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http://www.animalgenome.org/pigs/nagrp.html
Database and resources on the pig genome.
Proper citation: U.S. Pig Genome Project (RRID:SCR_008151) Copy
The objective of this project is to develop physical maps of the sorghum and rice genomes, based on BAC contigs that are cross-linked to each other and also to genetic maps and BAC islands for other large-genome crops and a library of ca. 50,000 expressed-sequence tags (EST''s) and corresponding cDNA clones, from diverse sorghum organs and developmental states. It also aims to improve understanding of genetic diversity and allelic richness that might be harbored ex situ (in gene banks) or in situ (in nature), and refine techniques for assesing allelic richness and Expedite data acquisition and utilization by a sound parnership between laboratory scientists and computational biologists. Specific goals of developing physical maps of sorghum and rice genomes include: -Enrich cross-links between sorghum and rice by mapping additional rice probes on sorghum. -Apply mapped DNA probes to macroarrays of sorghum, sugarcane, rice, and maize BACs. -Fingerprint 10x BAC libraries of Sorghum bicolor and S. propinquum. Libraries presently 3x and 6x respectively, to be expanded to 10x each. -Use fragment-matching (BAC-RF) method to determine locus-specificity in polyploids. - Contig assembly based on 1-3, plus rice BAC fingerprints generated under a separate Novartis project. -Evaluate methodology for rapid high-throughput assignment of new ESTs to BACs. -Conduct genomic sequencing in a region duplicated in both sorghum and arabidopsis. Selected BACs from sorghum(2), sugarcane, maize, rice, wheat. By improving the understanding of genetic diversity and allelic richness, the goal is to: -Sequence previously mapped sorghum DNA probes. -Discover & characterize 100 single nucleotide polymorphisms (SNPs) from cDNA markers. -Develop colorimetric high-throughput genotyping assays, and utilize to assess genetic diversity in geographically- and phenotypically-diverse sorghums. -Develop colorimetric high-throughput asssays for identifying phytochrome allelic variation, and apply these assays to a core collection representing a large set of genetic resources. -Support informatics group to streamline cataloging of DNA-level information relevant to large genetic resources collections. Lastly, the goals of expediting data acquisition and utilization include: -A new web-based resource for 3D-integration and visualization of structural and functional genomic data will be developed. -New sequence assembly and alignment software SABER (Sequence AssemBly in the presence of ERror), and PRIMAL(Practical RIgorous Multiple ALignment), will be evaluated with reference to existing standards (PHRED, PHRAP). -Specialized image processing and image analysis tools will be developed for acquistion and interpretation of qualitative and quantitative hybridization signals. To deal expeditiously with large volumes of data, parallel processing approaches will be investigated. Sponsors: * National Science Foundation (NSF) * National Sorghum Producers * University of Georgia Research Foundation (UGARF) * Georgia Research Alliance (GRA)
Proper citation: Comparative Saccharinae Genomics Resource (RRID:SCR_008153) Copy
http://genewindow.nci.nih.gov/
Software tool for pre- and post-genetic bioinformatics and analytical work, developed and used at the Core Genotyping Facility (CGF) at the National Cancer Institute. While Genewindow is implemented for the human genome and integrated with the CGF laboratory data, it stands as a useful tool to assist investigators in the selection of variants for study in vitro, or in novel genetic association studies. The Genewindow application and source code is publicly available for use in other genomes, and can be integrated with the analysis, storage, and archiving of data generated in any laboratory setting. This can assist laboratories in the choice and tracking of information related to genetic annotations, including variations and genomic positions. Features of GeneWindow include: -Intuitive representation of genomic variation using advanced web-based graphics (SVG) -Search by HUGO gene symbol, dbSNP ID, internal CGF polymorphism ID, or chromosome coordinates -Gene-centric display (only when a gene of interest is in view) oriented 5 to 3 regardless of the reference strand and adjacent genes -Two views, a Locus Overview, which varies in size depending on the gene or genomic region being viewed and, below it, a Sequence View displaying 2000 base pairs within the overview -Navigate the genome by clicking along the gene in the Locus Overview to change the Sequence View, expand or contract the genomic interval, or shift the view in the 5 or 3 direction (relative to the current gene) -Lists of available genomic features -Search for sequence matches in the Locus Overview -Genomic features are represented by shape, color and opacity with contextual information visible when the user moves over or clicks on a feature -Administrators can insert newly-discovered polymorphisms into the Genewindow database by entering annotations directly through the GUI -Integration with a Laboratory Information Management System (LIMS) or other databases is possible
Proper citation: GeneWindow (RRID:SCR_008183) Copy
http://bio-bwa.sourceforge.net/
Software for aligning sequencing reads against large reference genome. Consists of three algorithms: BWA-backtrack, BWA-SW and BWA-MEM. First for sequence reads up to 100bp, and other two for longer sequences ranged from 70bp to 1Mbp.
Proper citation: BWA (RRID:SCR_010910) Copy
https://www.genome-cloud.com/user/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 29, 2019. A cloud platform for next-generation sequencing analysis and storage. Services include: * g-Analysis: Automated genome analysis pipelines at your fingertips * g-Cluster: Easy-of-use and cost-effective genome research infrastructure * g-Storage: A simple way to store, share and protect data * g-Insight: Accurate analysis and interpretation of biological meaning of genome data
Proper citation: GenomeCloud (RRID:SCR_011886) Copy
Web based instant protein network modeler for newly sequenced species. Web server designed to instantly construct genome scale protein networks using protein sequence data. Provides network visualization, analysis pages and solution for instant network modeling of newly sequenced species.
Proper citation: JiffyNet (RRID:SCR_011954) Copy
Catalog of published genome-wide association studies. Genome-wide set of genetic variants in different individuals to see if any variant is associated with trait and disease. Database of genome-wide association study (GWAS) publications including only those attempting to assay single nucleotide polymorphisms (SNPs). Publications are organized from most to least recent date of publication. Studies are identified through weekly PubMed literature searches, daily NIH-distributed compilations of news and media reports, and occasional comparisons with an existing database of GWAS literature (HuGE Navigator). Works with HANCESTRO ancestry representation.
Proper citation: GWAS: Catalog of Published Genome-Wide Association Studies (RRID:SCR_012745) Copy
Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
Proper citation: KEGG (RRID:SCR_012773) Copy
A high-quality integrated knowledge resource specialized in the immunoglobulins (IG) or antibodies, T cell receptors (TR), major histocompatibility complex (MHC) of human and other vertebrate species, and in the immunoglobulin superfamily (IgSF), MHC superfamily (MhcSF) and related proteins of the immune system (RPI) of vertebrates and invertebrates, serving as the global reference in immunogenetics and immunoinformatics. IMGT provides a common access to sequence, genome and structure Immunogenetics data, based on the concepts of IMGT-ONTOLOGY and on the IMGT Scientific chart rules. IMGT works in close collaboration with EBI (Europe), DDBJ (Japan) and NCBI (USA). IMGT consists of sequence databases, genome database, structure database, and monoclonal antibodies database, Web resources and interactive tools.
Proper citation: IMGT - the international ImMunoGeneTics information system (RRID:SCR_012780) Copy
http://www-sequence.stanford.edu/group/candida/
The Stanford Genome Technology Center began a whole genome shotgun sequencing of strain SC5314 of Candida albicans. After reaching its original goal of 1.5X mean coverage of the haploid genome (16Mb) in summer, 1998, Stanford was awarded a supplemental grant to continue sequencing up to a coverage of 10X, performing as much assembly of the sequence as possible, using recognizable genes as nucleation points. Candida albicans is one of the most commonly encountered human pathogens, causing a wide variety of infections ranging from mucosal infections in generally healthy persons to life-threatening systemic infections in individuals with impaired immunity. Oral and esophogeal Candida infections are frequently seen in AIDS patients. Few classes of drugs are effective against these fungal infections, and all of them have limitations with regard to efficacy and side-effects.
Proper citation: Sequencing of Candida Albicans (RRID:SCR_013437) Copy
Functional genomic database for malaria parasites. Database for Plasmodium spp. Provides resource for data analysis and visualization in gene-by-gene or genome-wide scale. PlasmoDB 5.5 contains annotated genomes, evidence of transcription, proteomics evidence, protein function evidence, population biology and evolution data. Data can be queried by selecting from query grid or drop down menus. Results can be combined with each other on query history page. Search results can be downloaded with associated functional data and registered users can store their query history for future retrieval or analysis.Key community database for malaria researchers, intersecting many types of laboratory and computational data, aggregated by gene.
Proper citation: PlasmoDB (RRID:SCR_013331) Copy
Database for ESTs (Expressed Sequence Tags), consensus sequences, bacterial artificial chromosome (BAC) clones, BES (BAC End Sequences). They have generated 69,545 ESTs from 6 full-length cDNA libraries (Porcine Abdominal Fat, Porcine Fat Cell, Porcine Loin Muscle, Liver and Pituitary gland). They have also identified a total of 182 BAC contigs from chromosome 6. It is very valuable resources to study porcine quantitative trait loci (QTL) mapping and genome study. Users can explore genomic alignment of various data types, including expressed sequence tags (ESTs), consensus sequences, singletons, QTL, Marker, UniGene and BAC clones by several options. To estimate the genomic location of sequence dataset, their data aligned BES (BAC End Sequences) instead of genomic sequence because Pig Genome has low-coverage sequencing data. Sus scrofa Genome Database mainly provide comparative map of four species (pig, cattle, dog and mouse) in chromosome 6.
Proper citation: PiGenome (RRID:SCR_013394) Copy
http://bioinformatics.psb.ugent.be/ENIGMA/
A software tool to extract gene expression modules from perturbational microarray data, based on the use of combinatorial statistics and graph-based clustering. The modules are further characterized by incorporating other data types, e.g. GO annotation, protein interactions and transcription factor binding information, and by suggesting regulators that might have an effect on the expression of (some of) the genes in the module. Version : ENIGMA 1.1 used GO annotation version : Aug 29th 2007
Proper citation: ENIGMA (RRID:SCR_013400) Copy
http://fnih.org/work/past-programs/genetic-association-information-network-gain
The Genetic Association Information Network (GAIN) supports a series of Genome-Wide Association Studies (GWAS) designed to identify specific points of DNA variation associated with the occurrence of a particular common disease. Initially focusing on six major common diseases, GAIN focused on combining the results with clinical data to create a significant new resource for genetic researchers.
Proper citation: Genetic Association Information Network (GAIN) (RRID:SCR_013703) Copy
http://deweylab.biostat.wisc.edu/rsem/
Software package for quantifying gene and isoform abundances from single end or paired end RNA Seq data. Accurate transcript quantification from RNA Seq data with or without reference genome. Used for accurate quantification of gene and isoform expression from RNA-Seq data.
Proper citation: RSEM (RRID:SCR_000262) Copy
Graduate School of Genome Science and Technology (GST) is a Life Science graduate program founded on two premises. First, whole-genome sequences and related large-scale datasets have transformed how we perform biological research, a trend that is gathering momentum and is anticipated to frame the way the biology research is accomplished for many years to come. Second, advances in technology, whether at the level of instrumentation, computation, or wet lab reagents, have long been a powerful driving force in biology. The GST program is home to faculty mentors from many walks of life. The virulence factors of pathogenic fungi and the engineering of photosynthetic reaction complexes for bioenergy harvesting are just two examples from the cornucopia of research projects being pursued in GST.
Proper citation: University of Tennessee Genome Science and Technology Graduate Program (RRID:SCR_000038) Copy
http://www.atgc-montpellier.fr/mpscan/
Web tool for index free mapping of multiple short reads on a genome.
Proper citation: MPscan (RRID:SCR_000587) Copy
A software application and database viewing system for genomic research, more specifically formulti-genome comparison and pattern discovery via genome self-comparison. Data are available for a range of species including Human Chr3, Human Chr12, Sea Urchin, Tribolium, and cow. The Genboree Discovery System is the largest software system developed at the bioinformatics laboratory at Baylor in close collaboration with the Human Genome Sequencing Center. Genboree is a turnkey software system for genomic research. Genboree is hosted on the Internet and, as of early 2007, the number of registered users exceeds 600. While it can be configured to support almost any genome-centric discovery process, a number of configurations already exist for specific applications. Current focus is on enabling studies of genome variation, including array CGH studies, PCR-based resequencing, genome resequencing using comparative sequence assembly, genome remapping using paired-end tags and sequences, genome analysis and annotation, multi-genome comparison and pattern discovery via genome self-comparison. Genboree database and visualization settings, tools, and user roles are configurable to fit the needs of specific discovery processes. Private permanent project-specific databases can be accessed in a controlled way by collaborators via the Internet. Project-specific data is integrated with relevant data from public sources such as genome browsers and genomic databases. Data processing tools are integrated using a plug-in model. Genboree is extensible via flexible data-exchange formats to accommodate project specific tools and processing steps. Our Positional Hashing method, implemented in the Pash program, enables extremely fast and accurate sequence comparison and pattern discovery by employing low-level parallelism. Pash enables fast and sensitive detection of orthologous regions across mammalian genomes, and fast anchoring of hundreds of millions of short sequences produced by next-generation sequencing technologies. We are further developing the Pash program and employing it in the context of various discovery pipelines. Our laboratory participates in the pilot stage of the TCGA (The Cancer Genome Atlas) project. We aim to develop comprehensive, rapid, and economical methods for detecting recurrent chromosomal aberrations in cancer using next-generation sequencing technologies. The methods will allow detection of recurrent chromosomal aberrations in hundreds of small (
Proper citation: Genboree Discovery System (RRID:SCR_000747) Copy
International collaborative research project and database of annotated mammalian genome. Used to improve estimates of total number of genes and their alternative transcript isoforms in both human and mouse. Consortium to assign functional annotations to full length cDNAs that were collected during Mouse Encyclopedia Project at RIKEN.
Proper citation: Functional Annotation of the Mammalian Genome (RRID:SCR_000788) Copy
https://sourceforge.net/projects/popbam/
A tool to perform evolutionary or population-based analyses of next-generation sequencing data. POPBAM takes a BAM file as its input and can compute many widely used evolutionary genetics measures in sliding windows across a genome.
Proper citation: POPBAM (RRID:SCR_000464) Copy
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