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http://www.lgm.upmc.fr/parseq/

Statistical software for transcription landscape reconstruction at a basepair resolution from RNA Seq read counts. It is based on a state-space model which describes, in terms of abrupt shifts and more progressive drifts, the transcription level dynamics along the genome. Alongside variations of transcription level, it incorporates a component of short-range variation to pull apart local artifacts causing correlated dispersion. Reconstruction of the transcription level relies on a conditional sequential Monte Carlo approach that is combined with parameter estimation in a Markov chain Monte Carlo algorithm known as particle Gibbs. The method allows to estimate the local transcription level, to call transcribed regions, and to identify the transcript borders.

Proper citation: Parseq (RRID:SCR_003464) Copy   

•   Source: SciCrunch Registry

https://www.wtccc.org.uk/

Consortium of 50 research groups across the UK to harness the power of newly-available genotyping technologies to improve our understanding of the aetiological basis of several major causes of global disease. The consortium has gathered genotype data for up to 500,000 sites of genome sequence variation (single nucleotide polymorphisms or SNPs) in samples ascertained for the disease phenotypes. Analysis of the genome-wide association data generated has lead to the identification of many SNPs and genes showing evidence of association with disease susceptibility, some of which will be followed up in future studies. In addition, the Consortium has gained important insights into the technical, analytical, methodological and biological aspects of genome-wide association analysis. The core of the study comprised an analysis of 2,000 samples from each of seven diseases (type 1 diabetes, type 2 diabetes, coronary heart disease, hypertension, bipolar disorder, rheumatoid arthritis and Crohn's disease). For each disease, the case samples have been ascertained from sites widely distributed across Great Britain, allowing us to obtain considerable efficiencies by comparing each of these case populations to a common set of 3,000 nationally-ascertained controls also from England, Scotland and Wales. These controls come from two sources: 1,500 are representative samples from the 1958 British Birth Cohort and 1,500 are blood donors recruited by the three national UK Blood Services. One of the questions that the WTCCC study has addressed relates to the relative merits of these alternative strategies for the generation of representative population cohorts. Genotyping for this main Case Control study was conducted by Affymetrix using the (commercial) Affymetrix 500K chip. As part of this study a total of 17,000 samples were typed for 500,000 SNPs. There are two additional components to the study. First, the WTCCC award is part-funding a study of host resistance to infectious diseases in African populations. The same approach has been used to type 2,000 cases of tuberculosis (TB) and 2,000 cases of malaria, as well as 2,000 shared controls. As well as addressing diseases of major global significance, and extending WTCCC coverage into the area of infectious disease, the inclusion of samples of African origin has obvious benefits with respect to methodological aspects of genome-wide association analysis. Second, the WTCCC has, for four additional diseases (autoimmune thyroid disease, breast cancer, ankylosing spondylitis, multiple sclerosis), completed an analysis of 15,000 SNPs designed to represent a large proportion of the known non-synonymous coding SNPs across the genome. This analysis has been performed at the WTSI using a custom Infinium chip (Illumina). Data release The genotypic data of the control samples (1958 British Birth Cohort and UK Blood Service) and from seven diseases analyzed in the main study are now available to qualified researchers. Summary genotype statistics for these collections are available directly from the website. Access to the individual-level genotype data and summary genotype statistics is by application to the Consortium Data Access Committee (CDAC) and approval subject to a Data Access Agreement. WTCCC2: A further round of GWA studies were funded in April 2008. These include 15 WTCCC-collaborative studies and 12 independent studies be supported totaling approximately 120,000 samples. Many of the studies represent major international collaborative networks that have together assembled large sample collections. WTCCC2 will perform genome-wide association studies in 13 disease conditions: Ankylosing spondylitis, Barrett's oesophagus and oesophageal adenocarcinoma, glaucoma, ischaemic stroke, multiple sclerosis, pre-eclampsia, Parkinson's disease, psychosis endophenotypes, psoriasis, schizophrenia, ulcerative colitis and visceral leishmaniasis. WTCCC2 will also investigate the genetics of reading and mathematics abilities in children and the pharmacogenomics of statin response. Over 60,000 samples will be analyzed using either the Affymetrix v6.0 chip or the Illumina 660K chip. The WTCCC2 will also genotype 3,000 controls each from the 1958 British Birth cohort and the UK Blood Service control group, and the 6,000 controls will be genotyped on both the Affymetrix v6.0 and Illumina 1.2M chips. WTCCC3: The Wellcome Trust has provided support for a further round of GWA studies in January 2009. These include 5 WTCCC-collaborative studies to be carried out in WTCCC3 and 5 independent studies, across a range of diseases. Many of the studies represent major international collaborative networks that have together assembled large sample collections. WTCCC3 will perform genome-wide association studies in the following 4 disease conditions: primary biliary cirrhosis, anorexia nervosa, pre-eclampsia in UK subjects, and the interactions between donor and recipient DNA related to early and late renal transplant dysfunction. The WTCCC3 will also carry out a pilot in a study of the genetics of host control of HIV-1 infection. Over 40,000 samples will be analyzed using the Illumina 660K chip. The WTCCC3 will utilize the 6,000 control genotypes generated by the WTCCC2.

Proper citation: Wellcome Trust Case Control Consortium (RRID:SCR_001973) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/tbrowse/

Software providing a HTML5/javascript based browser for visualizing RNA-seq results in the familiar track layout of common genome browser. But given the quantitative nature of RNA-seq data, in addition to visualizing sequence coverage, the browser quantitates transcript abundance across regions of interest. The HTML5 functionality is made of use to render all the tracks using the canvas drawing element. This greatly reduces the load on servers and allows for rich interactive graphics without the need for third-party plugins. Furthermore, this framework completely segregates data from visualization, making development much easier. The browser is designed to run on all modern browsers: Firefox, Safari, Chrome, Opera and Internet Explorer (though not recommended).

Proper citation: tbrowse (RRID:SCR_001918) Copy   

•   Source: SciCrunch Registry

http://www.genoscope.cns.fr/spip/spip.php?lang=en

French national sequencing center with the following resources: * Sequencing ** Genoscope Projects * Environmental genomics ** Microbial diversity in wastewater ** Metabolic genomics * Bioinformatics ** Atelier for comparative genomics ** Computational Systems Biology ** Servers resources *** GGB for Generic Genome Browser: graphic interface for various databases (sequence, annotation, syntenies...) for a given organism. *** MaGe for Magnifying Microbial Genomes: annotation system for microbial genomes.

Proper citation: Genoscope (RRID:SCR_002172) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/science/programs/genome-biology/computational-rd/computational-research-and-development

A software for genome assembly, and is specifically designed to analyze long Sanger-chemistry reads.

Proper citation: ARACHNE (RRID:SCR_000351) Copy   

•   Source: SciCrunch Registry

http://www.scienceexchange.com/facilities/genomics-services-lab

A lab that offers genetic research tools such as RNA sequencing and a variety of arrays.

Proper citation: HudsonAlpha Genomics Services Lab (RRID:SCR_000353) Copy   

•   Source: SciCrunch Registry

http://gmt.genome.wustl.edu/pindel/0.2.4/

Software to detect breakpoints of large deletions, medium sized insertions, inversions, tandem duplications and other structural variants at single-based resolution from next-gen sequence data. It uses a pattern growth approach to identify the breakpoints of these variants from paired-end short reads., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Pindel (RRID:SCR_000560) Copy   

•   Source: SciCrunch Registry

http://paleogenomics.irmacs.sfu.ca/FPSAC/

Sogftware for fast Phylogenetic Scaffolding of Ancient Contigs.

Proper citation: FPSAC (RRID:SCR_000555) Copy   

•   Source: SciCrunch Registry

http://genome.crg.es/software/gfftools/GFF2PS.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software program for visualizing annotations of genomic sequences. The program has features such as the ability to create comprehensive plots, customizable parameters, and flexibility in file format.

Proper citation: Genome BioInformatics Research Lab - gff2ps (RRID:SCR_000462) Copy   

•   Source: SciCrunch Registry

http://www.brown.edu/Research/Istrail_Lab/hapcompass.php

Software that utilizes a fast cycle basis algorithm for the accurate haplotype assembly of sequence data. It is able to create pairwise SNP phasings.

Proper citation: HapCompass (RRID:SCR_000942) Copy   

•   Source: SciCrunch Registry

http://www.iro.umontreal.ca/~csuros/quadgt/

Software package for calling single-nucleotide variants in four sequenced genomes comprising a normal-tumor pair and the two parents. Genotypes are inferred using a joint model of parental variant frequencies, de novo germline mutations, and somatic mutations. The model quantifies the descent-by-modification relationships between the unknown genotypes by using a set of parameters in a Bayesian inference setting. Note that you can use it on any subset of the four related genomes, including parent-offspring trios, and normal-tumor pairs without parental samples.

Proper citation: QuadGT (RRID:SCR_000073) Copy   

•   Source: SciCrunch Registry

http://soap.genomics.org.cn/soapfuse.html

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on August 23,2022. An open source tool developed for genome-wide detection of fusion transcripts from human being paired-end RNA-Seq data. This tool is a part of a larger set of tools to efficiently align oligonucleotides onto reference sequences .

Proper citation: SOAPfuse (RRID:SCR_000078) Copy   

•   Source: SciCrunch Registry

http://www.scienceexchange.com/facilities/edgebio

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. A contract research organization that provides genomics services such as sequencing, bioinformatics, NGS data analysis and whole exome sequencing. EdgeBio is a CLIA-approved service provider.

Proper citation: EdgeBio (RRID:SCR_000183) Copy   

•   Source: SciCrunch Registry

https://github.com/HMPNK/CSA2.6

Software pipeline for high-throughput chromosome level vertebrate genome assembly. Pipeline, which after contig assembly performs post assembly improvements by ordering assembly and closing gaps, as well as splitting of low supported regions.

Proper citation: Chromosome Scale Assembler (RRID:SCR_017960) Copy   

•   Source: SciCrunch Registry

http://zgc.nci.nih.gov/

Part of zebrafish genome project. ZGC project to produce cDNA libraries, clones and sequences to provide complete set of full-length (open reading frame) sequences and cDNA clones of expressed genes for zebrafish. All ZGC sequences are deposited in GenBank and clones can be purchased from distributors of IMAGE consortium. With conclusion of ZGC project in September 2008, GenBank records of ZGC sequences will be frozen, without further updates. Since definition of what constitutes full-length coding region for some of genes and transcripts for which we have ZGC clones will likely change in future, users planning to order ZGC clones will need to monitor for these changes. Users can make use of genome browsers and gene-specific databases, such as UCSC Genome browser, NCBI's Map Viewer, and Entrez Gene, to view relevant regions of genome (browsers) or gene-related information (Entrez Gene).

Proper citation: Zebrafish Gene Collection (RRID:SCR_007054) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/Projects/D_rerio/zmp/

Create knockout alleles in protein coding genes in the zebrafish genome, using a combination of whole exome enrichment and Illumina next generation sequencing, with the aim to cover them all. Each allele created is analyzed for morphological differences and published on the ZMP site. Transcript counting is performed on alleles with a morphological phenotype. Alleles generated are archived and can be requested from this site through the Zebrafish International Resource Center (ZIRC). You may register to receive updates on genes of interest, or browse a complete list, or search by Ensembl ID, gene name or human and mouse orthologue.

Proper citation: ZMP (RRID:SCR_006161) Copy   

•   Source: SciCrunch Registry

http://www.mousephenotype.org/

Center that produces knockout mice and carries out high-throughput phenotyping of each line in order to determine function of every gene in mouse genome. These mice will be preserved in repositories and made available to scientific community representing valuable resource for basic scientific research as well as generating new models for human diseases.

Proper citation: International Mouse Phenotyping Consortium (IMPC) (RRID:SCR_006158) Copy   

•   Source: SciCrunch Registry

http://ccr.coriell.org/Sections/Collections/HuREF/?SsId=78

The Human Reference Genetic Material Repository makes available DNA from a single individual, J. Craig Venter, whose genome has been sequenced and assembled. The DNA samples are prepared from a lymphoblastoid cell line established at Coriell Cell Repositories from a sample of peripheral blood. The DNA samples are available in 50 microgram aliquots. The lymphoblastoid cell line is not available for distribution. The human DNA sample provided is that of J. Craig Venter whose DNA from white blood cells and sperm was sequenced using Sanger chemistry (ABI Capillary Electrophoresis Platforms 3700 and 3730xl), assembled using the Celera Assembler and was published in PLoS Biology . J. Craig Venter, born on 14 October 1946, is a Caucasian male of self-reported European-American ancestry. The data available on this sample, whose genome assembly is referred to as HuRef, includes: * Whole Genome Shotgun Sequencing data * Sequence trace set deposited by JCVI in the NCBI trace archive * Human Genome Browser displaying sequence assembly, DNA variants and gene annotations Additional data sets from this study include: * Full set of Sanger reads used for genome assembly * SNP and insertion/deletion variant on the human genome sequence coordinates (NCBI version 36) * Affymetrix 500K GeneChip data * Illumina HumanHap650Y Genotyping BeadChip data Given the amount of data publicly available the genomic content of this sample, HuRef will be useful as a reference for many genetic studies.

Proper citation: Human Reference Genetic Material Repository (RRID:SCR_004693) Copy   

•   Source: SciCrunch Registry

https://github.com/BackofenLab/HVSeeker/tree/main

Software tool for distinguishing between bacterial and phage sequences. Consists of two separate models: one analyzing DNA sequences and the other focusing on proteins.

Proper citation: HVSeeker (RRID:SCR_026120) Copy   

•   Source: SciCrunch Registry

https://github.com/shendurelab/LACHESIS

Software tool for chromosome scale scaffolding of de novo genome assemblies based on chromatin interactions.Method exploits signal of genomic proximity in Hi-C datasets for ultra long range scaffolding of de novo genome assemblies.

Proper citation: LACHESIS (RRID:SCR_017644) Copy   

•   Source: SciCrunch Registry