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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   

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http://www.informatics.jax.org/searches/AMA_form.shtml

Ontology that organizes anatomical structures for the adult mouse (Theiler stage 28) spatially and functionally, using ''is a'' and ''part of'' relationships. The ontology is used to describe expression data for the adult mouse and phenotype data pertinent to anatomy in standardized ways. The browser can be used to view anatomical terms and their relationships in a hierarchical display.

Proper citation: Adult Mouse Anatomy Ontology (RRID:SCR_006568) Copy   

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http://bio.math.berkeley.edu/eXpress/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented January 29, 2018.
From website: "Note that the eXpress software is also no longer being developed. We recommend you use kallisto instead." Kallisto can be found at http://pachterlab.github.io/kallisto/.

Software for streaming quantification for high-throughput DNA/RNA sequencing.
Can be used in any application where abundances of target sequences need to be estimated from short reads sequenced from them.

Proper citation: eXpress (RRID:SCR_006873) Copy   

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http://genome.ucsc.edu/ENCODE

Encyclopedia of DNA elements consisting of list of functional elements in human genome, including elements that act at protein and RNA levels, and regulatory elements that control cells and circumstances in which gene is active. Enables scientific and medical communities to interpret role of human genome in biology and disease. Provides identification of common cell types to facilitate integrative analysis and new experimental technologies based on high-throughput sequencing. Genome Browser containing ENCODE and Epigenomics Roadmap data. Data are available for entire human genome.

Proper citation: ENCODE (RRID:SCR_006793) Copy   

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http://www.1000genomes.org/

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

Proper citation: 1000 Genomes: A Deep Catalog of Human Genetic Variation (RRID:SCR_006828) Copy   

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http://cistrome.org

Web based integrative platform for transcriptional regulation studies.

Proper citation: Cistrome (RRID:SCR_000242) Copy   

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http://megasoftware.net/

Software integrated tool for conducting automatic and manual sequence alignment, inferring phylogenetic trees, mining web based databases, estimating rates of molecular evolution, and testing evolutionary hypotheses. Used for comparative analysis of DNA and protein sequences to infer molecular evolutionary patterns of genes, genomes, and species over time. MEGA version 4 expands on existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. MEGA version 6 enables inference of timetrees, as it implements RelTime method for estimating divergence times for all branching points in phylogeny.

Proper citation: MEGA (RRID:SCR_000667) Copy   

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http://www.genome.wisc.edu/

The E. coli Genome Project has the goal of completely sequencing the E. coli and human genomes. They began isolation of an overlapping lambda clonebank of E. coli K-12 strain MG1655. Those clones served as the starting material in our initial efforts to sequence the whole genome. Improvements in sequencing technology have since reached the point where whole-genome sequencing of microbial genomes is routine, and the human genome has in fact been completed. They initiated additional sequencing efforts, concentrating on pathogenic members of the family Enterobacteriaceae -- to which E. coli belongs. They also began a systematic functional characterization of E. coli K-12 genes and their regulation, using the whole genome sequence to address how the over 4000 genes of this organism act together to enable its survival in a wide range of environments.

Proper citation: E. coli Genome project (RRID:SCR_008139) Copy   

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http://www.hgsc.bcm.tmc.edu/content/bovine-genome-project

Downloadable files of the bos taurus genome. Draft assemblies available for download as contigs or linearized scaffolds of the genomic sequence of cow, Bos taurus, including the final draft assembly (7.1 coverage) and the two previous assemblies. The genome is sequenced to 6- to 8-fold sequence depth, with high-quality finished sequence in some areas. Accompanying EST and SNP analyses is also included. The bovine genome assembly and analysis and the study of cattle genetic history were published in April 24, 2009 issue of Science. The Human Genome Sequencing Center provides BLAST searches of the genome assemblies, either as contigs or as linearized chromosome sequences. The WGS sequence enriched BAC assemblies and the unassembled reads (sequencing reads that did not end up in the genome assembly) can also be searched by BLAST. Traces are available from the NCBI Trace Archive by using the link in the sidebar or by using NCBI MegaBLAST with a same species or cross species query.

Proper citation: Bovine Genome Project (RRID:SCR_008370) Copy   

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http://mged.sourceforge.net/ontologies/MGEDontology.php

An ontology including concepts, definitions, terms, and resources for a standardized description of a microarray experiment in support of MAGE v.1. The MGED ontology is divided into the MGED Core ontology which is intended to be stable and in synch with MAGE v.1; and the MGED Extended ontology which adds further associations and classes not found in MAGE v.1. These terms will enable structure queries of elements of the experiments. Furthermore, the terms will also enable unambiguous descriptions of how the experiment was performed.

Proper citation: MGED Ontology (RRID:SCR_004484) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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://smd.princeton.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 17, 2021. Database to store, annotate, view, analyze and share microarray data. It provides registered users access to their own data, provides users access to public data, and tools with which to analyze those data, to any public user anywhere in the world. The GenePattern software package has been incorporated directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability. SMD search options allow the user to Search By Experiments, Search By Datasets, or Search By Gene Names. Web services are provided using common standards, such as Simple Object Access Protocol (SOAP). This enables both local and remote researchers to connect to an installation of the database and retrieve data using pre-defined methods, without needing to resort to use of a web browser.

Proper citation: SMD (RRID:SCR_004987) Copy   

•   Source: SciCrunch Registry

https://CivicDb.org

Open-access, community-driven knowledgebase designed to crowdsource and curate evidence on the clinical significance of cancer-related genomic variants. It helps researchers and clinicians interpret tumor DNA mutations to guide precision medicine.

Proper citation: CivicDb (RRID:SCR_028055) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/sites/GeneTests/lab

The GeneTests Web site, a publicly funded medical genetics information resource developed for physicians, other healthcare providers, and researchers, is available at no cost to all interested persons. By providing current, authoritative information on genetic testing and its use in diagnosis, management, and genetic counseling, GeneTests promotes the appropriate use of genetic services in patient care and personal decision making. At This Site: * GeneReviews: Expert-authored peer-reviewed disease descriptions * Laboratory Directory: International directory of genetic testing laboratories * Clinic Directory: International directory of genetics and prenatal diagnosis clinics * Educational Materials: Illustrated glossary, information on genetic services, PowerPoint presentations, annotated Internet resources We comply with the HONcode standard for trustworthy health information.

Proper citation: GeneTests (RRID:SCR_010725) Copy   

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https://github.com/macs3-project/MACS

Software Python package for identifying transcript factor binding sites. Used to evaluate significance of enriched ChIP regions. Improves spatial resolution of binding sites through combining information of both sequencing tag position and orientation. Can be used for ChIP-Seq data alone, or with control sample with increase of specificity.

Proper citation: MACS (RRID:SCR_013291) Copy   

•   Source: SciCrunch Registry

http://www.wormbase.org

Central data repository for nematode biology including complete genomic sequence, gene predictions and orthology assignments from range of related nematodes.Data concerning genetics, genomics and biology of C. elegans and related nematodes. Derived from initial ACeDB database of C. elegans genetic and sequence information, WormBase includes genomic, anatomical and functional information of C. elegans, other Caenorhabditis species and other nematodes. Maintains public FTP site where researchers can find many commonly requested files and datasets, WormBase software and prepackaged databases.

Proper citation: WormBase (RRID:SCR_003098) Copy   

•   Source: SciCrunch Registry

http://www.bioperl.org

BioPerl is a community effort to produce Perl code which is useful in biology. This toolkit of perl modules is useful in building bioinformatics solutions in Perl. It is built in an object-oriented manner so that many modules depend on each other to achieve a task. The collection of modules in the bioperl-live repository consist of the core of the functionality of bioperl. Additionally auxiliary modules for creating graphical interfaces (bioperl-gui), persistent storage in RDMBS (bioperl-db), running and parsing the results from hundreds of bioinformatics applications (Run package), software to automate bioinformatic analyses (bioperl-pipeline) are all available as Git modules in our repository. The BioPerl toolkit provides a library of hundreds of routines for processing sequence, annotation, alignment, and sequence analysis reports. It often serves as a bridge between different computational biology applications assisting the user to construct analysis pipelines. This chapter illustrates how BioPerl facilitates tasks such as writing scripts summarizing information from BLAST reports or extracting key annotation details from a GenBank sequence record. BioPerl includes modules written by Sohel Merchant of the GO Consortium for parsing and manipulating OBO ontologies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: BioPerl (RRID:SCR_002989) Copy   

•   Source: SciCrunch Registry

http://www.bioontology.org

Organization that provides biomedical researchers with online tools and a web portal enabling them to access, review, and integrate disparate ontological resources in all aspects of biomedical investigation and clinical practice. A major focus of the work involves the use of biomedical ontologies to aid in the management and analysis of data derived from complex experiments.

Proper citation: National Center for Biomedical Ontology (RRID:SCR_003304) Copy   

•   Source: SciCrunch Registry

https://seahorse.networkmedicine.org

Web-based database and search tool for exploratory data analysis in which we have pre-computed statistical associations between available data elements. Large-scale, open-access data sets such as the Genotype Tissue Expression Project (GTEx) and The Cancer Genome Atlas (TCGA) include multi-omic data on large numbers of samples along with extensive clinical and phenotypic information. Allows users to explore significant associations using tabulated summary statistics, data visualizations, and functional enrichment analyses (using RNA-seq data) for identified sets of genes.

Proper citation: SEAHORSE (RRID:SCR_027399) Copy   

•   Source: SciCrunch Registry