate data harmonization to legacy data. Measurement protocols that address wide range of research domains. Information about each protocol to ensure consistent data collection.Collections of protocols that add depth to Toolkit in specific areas.Tools to help investigators implement measurement protocols.
Proper citation: Phenotypes and eXposures Toolkit (RRID:SCR_006532) Copy
Database for genetic, genomic, phenotype, and disease data generated from rat research. Centralized database that collects, manages, and distributes data generated from rat genetic and genomic research and makes these data available to scientific community. Curation of mapped positions for quantitative trait loci, known mutations and other phenotypic data is provided. Facilitates investigators research efforts by providing tools to search, mine, and analyze this data. Strain reports include description of strain origin, disease, phenotype, genetics, immunology, behavior with links to related genes, QTLs, sub-strains, and strain sources.
Proper citation: Rat Genome Database (RGD) (RRID:SCR_006444) Copy
http://www.gigasciencejournal.com/
An online open-access open-data journal, publishing ''big-data'' studies from the entire spectrum of life and biomedical sciences whose publication format links standard manuscript publication with its affiliated database, GigaDB, that hosts all associated data, provides data analysis tools, cloud-computing resources, and a DOI assignment to every dataset. GigaScience covers not just ''omic'' type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale sharable data. Supporting the open-data movement, they require that all supporting data and source code be publicly available in a suitable public repository and/or under a public domain CC0 license in the BGI GigaScience database. Using the BGI cloud as a test environment, they also consider open-source software tools / methods for the analysis or handling of large-scale data. When submitting a manuscript, please contact them if you have datasets or cloud applications you would like them to host. To maximize data usability submitters are encouraged to follow best practice for metadata reporting and are given the opportunity to submit in ISA-Tab format.
Proper citation: GigaScience (RRID:SCR_006565) Copy
Database of Drosophila genetic and genomic information with information about stock collections and fly genetic tools. Gene Ontology (GO) terms are used to describe three attributes of wild-type gene products: their molecular function, the biological processes in which they play a role, and their subcellular location. Additionally, FlyBase accepts data submissions. FlyBase can be searched for genes, alleles, aberrations and other genetic objects, phenotypes, sequences, stocks, images and movies, controlled terms, and Drosophila researchers using the tools available from the "Tools" drop-down menu in the Navigation bar.
Proper citation: FlyBase (RRID:SCR_006549) Copy
Service providing functional analysis of proteins by classifying them into families and predicting domains and important sites. They combine protein signatures from a number of member databases into a single searchable resource, capitalizing on their individual strengths to produce a powerful integrated database and diagnostic tool. This integrated database of predictive protein signatures is used for the classification and automatic annotation of proteins and genomes. InterPro classifies sequences at superfamily, family and subfamily levels, predicting the occurrence of functional domains, repeats and important sites. InterPro adds in-depth annotation, including GO terms, to the protein signatures. You can access the data programmatically, via Web Services. The member databases use a number of approaches: # ProDom: provider of sequence-clusters built from UniProtKB using PSI-BLAST. # PROSITE patterns: provider of simple regular expressions. # PROSITE and HAMAP profiles: provide sequence matrices. # PRINTS provider of fingerprints, which are groups of aligned, un-weighted Position Specific Sequence Matrices (PSSMs). # PANTHER, PIRSF, Pfam, SMART, TIGRFAMs, Gene3D and SUPERFAMILY: are providers of hidden Markov models (HMMs). Your contributions are welcome. You are encouraged to use the ''''Add your annotation'''' button on InterPro entry pages to suggest updated or improved annotation for individual InterPro entries.
Proper citation: InterPro (RRID:SCR_006695) Copy
Database of peer-reviewed, continually updated annotation for the Pseudomonas aeruginosa PAO1 reference strain genome expanded to include all Pseudomonas species to facilitate cross-strain and cross-species genome comparisons with high quality comparative genomics. The database contains robust assessment of orthologs, a novel ortholog clustering method, and incorporates five views of the data at the sequence and annotation levels (Gbrowse, Mauve and custom views) to facilitate genome comparisons. Other features include more accurate protein subcellular localization predictions and a user-friendly, Boolean searchable log file of updates for the reference strain PAO1. The current annotation is updated using recent research literature and peer-reviewed submissions by a worldwide community of PseudoCAP (Pseudomonas aeruginosa Community Annotation Project) participating researchers. If you are interested in participating, you are invited to get involved. Many annotations, DNA sequences, Orthologs, Intergenic DNA, and Protein sequences are available for download.
Proper citation: Pseudomonas Genome Database (RRID:SCR_006590) Copy
Collection of data related to crop plant and model organism Zea mays. Used to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models and to provide support services to the community of maize researchers. Data stored at MaizeGDB was inherited from the MaizeDB and ZmDB projects. Sequence data are from GenBank. Data are searchable by phenotype, traits, Pests, Gel Pattern, and Mutant Images.
Proper citation: MaizeGDB (RRID:SCR_006600) Copy
https://www.phenx.org/Default.aspx?tabid=56
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on 05 01 2025. PhenX is a project to prioritize Phenotype and eXposure measures for Genome-wide Association Studies (GWAS). Leaders of the scientific community will assess and prioritize a broad range of domains relevant to genomics research and public health. The PhenX Steering Committee (SC), chaired by Dr. Jonathan Haines, provides leadership in the selection of domains and domain experts. Members of the SC include outstanding scientists from the research community and liaisons from the Institutes and Centers of the National Institutes of Health. Consensus measures for GWAS will have a direct impact on biomedical research and ultimately on public health. During the course of this project, up to 20 research domains will be examined, with up to 15 measures being recommended for use in future GWAS and other large-scale genomic research efforts. The goal is to maximize the benefits of future research by having comparable measures so that studies can be integrated. Each selected domain will be reviewed by a Working Group (WG) of scientists who are experts in the research area. A systematic review of the literature will guide the WGs selection of up to 15 high priority measures with standardized approaches for measurement. Selection criteria for the measures include factors such as validity, reproducibility, cost, feasibility, and burden to both investigators and participants. The scientific community will be asked to provide input on proposed measures. Consensus development is a key component of the project.
Proper citation: Consensus Measures for Phenotype and Exposure (RRID:SCR_006688) Copy
http://sourceforge.net/projects/gasic/
A method to correct read alignment results for the ambiguities imposed by similarities of genomes.
Proper citation: GASiC (RRID:SCR_006765) Copy
http://pre.ensembl.org/index.html
Database of genomes that are in the process of being annotated are provided as an early access site for users. Genomes are here when the initial BLAST analysis on a new assembly has been done but the gene build has not been completed. Owing to the preliminary nature of the data, Pre-Ensembl provides views of the assembly, BLAST against the assembly and download of portions of the assembly - and little else. A number of ready-made tools for processing your data are also available. In general a full Ensembl release takes months depending on how complex the data are and the time constraints of people in the team. Occasionally a more complete gene build will be released on this site, but without any comparative genomics, variation or other additional data. Many other species with fully annotated genomic data, more website features and documentation are available at www.ensembl.org
Proper citation: Pre Ensembl (RRID:SCR_006766) Copy
Data resource that includes a large collection of genome-wide ChIP-Seq experiments performed on transcription factors (TFs), histone modifications, RNA polymerases and others. Enriched peak regions from the ChIP-Seq experiments are crossed with the genomic coordinates of a set of input genes, to identify which of the experiments present a statistically significant number of peaks within the input genes' loci. The input can be a cluster of co-expressed genes, or any other set of genes sharing a common regulatory profile. Users can thus single out which TFs are likely to be common regulators of the genes, and their respective correlations. Also, by examining results on promoter activation, transcription, histone modifications, polymerase binding and so on, users can investigate the effect of the TFs (activation or repression of transcription) as well as of the cell or tissue specificity of the genes' regulation and expression.
Proper citation: Cscan (RRID:SCR_006756) Copy
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