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http://www.genomecanada.ca/

Genome Canada is a non-profit organization that is funded by the Government of Canada. The organization funds large-scale science and technology to fuel innovation regarding genomics in multiple sectors such as health, agriculture and agri-food, forestry, fisheries and aquaculture, environment, energy and mining. They create partnerships at the program and research project levels.

Proper citation: Genome Canada (RRID:SCR_000966) Copy   

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http://patchwork.r-forge.r-project.org/

Software tool for analyzing and visualizing allele-specific copy numbers and loss-of-heterozygosity in cancer genomes. The data input is in the format of whole-genome sequencing data which enables characterization of genomic alterations ranging in size from point mutations to entire chromosomes. High quality results are obtained even if samples have low coverage, ~4x, low tumor cell content or are aneuploid. Patchwork takes BAM files as input whereas PatchworkCG takes input from CompleteGenomics files. TAPS performs the same analysis as Patchwork but for microarray data.

Proper citation: Patchwork (RRID:SCR_000072) Copy   

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http://exon.gatech.edu/paul/unsplicer/index.htm

An RNA-seq alignment program that provides alignment of short reads to a reference genome. The program requires two inputs that are provided by the output of GeneMark-ES: HMM model parameters and ab initio gene predictions. UnSplicer is a sister pipeline to TrueSight.

Proper citation: UnSplicer (RRID:SCR_000226) 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://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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https://gemini.readthedocs.io/en/latest/

Framework for exploring genetic variation in the context of the genome annotations available for the human genome. Users can load a VCF file into a database and each variant is automatically annotated by comparing it to several genome annotations from source such as ENCODE tracks, UCSC tracks, OMIM, dbSNP, KEGG, and HPRD.

Proper citation: GEMINI (RRID:SCR_014819) Copy   

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http://www.sanger.ac.uk/

Non profit research organization for genome sequences to advance understanding of biology of humans and pathogens in order to improve human health globally. Provides data which can be translated for diagnostics, treatments or therapies including over 100 finished genomes, which can be downloaded. Data are publicly available on limited basis, and provided more extensively upon request.

Proper citation: Wellcome Trust Sanger Institute; Hinxton; United Kingdom (RRID:SCR_011784) Copy   

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http://www.genestack.com

A universal collaborative platform for bioinformatics application development that allows users to store and share large data sets securely within and across organizations, with free access to public data from major databases. The platform includes open-source and proprietary genomics applications, working together independent of file formats. For developers an SDK, APIs and a marketplace are provided.

Proper citation: Genestack (RRID:SCR_011885) Copy   

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http://www.genboree.org/java-bin/EpigenomeAtlas/workbench.jsp?isPublic=yes&context=EpigenomeAtlas

Service where users are able to upload and store data, access bioinformatics tools, and perform analyses.

Proper citation: Genboree Workbench (RRID:SCR_011864) Copy   

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http://bioinfo-out.curie.fr/projects/snp_gap/

Software for automatic detection of absolute segmental copy numbers and genotype status in complex cancer genome profiles measured by single-nucleotide polymorphism (SNP) arrays. The method is based on pattern recognition of segmented and smoothed copy number and allelic imbalance profiles. The method performs well even for poor-quality data, low tumor content, and highly rearranged tumor genomes.

Proper citation: Genome Alteration Print (RRID:SCR_012016) Copy   

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https://bitbucket.org/nsegata/phylophlan/wiki/Home

Software pipeline for reconstructing highly accurate and resolved phylogenetic trees based on whole-genome sequence information. Pipeline is scalable to thousands of genomes and uses the most conserved 400 proteins for extracting the phylogenetic signal. PhyloPhlAn also implements taxonomic curation, estimation, and insertion operations., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PhyloPhlAn (RRID:SCR_013082) Copy   

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http://ctb.pku.edu.cn/main/SheGroup/Software/MED2.htm

A non-supervised gene prediction algorithm for prokaryotic genomes with multivariate entropy distance method.

Proper citation: MED (RRID:SCR_013403) Copy   

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http://cancergenome.nih.gov/

Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).

Proper citation: The Cancer Genome Atlas (RRID:SCR_003193) Copy   

•   Source: SciCrunch Registry

http://ki.se/en/meb/twingene-and-genomeeutwin

In collaboration with GenomeEUtwin, the TwinGene project investigates the importance of quantitative trait loci and environmental factors for cardiovascular disease. It is well known that genetic factors are of considerable importance for some familial lipid syndromes and that Type A Behavior pattern and increased lipid levels infer increased risk for cardiovascular disease. It is furthermore known that genetic factors are of importance levels of blood lipid biomarkers. The interplay of genetic and environmental effects for these risk factors in a normal population is less well understood and virtually unknown for the elderly. In the TwinGene project twins born before 1958 are contacted to participate. Health and medication data are collected from self-reported questionnaires, and blood sampling material is mailed to the subject who then contacts a local health care center for blood sampling and a health check-up. In the simple health check-up, height, weight, circumference of waist and hip, and blood pressure are measured. Blood is sampled for DNA extraction, serum collection and clinical chemistry tests of C-reactive protein, total cholesterol, triglycerides, HDL and LDL cholesterol, apolipo��protein A1 and B, glucose and HbA1C. The TwinGene cohort contains more than 10000 of the expected final number of 16000 individuals. Molecular genetic techniques are being used to identify Quantitative Trait Loci (QTLs) for cardiovascular disease and biomarkers in the TwinGene participants. Genome-wide linkage and association studies are ongoing. DZ twins have been genome-scanned with 1000 STS markers and a subset of 300 MZ twins have been genome-scanned with Illumina 317K SNP platform. Association of positional candidate SNPs arising from these genomscans are planned. The TwinGene project is associated with the large European collaboration denoted GenomEUtwin (www.genomeutwin.org, see below) which since 2002 has aimed at gathering genetic data on twins in Europe and setting up the infrastructure needed to enable pooling of data and joint analyses. It has been the funding source for obtaining the genome scan data. Types of samples: * EDTA whole blood * DNA * Serum Number of sample donors: 12 044 (sample collection completed)

Proper citation: KI Biobank - TwinGene (RRID:SCR_006006) Copy   

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http://www.informatics.jax.org/batch_data.shtml

Software tool to access various mouse genome information in batch format. Batch data and analysis tools.

Proper citation: Batch Data and Analysis Tool (RRID:SCR_017515) Copy   

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http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

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http://hugenavigator.net/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023. Knowledge base of genetic associations and human genome epidemiology including information on population prevalence of genetic variants, gene-disease associations, gene-gene and gene- environment interactions, and evaluation of genetic tests. This tool explores HuGENet, the Human Genome Epidemiology Network, which is a global collaboration of individuals and organizations committed to the assessment of the impact of human genome variation on population health and how genetic information can be used to improve health and prevent disease. What does HuGE Navigator offer? *HuGEpedia - an encyclopedia of human genetic variation in health and disease, includes, Phenopedia and Genopedia. Phenopedia allows you to look up gene-disease association summaries by disease, and Genopedia allows you to look up gene-disease association summaries by gene. In general, HuGEpedia is a searchable database that summarizes published articles about human disease and genetic variation, including primary studies, reviews, and meta-analyses. It provides links to Pubmed abstracts, researcher contact info, trends, and more. *HuGEtools - searching and mining the literature in human genome epidemiology, includes, HuGE Literature Finder, HuGE Investigator Browser, Gene Prospector, HuGE Watch, Variant Name Mapper, and HuGE Risk Translator. *HuGE Literature Finder finds published articles in human genome epidemiology since 2001. The search query can include genes, disease, outcome, environmental factors, author, etc. Results can be filtered by these categories. It is also possible to see all articles in the database for a particular topic, such as genotype prevalence, pharmacogenomics, or clinical trial. *HuGE Investigator Browser finds investigators in a particular field of human genome epidemiology. This info is obtained using a behind-the-scenes tool that automatically parses PubMed affiliation data. *Gene Prospector is a gateway for evaluating genes in relation to disease and risk factors. This tool allows you to enter a disease or risk factor and then supplies you with a table of genes associated w/your query that are ranked based on strength of evidence from the literature. This evidence is culled from the HuGE Literature Finder and NCBI Entrez Gene - And you're given the scoring formula. The Gene Prospector results table provides access to the Genopedia entry for each gene in the list, general info including links to other resources, SNP info, and associated literature from HuGE, PubMed, GWAS, and more. It is a great place to locate a lot of info about your disease/gene of interest very quickly. *HuGE Watch tracks the evolution of published literature, HuGE investigators, genes studied, or diseases studied in human genome epidemiology. For example, if you search Trend/Pattern for Diseases Studied you'll initially get a graph and chart of the number of diseases studied per year since 1997. You can refine these results by limiting the temporal trend to a category or study type such as Gene-gene Interaction or HuGE Review. *Variant Name Mapper maps common names and rs numbers of genetic variants using information from SNP500Cancer, SNPedia, pharmGKB, ALFRED, AlzGene, PDGene, SZgene, HuGE Navigator, LSDBs, and user submissions. *HuGE Risk Translator calculates the predictive value of genetic markers for disease risk. To do so, users must enter the frequency of risk variant, the population disease risk, and the odds ratio between the gene and disease. This information is necessary in order to yield a useful predictive result. *HuGEmix - a series of HuGE related informatics utilities and projects, includes, GAPscreener, HuGE Track, Open Source. GAPscreener is a screening tool for published literature on human genetic associations; HuGE Track is a custom track built for HuGE data in the UCSC Genome Browser; and Open Source is infrastructure for managing knowledge and information from PubMed.

Proper citation: HuGE Navigator - Human Genome Epidemiology Navigator (RRID:SCR_003172) Copy   

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http://www.xenbase.org/

Data collection for Xenopus laevis and Xenopus tropicalis biology and genomics.

Proper citation: Xenbase (RRID:SCR_003280) Copy   

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https://bioconductor.org/packages/genomation/

Software R package for simplfiying common tasks in genomic feature analysis. Toolkit to summarize, annotate and visualize genomic intervals. Provides functions for reading BED and GFF files as GRanges objects, summarizing genomic features over predefined windows so users can make average enrichment of features over defined regions or produce heatmaps. Can annotate given regions with other genomic features such as exons,introns and promoters.

Proper citation: genomation (RRID:SCR_003435) Copy   

•   Source: SciCrunch Registry