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https://imputationserver.sph.umich.edu/

Web server to implement whole genotype imputation workflow for efficient parallelization of computationally intensive tasks. Service for imputation that facilitates access to new reference panels and greatly improves user experience and productivity. Used to find haplotype segments and reference panel of sequenced genomes, assign genotypes at untyped markers, improve genome coverage, facilitate comparison and combination of studies that use different marker panels, increase power to detect genetic association, and guide fine mapping.

Proper citation: Michigan Imputation Server (RRID:SCR_017579) Copy   

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http://mummer.sourceforge.net/

Software package as system for rapidly aligning entire genomes. Alignment tool for DNA and protein sequences. Can align incomplete genomes.

Proper citation: MUMmer (RRID:SCR_018171) Copy   

•   Source: SciCrunch Registry

http://research-pub.gene.com/gmap/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. A software program for mapping and aligning cDNA sequences to a genome. The program maps and aligns a single sequence with minimal startup time and memory requirements, and provides fast batch processing of large sequence sets. The program generates accurate gene structures, even in the presence of substantial polymorphisms and sequence errors, without using probabilistic splice site models. Methodology underlying the program includes a minimal sampling strategy for genomic mapping, oligomer chaining for approximate alignment, sandwich DP for splice site detection, and microexon identification with statistical significance testing.

Proper citation: GMAP (RRID:SCR_008992) Copy   

•   Source: SciCrunch Registry

https://www.mtocdb.org/?next=/browse/results/

A database of over 300 Electron Microscopy (EM) images of centrioles and centriole related structures from almost 60 species, described by a controlled vocabulary allowing detailed description of the observed structures. This knowledge is supplemented by a manually curated list of proteins known to be involved in centriole assembly, their (putative) orthologs, and localization information. mtocDB aims to characterize the naturally occurring morphological variation observed in centrioles and centriole associated structure alongside molecular information on the proteins involved in their assembly. Examining these in an evolutionary context will allow the cell biology community to infer meaningful relationships between cellular assembly mechanisms and the structures they form. This community resource for cell biologists interested in the the evolution of centrioles and centriole related structures aims to bridge the gap between structural morphology and molecular function by examining naturally occurring structural variation in a phylogenomic context. Centrioles are cylindrical microtubule arrays required for stability and duplication of the centrosome in animal cells, and for the assembly of cilia and flagella in many eukaryotes. The presence of centrioles throughout most eukaryotic branches suggests that this structure was present in the last eukaryotic common ancestor. Although centrioles show a typically well conserved structure, they can perform several functions and display a diversity of accessory structures. However, this diversity is not properly classified beyond model organisms, and the information contained in decades of electronic microscopy of other organisms remains untapped.

Proper citation: mtocDB (RRID:SCR_008933) Copy   

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http://gwas.biosciencedbc.jp/cgi-bin/hvdb/hv_top.cgi

A repository database to achieve continuous and intensive management of GWAS data and variation data identified by next generation sequencing (NGS) and data-sharing among researchers. In this database, variations including short/long insertions / deletions and structural variations related to disease susceptibility, virus resistance, and drug response are registered along with statistical genetic results and simple clinical characteristics to clarify the locus specific characteristics. Currently this database contains information extracted from scientific papers and next generation sequencing results and other small scale experimental results of several research laboratories. Mutation data submission is greatly appreciated.

Proper citation: Human Variation DB (RRID:SCR_009014) Copy   

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http://www.evocontology.org/site/Main/EvocOntologyDotOrg

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented September 6, 2016. Set of orthogonal controlled vocabularies that unifies gene expression data by facilitating a link between the genome sequence and expression phenotype information. The system associates labelled target cDNAs for microarray experiments, or cDNA libraries and their associated transcripts with controlled terms in a set of hierarchical vocabularies. eVOC consists of four orthogonal controlled vocabularies suitable for describing the domains of human gene expression data including Anatomical System, Cell Type, Pathology and Developmental Stage. The four core eVOC ontologies provide an appropriate set of detailed human terms that describe the sample source of human experimental material such as cDNA and SAGE libraries. These expression terms are linked to libraries and transcripts allowing the assessment of tissue expression profiles, differential gene expression levels and the physical distribution of expression across the genome. Analysis is currently possible using EST and SAGE data, with microarray data being incorporated. The eVOC data is increasingly being accepted as a standard for describing gene expression and eVOC ontologies are integrated with the Ensembl EnsMart database, the Alternate Transcript Diversity Project and the UniProt Knowledgebase. Several groups are currently working to provide shared development of this resource such that it is of maximum use in unifying transcript expression information.

Proper citation: eVOC (RRID:SCR_010704) Copy   

•   Source: SciCrunch Registry

http://www.g-language.org/GenomeProjector/

A searchable database browser with zoomable user interface using Google Map API. Genome Projector currently contains 4 views: Genome map, Plasmid map, Pathway map, and DNA walk.

Proper citation: Genome Projector (RRID:SCR_011790) 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://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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.pombase.org/

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   

•   Source: SciCrunch Registry

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