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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
https://bioconductor.org/packages/release/bioc/html/oligo.html
Software package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files).
Proper citation: oligo (RRID:SCR_015729) Copy
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
http://code.google.com/p/rna-star/
Software performing alignment of high-throughput RNA-seq data. Aligns RNA-seq reads to reference genome using uncompressed suffix arrays.
Proper citation: STAR (RRID:SCR_004463) Copy
http://www.sanger.ac.uk/science/tools/seqtools
Software for multiple sequence alignment viewing, editing and phylogeny. It includes a set of user-configurable modes to color residues used to create high-quality reference alignments.
Proper citation: Belvu (RRID:SCR_015989) Copy
http://bioplex.hms.harvard.edu/
Database of cell lines with each expressing a tagged version of a protein from the ORFeome collection. The overarching project goal is to determine protein interactions for every member of the collection.
Proper citation: BioPlex (RRID:SCR_016144) Copy
http://www.sanger.ac.uk/science/tools/seqtools
Software for sequence alignment that is a graphical dot-matrix program for detailed comparison of two sequences.
Proper citation: Dotter (RRID:SCR_016080) Copy
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
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
http://amp.pharm.mssm.edu/LJP/
Interactive on line tool where signatures are tagged with user selected metadata and external transcript signatures are projected onto network. Browser to visualize signatures from breast cancer cell lines treated with single molecule perturbations.
Proper citation: LINCS Joint Project - Breast Cancer Network Browser (RRID:SCR_016181) Copy
https://github.com/jbelyeu/SV-plaudit
Software for rapidly curating structural variant (SVs) predictions. SV-plaudit provides a pipeline for creating image views of genomic intervals, automatically storing them in the cloud, deploying a website to view/score them, and retrieving scores for analysis.
Proper citation: SV-plaudit (RRID:SCR_016285) Copy
Software assembler and analysis tool for whole-genome short-gun sequencing for Illumina reads. Provides tools for error correction, sequence-to-read alignment and comparison between read sets. Used for large genomes.
Proper citation: fermi (RRID:SCR_016652) Copy
http://www.ccb.jhu.edu/software/centrifuge/
Software for rapid and sensitive classification of metagenomic sequences. Used for the classification of DNA sequences from microbial samples and analysis of large metagenomics data sets on conventional desktop computers.
Proper citation: Centrifuge Classifier (RRID:SCR_016665) Copy
https://github.com/fbreitwieser/pavian
Software R package for interactive analysis of metagenomics classification results with a special focus on infectious disease diagnosis. Used for analyzing and visualization of metagenomics classification results from classifiers such as Kraken, Centrifuge and MetaPhlAn. Provides an alignment viewer for validation of matches to a particular genome.
Proper citation: Pavian (RRID:SCR_016679) Copy
https://csgid.org/csgid/metal_sites
Metal binding site validation server. Used for systematic inspection of the metal-binding architectures in macromolecular structures. The validation parameters that CMM examines cover the entire binding environment of the metal ion, including the position, charge and type of atoms and residues surrounding the metal.
Proper citation: CheckMyMetal (RRID:SCR_016887) Copy
https://picrust.github.io/picrust/
Software package to predict metagenome functional content from marker gene (e.g., 16S rRNA) surveys and full genomes. Used to predict which gene families are present and then combines gene families to estimate the composite metagenome.
Proper citation: PICRUSt (RRID:SCR_016855) Copy
https://github.com/ruanjue/wtdbg2.git
Software tool as de novo sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies. It assembles raw reads without error correction and then builds consensus from intermediate assembly output. Desiged to assemble huge genomes in very limited time.
Proper citation: WTDBG (RRID:SCR_017225) Copy
https://www.mc.vanderbilt.edu/victr/dcc/projects/acc/index.php/Main_Page
A national consortium formed to develop, disseminate, and apply approaches to research that combine DNA biorepositories with electronic medical record (EMR) systems for large-scale, high-throughput genetic research. The consortium is composed of seven member sites exploring the ability and feasibility of using EMR systems to investigate gene-disease relationships. Themes of bioinformatics, genomic medicine, privacy and community engagement are of particular relevance to eMERGE. The consortium uses data from the EMR clinical systems that represent actual health care events and focuses on ethical issues such as privacy, confidentiality, and interactions with the broader community.
Proper citation: eMERGE Network: electronic Medical Records and Genomics (RRID:SCR_007428) Copy
Resource for experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Most of these noncoding elements were selected for testing based on their extreme conservation in other vertebrates or epigenomic evidence (ChIP-Seq) of putative enhancer marks. Central public database of experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Users can retrieve elements near single genes of interest, search for enhancers that target reporter gene expression to particular tissue, or download entire collections of enhancers with defined tissue specificity or conservation depth.
Proper citation: VISTA Enhancer Browser (RRID:SCR_007973) Copy
The Distributed Annotation System (DAS) defines a communication protocol used to exchange annotations on genomic or protein sequences. It is motivated by the idea that such annotations should not be provided by single centralized databases, but should instead be spread over multiple sites. Data distribution, performed by DAS servers, is separated from visualization, which is done by DAS clients. The advantages of this system are that control over the data is retained by data providers, data is freed from the constraints of specific organisations and the normal issues of release cycles, API updates and data duplication are avoided. DAS is a client-server system in which a single client integrates information from multiple servers. It allows a single machine to gather up sequence annotation information from multiple distant web sites, collate the information, and display it to the user in a single view. Little coordination is needed among the various information providers. DAS is heavily used in the genome bioinformatics community. Over the last years we have also seen growing acceptance in the protein sequence and structure communities. A DAS-enabled website or application can aggregate complex and high-volume data from external providers in an efficient manner. For the biologist, this means the ability to plug in the latest data, possibly including a user''s own data. For the application developer, this means protection from data format changes and the ability to add new data with minimal development cost. Here are some examples of DAS-enabled applications or websites for end users: :- Dalliance Experimental Web/Javascript based Genome Viewer :- IGV Integrative Genome Viewer java based browser for many genomes :- Ensembl uses DAS to pull in genomic, gene and protein annotations. It also provides data via DAS. :- Gbrowse is a generic genome browser, and is both a consumer and provider of DAS. :- IGB is a desktop application for viewing genomic data. :- SPICE is an application for projecting protein annotations onto 3D structures. :- Dasty2 is a web-based viewer for protein annotations :- Jalview is a multiple alignment editor. :- PeppeR is a graphical viewer for 3D electron microscopy data. :- DASMI is an integration portal for protein interaction data. :- DASher is a Java-based viewer for protein annotations. :- EpiC presents structure-function summaries for antibody design. :- STRAP is a STRucture-based sequence Alignment Program. Hundreds of DAS servers are currently running worldwide, including those provided by the European Bioinformatics Institute, Ensembl, the Sanger Institute, UCSC, WormBase, FlyBase, TIGR, and UniProt. For a listing of all available DAS sources please visit the DasRegistry. Sponsors: The initial ideas for DAS were developed in conversations with LaDeana Hillier of the Washington University Genome Sequencing Center.
Proper citation: Distributed Annotation System (RRID:SCR_008427) Copy
http://www.broad.mit.edu/mpg/grail/
A tool to examine relationships between genes in different disease associated loci. Given several genomic regions or SNPs associated with a particular phenotype or disease, GRAIL looks for similarities in the published scientific text among the associated genes. As input, users can upload either (1) SNPs that have emerged from a genome-wide association study or (2) genomic regions that have emerged from a linkage scan or are associated common or rare copy number variants. SNPs should be listed according to their rs#''s and must be listed in HapMap. Genomic Regions are specified by a user-defined identifier, the chromosome that it is located on, and the start and end base-pair positions for the region. Grail can take two sets of inputs - Query regions and Seed regions. Seed regions are definitely associated SNPs or genomic regions, and Query regions are those regions that the user is attempting to evaluate agains them. In many applications the two sets are identical. Based on textual relationships between genes, GRAIL assigns a p-value to each region suggesting its degree of functional connectivity, and picks the best candidate gene. GRAIL is developed by Soumya Raychaudhuri in the labs of David Altshuler and Mark Daly at the Center for Human Genetic Research of Massachusetts General Hospital and Harvard Medical School, and the Broad Institute. GRAIL is described in manuscript, currently in preparation.
Proper citation: Gene Relationships Across Implicated Loci (RRID:SCR_008537) Copy
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