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Statistical software tool for calling common and rare variants in analysis of pool or individual next-generation sequencing data. This software is optimized for analysis of whole-exome sequencing data and whole-genome sequencing data.
Proper citation: SNVer (RRID:SCR_002061) Copy
https://software.broadinstitute.org/gatk/
A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)
Proper citation: GATK (RRID:SCR_001876) Copy
Portal providing access to all JGI genomic databases and analytical tools, sequencing projects and their status, search for and download assemblies and annotations of sequenced genomes, and interactively explore those genomes and compare them with other sequenced microbes, fungi, plants or metagenomes using specialized systems tailored to each particular class of organisms. The Department of Energy (DOE) Joint Genome Institute (JGI) is a national user facility with massive-scale DNA sequencing and analysis capabilities dedicated to advancing genomics for bioenergy and environmental applications. Beyond generating tens of trillions of DNA bases annually, the Institute develops and maintains data management systems and specialized analytical capabilities to manage and interpret complex genomic data sets, and to enable an expanding community of users around the world to analyze these data in different contexts over the web.
Proper citation: JGI Genome Portal (RRID:SCR_002383) Copy
Collection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.
Proper citation: Ensembl (RRID:SCR_002344) Copy
http://www.ncbi.nlm.nih.gov/SNP/
Database as central repository for both single base nucleotide substitutions and short deletion and insertion polymorphisms. Distinguishes report of how to assay SNP from use of that SNP with individuals and populations. This separation simplifies some issues of data representation. However, these initial reports describing how to assay SNP will often be accompanied by SNP experiments measuring allele occurrence in individuals and populations. Community can contribute to this resource.
Proper citation: dbSNP (RRID:SCR_002338) Copy
http://www.yandell-lab.org/software/vaast.html
A probabilistic search tool for identifying damaged genes and their disease-causing variants in personal genome sequences. VAAST combines elements of phylogenetic conservation, amino acid substitution, and aggregative approaches to variant prioritization into a single unified likelihood-framework that allows users to accurately identify damaged genes and deleterious variants. The software can score both coding (SNV, indel and splice site) and non-coding variants (SNV), evaluating the cumulative impact of both types of variants simultaneously. It can identify rare variants causing rare genetic diseases and can also use both rare and common variants to identify genes responsible for common diseases.
Proper citation: VAAST (RRID:SCR_002179) Copy
An open-source, web-based platform and suite of software tools for for sharing heterogeneous scientific research datasets, models or simulations, processes and research outcomes - and collaborations between scientists. It preserves associations between them, along with information about the people and organizations involved. Underpinning SEEK is the ISA infrastructure, a standard format for describing how individual experiments are aggregated into wider studies and investigations. Within SEEK, ISA has been extended and is configurable to allow the structure to be used outside of Biology. SEEK is incorporating semantic technology allowing sophisticated queries over the data, yet without getting in the way of your users. Access to the RESTful API to access the data within SEEK is available.
Proper citation: SEEK (RRID:SCR_002651) Copy
http://rubioseq.sourceforge.net/
Stand-alone and multiplatform application for the integrated analysis of NGS data. It implements pipelines for the analysis of single nucleotide and copy-number variation and bisulfite-seq and ChIP-seq experiments.
Proper citation: RUbioSeq (RRID:SCR_002508) Copy
Framework for identifying, locating, relating, accessing, integrating, and analyzing information from neuroscience research. Users can search for and add neuroscience-related resources at NIF portal and receive and RRID to track and cite resources within scientific manuscripts.
Proper citation: Neuroscience Information Framework (RRID:SCR_002894) Copy
http://hihg.med.miami.edu/software-download/seqem-version-1.0
Online tool for utilizing a genotype calling algorithm for next-generation sequence data.
Proper citation: SeqEM (RRID:SCR_002021) Copy
A centralized sequence database and community resource for Tribolium genetics, genomics and developmental biology containing genomic sequence scaffolds mapped to 10 linkage groups, genetic linkage maps, the official gene set, Reference Sequences from NCBI (RefSeq), predicted gene models, ESTs and whole-genome tiling array data representing several developmental stages. The current version of Beetlebase is built on the Tribolium castaneum 3.0 Assembly (Tcas 3.0) released by the Human Genome Sequencing Center at the Baylor College of Medicine. The database is constructed using the upgraded Generic Model Organism Database (GMOD) modules. The genomic data is stored in a PostgreSQL relational database using the Chado schema and visualized as tracks in GBrowse. The genetic map is visualized using the comparative genetic map viewer CMAP. To enhance search capabilities, the BLAST search tool has been integrated with the GMOD tools. Tribolium castaneum is a very sophisticated genetic model organism among higher eukaryotes. As the member of a primitive order of holometabolous insects, Coleoptera, Tribolium is in a key phylogenetic position to understand the genetic innovations that accompanied the evolution of higher forms with more complex development. Coleoptera is also the largest and most species diverse of all eukaryotic orders and Tribolium offers the only genetic model for the profusion of medically and economically important species therein. The genome sequences may be downloaded.
Proper citation: BeetleBase (RRID:SCR_001955) Copy
Software package that functions as a de novo genome assembler based on the concept of string graphs. It is designed as a modular set of programs used to assemble large genomes from high coverage short read data.
Proper citation: SGA (RRID:SCR_001982) Copy
http://research-pub.gene.com/gmap/
Software to align single and paired end reads as short as 14 nt and of arbitrarily long length. Can detect short and long distance splicing, including interchromosomal splicing, in individual reads, using probabilistic models or database of known splice sites. Permits SNP-tolerant alignment to reference space of all possible combinations of major and minor alleles, and can align reads from bisulfite-treated DNA for study of methylation state.
Proper citation: GSNAP (RRID:SCR_005483) Copy
http://www.emouseatlas.org/emage
A database of in situ gene expression data in the developing mouse embryo and an accompanying suite of tools to search and analyze the data. mRNA in situ hybridization, protein immunohistochemistry and transgenic reporter data is included. The data held is spatially annotated to a framework of 3D mouse embryo models produced by EMAP (e-Mouse Atlas Project). These spatial annotations allow users to query EMAGE by spatial pattern as well as by gene name, anatomy term or Gene Ontology (GO) term. The conceptual framework which houses the descriptions of the gene expression patterns in EMAGE is the EMAP Mouse Embryo Anatomy Atlas. This consists of a set of 3D virtual embryos at different stages of development, as well as an accompanying ontology of anatomical terms found at each stage. The raw data images can be conventional 2D photographs (of sections or wholemount specimens) or 3D images of wholemount specimens derived from Optical Projection Tomography (OPT) or confocal microscopy. Users may submit data using a Data submission tool or without.
Proper citation: EMAGE Gene Expression Database (RRID:SCR_005391) Copy
http://bioinfo.cs.technion.ac.il/atrhunter/
Software that finds and displays approximate tandem repeats in DNA sequences.
Proper citation: ATRHUNTER (RRID:SCR_006480) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software tool for aligning sequences, similar to BLAST 2 sequences that colour-codes the alignments by reliability. Another useful feature of LAST is that it can compare huge (vertebrate-genome-sized) datasets. Unfortunately, this only applies to the downloadable version of LAST, not the web service. The web service can just about handle bacterial genomes, but it will take a few minutes and the output will be large. LAST can: * Handle big sequence data, e.g: ** Compare two vertebrate genomes ** Align billions of DNA reads to a genome * Indicate the reliability of each aligned column. * Use sequence quality data properly. * Compare DNA to proteins, with frameshifts. * Compare PSSMs to sequences * Calculate the likelihood of chance similarities between random sequences. LAST cannot (yet): * Do spliced alignment., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: LAST (RRID:SCR_006119) Copy
Web-based tool for the ontological analysis of large lists of genes. It can be used to determine biological annotations or combinations of annotations that are significantly associated to a list of genes under study with respect to a reference list. As well as single annotations, this tool allows users to simultaneously evaluate annotations from different sources, for example Biological Process and Cellular Component categories of Gene Ontology., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: GeneCodis (RRID:SCR_006943) Copy
http://www.ncbi.nlm.nih.gov/clinvar/
Archive of aggregated information about sequence variation and its relationship to human health. Provides reports of relationships among human variations and phenotypes along with supporting evidence. Submissions from clinical testing labs, research labs, locus-specific databases, expert panels and professional societies are welcome. Collects reports of variants found in patient samples, assertions made regarding their clinical significance, information about submitter, and other supporting data. Alleles described in submissions are mapped to reference sequences, and reported according to HGVS standard.
Proper citation: ClinVar (RRID:SCR_006169) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A database of candidate genes for mapped inherited human diseases. Candidate priorities are automatically established by a data mining algorithm that extracts putative genes in the chromosomal region where the disease is mapped, and evaluates their possible relation to the disease based on the phenotype of the disorder. Data analysis uses a scoring system developed for the possible functional relations of human genes to genetically inherited diseases that have been mapped onto chromosomal regions without assignment of a particular gene. Methodology can be divided in two parts: the association of genes to phenotypic features, and the identification of candidate genes on a chromosonal region by homology. This is an analysis of relations between phenotypic features and chemical objects, and from chemical objects to protein function terms, based on the whole MEDLINE and RefSeq databases.
Proper citation: Candidate Genes to Inherited Diseases (RRID:SCR_008190) Copy
https://sourceforge.net/projects/fraggenescan/
A software application for finding fragmented genes in short reads and may be applied to predict prokaryotic genes in incomplete assemblies or complete genomes.
Proper citation: FragGeneScan (RRID:SCR_011929) Copy
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