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http://www.alliancegenome.org/

Organization that aims to develop and maintain sustainable genome information resources to promote understanding of the genetic and genomic basis of human biology, health, and disease. The Alliance is composed of FlyBase, Mouse Genome Database (MGD), the Gene Ontology Consortium (GOC), Saccharomyces Genome Database (SGD), Rat Genome Database (RGD), WormBase, and the Zebrafish Information Network (ZFIN).

Proper citation: Alliance of Genome Resources (RRID:SCR_015850) Copy   

•   Source: SciCrunch Registry

https://www.metanetx.org/

Web application to perform automated model construction and genome annotation for large-scale metabolic networks. Platform for accessing, analyzing and manipulating genome-scale metabolic networks (GSM) as well as biochemical pathways.

Proper citation: MetaNetX (RRID:SCR_015882) Copy   

•   Source: SciCrunch Registry

http://www.vicbioinformatics.com/software.barrnap.shtml

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software to predict the location of ribosomal RNA genes in genomes. It supports bacteria, archaea, mitochondria, and eukaryotes. It takes FASTA DNA sequence as input, writes GFF3 as output, and supports multithreading., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Barrnap (RRID:SCR_015995) Copy   

•   Source: SciCrunch Registry

http://standage.github.io/AEGeAn

Software toolkit for the analysis and evaluation of genome annotations. The toolkit includes a variety of analysis programs, e.g. for comparing distinct sets of gene structure annotations (ParsEval), computation of gene loci (LocusPocus) and more.

Proper citation: Aegean (RRID:SCR_015965) Copy   

•   Source: SciCrunch Registry

https://github.com/EvolBioInf/andi

Software tool for rapidly computing and estimating evolutionary distance between closely related genomes. Because andi does not compute full alignments it scales even up to thousands of bacterial genomes.

Proper citation: andi (RRID:SCR_015971) Copy   

•   Source: SciCrunch Registry

https://github.com/thackl/cross-species-scaffolding

Software that generates in silico mate-pair reads from single-/paired-end reads of your organism of interest, and a closely related reference genome. It can improve draft genomes by using preferred scaffolding software with the newly created read data. Software that generates in silico mate-pair reads from single-/paired-end reads of your organism of interest, and a closely related reference genome. It can improve draft genomes by using preferred scaffolding software with the newly created read data. Super-scaffolding of draft genome assemblies with in silico mate-pair libraries derived from (closely) related references.

Proper citation: Cross-species scaffolding (RRID:SCR_015932) Copy   

•   Source: SciCrunch Registry

https://github.com/harry-thorpe/piggy

Pipeline for analyzing intergenic regions in bacteria. It is designed to be used in conjunction with Roary (https://github.com/sanger-pathogens/Roary).

Proper citation: Piggy (RRID:SCR_015941) Copy   

•   Source: SciCrunch Registry

https://github.com/PacificBiosciences/FALCON

Software package for aligning long sequencing reads as a diploid-aware genome assembler. Used for assembling non-inbred or rearranged heterozygous genomes.

Proper citation: Falcon (RRID:SCR_016089) Copy   

•   Source: SciCrunch Registry

http://baderlab.org/Software/EnrichmentMap

Source code of a Cytoscape plugin for functional enrichment visualization. It organizes gene-sets, such as pathways and Gene Ontology terms, into a network to reveal which mutually overlapping gene-sets cluster together.

Proper citation: EnrichmentMap (RRID:SCR_016052) Copy   

•   Source: SciCrunch Registry

http://www.xavierdidelot.xtreemhost.com/clonalframe.htm

Software package for the inference of bacterial microevolution using multilocus sequence data. It is used to identify the clonal relationships between the members of a sample, while also estimating the chromosomal position of homologous recombination events that have disrupted the clonal inheritance.

Proper citation: Clonalframe (RRID:SCR_016060) Copy   

•   Source: SciCrunch Registry

http://zzlab.net/blink/index.html

Software for next level of genome wide association studies with both individuals and markers in millions. The method releases the requirement that causative genes are evenly distributed on genome and consequently boosts statistical power.

Proper citation: BLINK (RRID:SCR_016288) Copy   

•   Source: SciCrunch Registry

https://sanger-pathogens.github.io/gubbins/

Software application as an algorithm that iteratively identifies loci containing elevated densities of base substitutions while concurrently constructing a phylogeny based on the putative point mutations outside of these regions. It is used for phylogenetic analysis of genome sequences and generating highly accurate reconstructions under realistic models of short-term bacterial evolution., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Gubbins (RRID:SCR_016131) Copy   

•   Source: SciCrunch Registry

http://www.omicsbean.cn

Software tool for multi-omics data analysis that can perform complex and personalized analysis. Network regulation and molecular mechanism models can be customized according to the requirements of the users.

Proper citation: OmicsBean (RRID:SCR_016322) Copy   

•   Source: SciCrunch Registry

https://github.com/Sung-Huan/ANNOgesic

Software tool for bacterial/archaeal RNA-Seq based genome annotations. Used for integrating, detecting, predicting, and grouping RNA-Seq data.

Proper citation: ANNOgesic (RRID:SCR_016326) Copy   

•   Source: SciCrunch Registry

https://omabrowser.org/oma/

Web based database interface for orthology prediction for the inference of orthologs among complete genomes. Used to relate genes across many species., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: OMA Orthology database (RRID:SCR_016425) Copy   

•   Source: SciCrunch Registry

https://github.com/MRCIEU/PhenoSpD

Software toolkit for phenotypic correlation estimation and multiple testing correction (Spectral Decomposition, SpD) for human phenome using genome-wide association study (GWAS) summary statistics. It is a command line R based tool.

Proper citation: PhenoSpD (RRID:SCR_016359) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/bioinformatics/GENEVITO/

A JAVA-based computer application that serves as a workbench for genome-wide analysis through visual interaction. GeneViTo offers an inspectional view of genomic functional elements, concerning data stemming both from database annotation and analysis tools for an overall analysis of existing genomes. The application deals with various experimental information concerning both DNA and protein sequences (derived from public sequence databases or proprietary data sources) and meta-data obtained by various prediction algorithms, classification schemes or user-defined features. Interaction with a Graphical User Interface (GUI) allows easy extraction of genomic and proteomic data referring to the sequence itself, sequence features, or general structural and functional features. Emphasis is laid on the potential comparison between annotation and prediction data in order to offer a supplement to the provided information, especially in cases of poor annotation, or an evaluation of available predictions. Moreover, desired information can be output in high quality JPEG image files for further elaboration and scientific use. GeneViTo has already been applied to visualize the genomes of two microbial organisms: the bacterion Chlamydia trachomatis and the archaeon Methanococcus jannaschii. The application is compatible with Linux or Windows ME-2000-XP operating systems, provided that the appropriate Java Runtime Environment (Java 1.4.1) is already installed in the system.

Proper citation: GeneVito (RRID:SCR_006211) Copy   

•   Source: SciCrunch Registry

http://www.ddduk.org/

The Deciphering Developmental Disorders (DDD) study aims to find out if using new genetic technologies can help doctors understand why patients get developmental disorders. To do this we have brought together doctors in the 23 NHS Regional Genetics Services throughout the UK and scientists at the Wellcome Trust Sanger Institute, a charitably funded research institute which played a world-leading role in sequencing (reading) the human genome. The DDD study involves experts in clinical, molecular and statistical genetics, as well as ethics and social science. It has a Scientific Advisory Board consisting of scientists, doctors, a lawyer and patient representative, and has received National ethical approval in the UK. Over the next few years, we are aiming to collect DNA and clinical information from 12,000 undiagnosed children in the UK with developmental disorders and their parents. The results of the DDD study will provide a unique, online catalogue of genetic changes linked to clinical features that will enable clinicians to diagnose developmental disorders. Furthermore, the study will enable the design of more efficient and cheaper diagnostic assays for relevant genetic testing to be offered to all such patients in the UK and so transform clinical practice for children with developmental disorders. Over time, the work will also improve understanding of how genetic changes cause developmental disorders and why the severity of the disease varies in individuals. The Sanger Institute will contribute to the DDD study by performing genetic analysis of DNA samples from patients with developmental disorders, and their parents, recruited into the study through the Regional Genetics Services. Using microarray technology and the latest DNA sequencing methods, research teams will probe genetic information to identify mutations (DNA errors or rearrangements) and establish if these mutations play a role in the developmental disorders observed in patients. The DDD initiative grew out of the groundbreaking DECIPHER database, a global partnership of clinical genetics centres set up in 2004, which allows researchers and clinicians to share clinical and genomic data from patients worldwide. The DDD study aims to transform the power of DECIPHER as a diagnostic tool for use by clinicians. As well as improving patient care, the DDD team will empower researchers in the field by making the data generated securely available to other research teams around the world. By assembling a solid resource of high-quality, high-resolution and consistent genomic data, the leaders of the DDD study hope to extend the reach of DECIPHER across a broader spectrum of disorders than is currently possible.

Proper citation: Deciphering Developmental Disorders (RRID:SCR_006171) Copy   

•   Source: SciCrunch Registry

http://vizhub.wustl.edu

A visualization hub displaying sequencing data from the Roadmap Epigenomics project. It hosts high volume of tracks from ENCODE and Roadmap Epigenomics projects, supports multiple organisms, visualizes chromatin-interaction data (e.g. Hi-C), performs gene set view, gene plot, and many others. All delivered on the web at high performance.

Proper citation: VizHub (RRID:SCR_006209) Copy   

•   Source: SciCrunch Registry

https://proteomecommons.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A public resource for sharing general proteomics information including data (Tranche repository), tools, and news. Joining or creating a group/project provides tools and standards for collaboration, project management, data annotation, permissions, permanent storage, and publication.

Proper citation: Proteome Commons (RRID:SCR_006234) Copy   

•   Source: SciCrunch Registry