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http://sequenceontology.org/

A collaborative ontology for the definition of sequence features used in biological sequence annotation. SO was initially developed by the Gene Ontology Consortium. Contributors to SO include the GMOD community, model organism database groups such as WormBase, FlyBase, Mouse Genome Informatics group, and institutes such as the Sanger Institute and the EBI. Input to SO is welcomed from the sequence annotation community. The OBO revision is available here: http://sourceforge.net/p/song/svn/HEAD/tree/ SO includes different kinds of features which can be located on the sequence. Biological features are those which are defined by their disposition to be involved in a biological process. Biomaterial features are those which are intended for use in an experiment such as aptamer and PCR_product. There are also experimental features which are the result of an experiment. SO also provides a rich set of attributes to describe these features such as polycistronic and maternally imprinted. The Sequence Ontologies use the OBO flat file format specification version 1.2, developed by the Gene Ontology Consortium. The ontology is also available in OWL from Open Biomedical Ontologies. This is updated nightly and may be slightly out of sync with the current obo file. An OWL version of the ontology is also available. The resolvable URI for the current version of SO is http://purl.obolibrary.org/obo/so.owl.

Proper citation: SO (RRID:SCR_004374) Copy   

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http://bix.ucsd.edu/projects/singlecell/

Software package for short read data from single cells that improves assembly through use of progressively increasing coverage cutoff. Used for single cell Illumina sequences, allows variable coverage datasets to be utilized with assembly of E. coli and S. aureus single cell reads. Assembles single cell genome of uncultivated SAR324 clade of Deltaproteobacteria.

Proper citation: Velvet-SC (RRID:SCR_004377) Copy   

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http://www.nematodes.org/nematodegenomes/index.php/Main_Page

A collaborative wiki that collates information on completed, ongoing and planned genome and transcriptome sequencing projects on species from phylum Nematoda. The intention is to encourage genome sequencing across the diversity of the phylum Nematoda. Wiki includes: * Published complete nematode genomes: A dynamically generated table of all species for which the genome is published. * Nematode species with genomes in progress: A dynamically generated table of all species for which a genome project is underway. Users may add species to the list * Proposed nematode genome projects: To propose a species for genome sequencing, edit its species page, and set the genome project status to proposed. * BLAST server: Search a number of the nematode-genomes-in-progress with genes of your choice. Currently there are 12 draft genomes available... * Genomes with Data available: Genomes with data available for download. Users may add more data URLs to strain pages or update the URLs.

Proper citation: 959 Nematode Genomes (RRID:SCR_006068) Copy   

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http://oligogenome.stanford.edu/

The Stanford Human OligoGenome Project hosts a database of capture oligonucleotides for conducting high-throughput targeted resequencing of the human genome. This set of capture oligonucleotides covers over 92% of the human genome for build 37 / hg19 and over 99% of the coding regions defined by the Consensus Coding Sequence (CCDS). The capture reaction uses a highly multiplexed approach for selectively circularizing and capturing multiple genomic regions using the in-solution method developed in Natsoulis et al, PLoS One 2011. Combined pools of capture oligonucleotides selectively circularize the genomic DNA target, followed by specific PCR amplification of regions of interest using a universal primer pair common to all of the capture oligonucleotides. Unlike multiplexed PCR methods, selective genomic circularization is capable of efficiently amplifying hundreds of genomic regions simultaneously in multiplex without requiring extensive PCR optimization or producing unwanted side reaction products. Benefits of the selective genomic circularization method are the relative robustness of the technique and low costs of synthesizing standard capture oligonucleotide for selecting genomic targets.

Proper citation: OligoGenome (RRID:SCR_006025) Copy   

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http://db-mml.sjtu.edu.cn/ICEberg/

ICEberg is an integrated database that provides comprehensive information about integrative and conjugative elements (ICEs) found in bacteria. ICEs are conjugative self-transmissible elements that can integrate into and excise from a host chromosome. An ICE contains three typical modules, integration and excision, conjugation, and regulation modules, that collectively promote vertical inheritance and periodic lateral gene flow. Many ICEs carry likely virulence determinants, antibiotic-resistant factors and/or genes coding for other beneficial traits. ICEberg offers a unique, highly organized, readily explorable archive of both predicted and experimentally supported ICE-relevant data. It currently contains details of 428 ICEs found in representatives of 124 bacterial species, and a collection of >400 directly related references. A broad range of similarity search, sequence alignment, genome context browser, phylogenetic and other functional analysis tools are readily accessible via ICEberg. ICEberg will facilitate efficient, multidisciplinary and innovative exploration of bacterial ICEs and be of particular interest to researchers in the broad fields of prokaryotic evolution, pathogenesis, biotechnology and metabolism. The ICEberg database will be maintained, updated and improved regularly to ensure its ongoing maximum utility to the research community.

Proper citation: ICEberg (RRID:SCR_006026) Copy   

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http://www.ncbi.nlm.nih.gov/projects/gv/rbc/main.fcgi?cmd=init

The dbRBC database provides an open, publicly accessible platform for DNA and clinical data related to the human Red Blood Cells (RBC). A new bioinformatics resource, dbRBC, has been installed at the National Center of Biotechnology Information (NCBI). This resource combines the well established Blood Group Antigen Gene Mutation Database (BGMUT) with tools and interlinked resources developed at the NCBI. The main task of dbRBC is to provide access to publicly available genomic, protein and structural information linked to the red blood cell antigens. The site offers a number of resources: * BGMUT Database * Alignment Viewer * SBT Tool * Probe/Primer Resource * Typing Kit Interface * Obstacle

Proper citation: NCBI dbRBC (RRID:SCR_005959) Copy   

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http://hannonlab.cshl.edu/index.html

The Hannon laboratory comprises a broad spectrum of programs in small RNA biology, mammalian genetics and genomics. We study RNAi and related pathways in a wide variety of organisms to extract common themes that define both the mechanisms by which small RNAs act and the biological processes which they impact. Currently, we focus on microRNAs, endogenous siRNAs and piRNAs and their roles in gene regulation, cancer biology, stem cell biology and in defense of the genome against transposons. In collaboration with Steve Elledge (Harvard) and Scott Lowe (CSHL), we develop genome-wide shRNA tools for RNAi-based genetics in mammalian cells, and we are now producing similar collections of artificial microRNAs for Arabidopsis with Detlef Weigel (MPI), Dick McCombie (CSHL) and Rob Martienssen (CSHL) as part of the 2010 project (see 2010.cshl.edu). Our genomic efforts include the application of RNAi-based genetic screens to cancer biology and stem cells. We also make heavy use of next generation sequencing methodologies for probing small RNA populations, in part as a member of the ENCODE consortium (with Tom Gingeras, CSHL). Finally, we develop (with Dick McCombie) and apply focal re-sequencing methods for identifying disease relevant mutations, for probing the epigenetic landscape and for the study of human evolution.

Proper citation: CSHL - Hannon Lab (RRID:SCR_005982) Copy   

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http://www.cmhd.ca/

Multidisciplinary collaboration undertaking genome-wide mutagenesis to functionally annotate the mouse genome and develop new mouse models relevant to human disease. To achieve these goals two major research platforms are carried out: Gene trapping and ENU Mutagenesis. A new challenge is faced in the post-genomic era - the assignment of biological function to the human genome sequence and projecting that assignment into understanding of human health and disease. The Centre for Modeling Human Disease (CMHD) was established to take part in the worldwide initiative to address these challenges. At the CMHD, two fundamentally different, yet complimentary methods are employed to generate mutant mouse models of human disease: chemical mutagenesis by ethylnitrosourea (ENU), and gene trap insertional mutagenesis. The Centre contributes its resources to similar international efforts and is the first of its kind in Canada. The Center is also actively developing other mutagenic strategies including pharmacologic and genetic modifier screens to dissect disease pathways, and novel mutagenic techniques using embryonic stem cells. ENU Database * Statistics for Mouse Physiological Parameters * Search Mutants by Phenotype * Search Mutants by Heritability Gene Trap Database * Search by in vitro Expression Pattern * Search by Gene Trap Sequences CMHD Members Only (must register and login) * Search Mouse Line * Histopathology * Sperm, Tissue, Slide Archiving * CMHD Database Download CMHD Services * Phenotyping * Genetic Mapping * Pathology * Pathology Service Charges

Proper citation: CMHD - Centre for Modeling Human Disease (RRID:SCR_006101) Copy   

•   Source: SciCrunch Registry

http://www.gwascentral.org/

Publicly available database of summary level findings from genetic association studies in humans, including genome wide association studies (GWAS). Previously named HGBASE, HGVbase and HGVbaseG2P.

Proper citation: GWAS Central (RRID:SCR_006170) Copy   

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http://epigenomegateway.wustl.edu/

Software tool for visualizing and interacting with whole-genome datasets. Browser hosts Human Epigenome Atlas data produced by Roadmap Epigenomics project, but its use of advanced, multi-resolution data formats and its user-friendly interface make it possible for investigators to upload and visualize their own data as custom tracks. Developed and maintained by Epigenome Informatics Group at Washington University in St. Louis.

Proper citation: WashU Epigenome Browser (RRID:SCR_006208) Copy   

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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   

•   Source: SciCrunch Registry

http://modencode.org/

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   

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http://sparkinsight.org

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   

•   Source: SciCrunch Registry

http://gensc.org/

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   

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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   

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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   

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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   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/ena/

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   

•   Source: SciCrunch Registry

https://www.phenxtoolkit.org/

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   

•   Source: SciCrunch Registry

http://rgd.mcw.edu

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   

•   Source: SciCrunch Registry