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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   

•   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

https://github.com/Teichlab/tracer

Software application for recovery of T cell receptor (TCR) data from single cell data. Used to reconstruct full-length, paired T cell receptor (TCR) sequences from T lymphocyte single-cell RNA sequence data. Links T cell specificity with functional response by revealing clonal relationships between cells alongside their transcriptional profiles.

Proper citation: TraCeR (RRID:SCR_016338) Copy   

•   Source: SciCrunch Registry

https://github.com/xavierdidelot/clonalorigin

Software package for comparative analysis of the sequences of a sample of bacterial genomes in order to reconstruct the recombination events that have taken place in their ancestry.

Proper citation: ClonalOrigin (RRID:SCR_016061) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/artemis/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Free genome browser and annotation tool that allows visualization of sequence features, next generation data and the results of analyses within the context of the sequence, and also its six-frame translation. Artemis is free software and is distributed under the terms of the GNU General Public License. Artemis is written in Java, and is available for UNIX, Macintosh and Windows systems. It can read EMBL and GENBANK database entries or sequence in FASTA, indexed FASTA or raw format. Other sequence features can be in EMBL, GENBANK or GFF format.

Proper citation: Artemis: Genome Browser and Annotation Tool (RRID:SCR_004267) Copy   

•   Source: SciCrunch Registry

http://svmerge.sourceforge.net/

Software pipeline to detect structural variants (SVs) by integrating calls from several existing SV callers, which are then validated and the breakpoints refined using local de novo assembly. The output is in BED format allowing for easy downstream analysis or viewing in a genome browser. It is modular and extensible allowing new callers to be incorporated as they become available.

Proper citation: SVMerge (RRID:SCR_004777) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/lookseq/

A web-based application for alignment visualization, browsing and analysis of genome sequence data.

Proper citation: LookSeq (RRID:SCR_005625) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/cnd/

A program to detect copy number variants from short read sequence data.

Proper citation: CnD (RRID:SCR_010818) Copy   

•   Source: SciCrunch Registry

https://github.com/wtsi-npg/Illuminus

A fast and accurate algorithm for assigning single nucleotide polymorphism (SNP) genotypes to microarray data from the Illumina BeadArray technology.

Proper citation: ILLUMINUS (RRID:SCR_000388) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/science/tools/carol

Software application that is a combined functional annotation score of non-synonymous coding variants. A major challenge in interpreting whole-exome data is predicting which of the discovered variants are deleterious or neutral. To address this question in silico, they have developed a score called Combined Annotation scoRing toOL (CAROL), which combines information from two bioinformatics tools: PolyPhen-2 and SIFT, in order to improve the prediction of the effect of non-synonymous coding variants. The combination of annotation tools can help improve automated prediction of whole-genome/exome non-synonymous variant functional consequences. (entry from Genetic Analysis Software) The software should run on any UNIX or GNU/Linux system.

Proper citation: CAROL (RRID:SCR_001800) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/science/tools/dindel

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 7,2024. Software program for calling small indels from short-read sequence data ("next generation sequence data"). It is currently designed to handle only Illumina data. Dindel takes BAM files with mapped Illumina read data and enables researchers to detect small indels and produce a VCF file of all the variant calls. It has been written in C++ and can be used on Linux-based and Mac computers (it has not been tested on Windows operating systems).

Proper citation: DINDEL (RRID:SCR_001827) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/dnaplotter/

Software application used to generate images of circular and linear DNA maps to display regions and features of interest. The images can be inserted into a document or printed out directly. As this uses Artemis it can read in the common file formats EMBL, GenBank and GFF3.

Proper citation: DNAPlotter (RRID:SCR_005006) Copy   

•   Source: SciCrunch Registry

http://www.ensembl.org/

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   

•   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.sanger.ac.uk/genetics/CGP/Software/AutoCSA/

AutoCSA (Automatic Comparative Sequence Analysis) is a mutation detection program designed to detect small mutations (1-50 bases) in sequence traces. The software is capable of detecting both homozygous and heterozygous base substitutions, as well as small insertions and deletions, to a high sensitivity. It has specifically been written with high throughput environments in mind, so it is easy to automate the analysis of large amounts of data with little manual intervention. AutoCSA is written in java and will run under java 1.4 or later versions which must be downloaded and installed on your computer. It should be emphasised that AutoCSA uses the raw sequence channels from the trace files generated by the ABI sequencers (.ab1 file extension). Traces which have been processed and the raw channels removed are not suitable for use with the software. The software has been tested successfully under Linux, MS windows XP, and Mac OS X 10.

Proper citation: AutoCSA (Automatic Comparative Sequence Analysis) (RRID:SCR_010616) Copy   

•   Source: SciCrunch Registry

https://cellmodelpassports.sanger.ac.uk/

Hub for clinical, genetic and functional datasets of preclinical cancer models.Provides details of cell model relationships, patient and clinical information, as well as access to associated genetic and functional datasets. Passports database contains curated details and standardized annotation for cell models, including cancer organoid cultures. Users can navigate database via tissue, cancer-type, genetic feature and data availability to select model. REST-API provides programmatic data access and exploration.

Proper citation: Cell Model Passports (RRID:SCR_027682) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/vagrent/

Software tool set for calculating the biological consequences of genomic variations. The suite of perl modules compares genomic variations with reference genome annotations and generates the possible effects each variant may have on the transcripts it overlaps. It evaluates each variation/transcript combination and describes the effects in the mRNA, CDS and protein sequence contexts. It provides details of the sequence and position of the change within the transcript / protein as well as Sequence Ontology terms to classify its consequences.

Proper citation: VAGrENT (RRID:SCR_005180) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/science/tools/seqtools

Software for sequence alignments that displays multiple match sequences aligned against a single genomic reference sequence. It can be used for manipulation, display and annotation of genomic data, to check the quality of an alignment, to find missing/misaligned sequence, and to identify splice sites and polyA sites.

Proper citation: Blixem (RRID:SCR_015994) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://decipher.sanger.ac.uk/

Interactive database which incorporates a suite of tools designed to aid the interpretation of submicroscopic chromosomal imbalance. Used to enhance clinical diagnosis by retrieving information from bioinformatics resources relevant to the imbalance found in the patient. Contributing to the DECIPHER database is a Consortium, comprising an international community of academic departments of clinical genetics. Each center maintains control of its own patient data (which are password protected within the center''''s own DECIPHER project) until patient consent is given to allow anonymous genomic and phenotypic data to become freely viewable within Ensembl and other genome browsers. Once data are shared, consortium members are able to gain access to the patient report and contact each other to discuss patients of mutual interest, thus facilitating the delineation of new microdeletion and microduplication syndromes.

Proper citation: DECIPHER (RRID:SCR_006552) Copy   

•   Source: SciCrunch Registry