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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.
http://shendurelab.github.io/MIPGEN/
Software for a fast, simple way to generate designs for MIP assays targeting hundreds or thousands of genomic loci in parallel. Packaged with MIPgen are scripts that aid in visualization of MIP designs and processing of MIP sequence reads to SAM files that can then be passed through any standard variant calling pipeline.
Proper citation: MIPgen (RRID:SCR_003325) Copy
https://bitbucket.org/johanneskoester/snakemake/wiki/
A Python based language and execution environment for make-like workflows. The system supports the use of automatically inferred multiple named wildcards (or variables) in input and output filenames.
Proper citation: Snakemake (RRID:SCR_003475) Copy
http://knowledgemap.mc.vanderbilt.edu/research/content/phewas-r-package
Software package contains methods for performing Phenome-Wide Association Study.
Proper citation: PheWAS R Package (RRID:SCR_003512) Copy
http://www.cellimagelibrary.org/
Freely accessible, public repository of vetted and annotated microscopic images, videos, and animations of cells from a variety of organisms, showcasing cell architecture, intracellular functionalities, and both normal and abnormal processes. Explore by Cell Process, Cell Component, Cell Type or Organism. The Cell includes images acquired from historical and modern collections, publications, and by recruitment.
Proper citation: Cell Image Library (CIL) (RRID:SCR_003510) Copy
https://code.google.com/p/bpipe/
Software tool for running and managing bioinformatics pipelines. It specializes in enabling users to turn existing pipelines based on shell scripts or command line tools into highly flexible, adaptable and maintainable workflows with a minimum of effort. Bpipe ensures that pipelines execute in a controlled and repeatable fashion and keeps audit trails and logs to ensure that experimental results are reproducible. Requiring only Java as a dependency, it is fully self-contained and cross-platform, making it very easy to adopt and deploy into existing environments.
Proper citation: Bpipe (RRID:SCR_003471) Copy
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
http://cran.r-project.org/web/packages/MultiPhen/
Software package that performs genetic association tests between SNPs (one-at-a-time) and multiple phenotypes (separately or in joint model).
Proper citation: MultiPhen (RRID:SCR_003498) Copy
http://www.biostat.wisc.edu/~kendzior/EBSEQ/
Software R package for RNA-Seq Differential Expression Analysis.
Proper citation: EBSeq (RRID:SCR_003526) Copy
Collection of pathways and pathway annotations. The core unit of the Reactome data model is the reaction. Entities (nucleic acids, proteins, complexes and small molecules) participating in reactions form a network of biological interactions and are grouped into pathways (signaling, innate and acquired immune function, transcriptional regulation, translation, apoptosis and classical intermediary metabolism) . Provides website to navigate pathway knowledge and a suite of data analysis tools to support the pathway-based analysis of complex experimental and computational data sets.
Proper citation: Reactome (RRID:SCR_003485) Copy
A freely available software tool available for the Windows and Linux platform, as well as the Online version Applet, for the analysis, comparison and search of digital reconstructions of neuronal morphologies. For the quantitative characterization of neuronal morphology, LM computes a large number of neuroanatomical parameters from 3D digital reconstruction files starting from and combining a set of core metrics. After more than six years of development and use in the neuroscience community, LM enables the execution of commonly adopted analyses as well as of more advanced functions, including: (i) extraction of basic morphological parameters, (ii) computation of frequency distributions, (iii) measurements from user-specified subregions of the neuronal arbors, (iv) statistical comparison between two groups of cells and (v) filtered selections and searches from collections of neurons based on any Boolean combination of the available morphometric measures. These functionalities are easily accessed and deployed through a user-friendly graphical interface and typically execute within few minutes on a set of 20 neurons. The tool is available for either online use on any Java-enabled browser and platform or may be downloaded for local execution under Windows and Linux.
Proper citation: L-Measure (RRID:SCR_003487) Copy
https://code.google.com/p/mztab/
A Java interface to the mzTab data exchange format for reporting a summary of proteomics results.
Proper citation: jmzTab (RRID:SCR_003481) Copy
http://www.compgen.org/tools/metagen
Software program providing a method for meta-analysis of case-control genetic association studies using random-effects logistic regression.
Proper citation: metagen (RRID:SCR_003443) Copy
Research informatics and analytics platform for the IMI OncoTrack consortium.
Proper citation: eTRIKS (RRID:SCR_003765) Copy
http://genome.sph.umich.edu/wiki/RAREMETAL
A software program that facilitates the meta-analysis of rare variants from genotype arrays or sequencing.
Proper citation: RAREMETAL (RRID:SCR_003573) Copy
http://clipserve.clip.ubc.ca/topfind
An integrated knowledgebase focused on protein termini, their formation by proteases and functional implications. It contains information about the processing and the processing state of proteins and functional implications thereof derived from research literature, contributions by the scientific community and biological databases. It lists more than 120,000 N- and C-termini and almost 10,000 cleavages. TopFIND is a resource for comprehensive coverage of protein N- and C-termini discovered by all available in silico, in vitro as well as in vivo methodologies. It makes use of existing knowledge by seamless integration of data from UniProt and MEROPS and provides access to new data from community submission and manual literature curating. It renders modifications of protein termini, such as acetylation and citrulination, easily accessible and searchable and provides the means to identify and analyse extend and distribution of terminal modifications across a protein. The data is presented to the user with a strong emphasis on the relation to curated background information and underlying evidence that led to the observation of a terminus, its modification or proteolytic cleavage. In brief the protein information, its domain structure, protein termini, terminus modifications and proteolytic processing of and by other proteins is listed. All information is accompanied by metadata like its original source, method of identification, confidence measurement or related publication. A positional cross correlation evaluation matches termini and cleavage sites with protein features (such as amino acid variants) and domains to highlight potential effects and dependencies in a unique way. Also, a network view of all proteins showing their functional dependency as protease, substrate or protease inhibitor tied in with protein interactions is provided for the easy evaluation of network wide effects. A powerful yet user friendly filtering mechanism allows the presented data to be filtered based on parameters like methodology used, in vivo relevance, confidence or data source (e.g. limited to a single laboratory or publication). This provides means to assess physiological relevant data and to deduce functional information and hypotheses relevant to the bench scientist. TopFIND PROVIDES: * Integration of protein termini with proteolytic processing and protein features * Displays proteases and substrates within their protease web including detailed evidence information * Fully supports the Human Proteome Project through search by chromosome location CONTRIBUTE * Submit your N- or C-termini datasets * Contribute information on protein cleavages * Provide detailed experimental description, sample information and raw data
Proper citation: TopFIND (RRID:SCR_008918) Copy
http://bioinformatics.fccc.edu/software/OpenSource/FGDP/FGDP.shtml
A Java-based, Microarray or Genechip data analysis system.
Proper citation: FGDP (RRID:SCR_008910) Copy
http://go.princeton.edu/cgi-bin/GOTermFinder
The Generic GO Term Finder finds the significant GO terms shared among a list of genes from an organism, displaying the results in a table and as a graph (showing the terms and their ancestry). The user may optionally provide background information or a custom gene association file or filter evidence codes. This tool is capable of batch processing multiple queries at once. GO::TermFinder comprises a set of object-oriented Perl modules GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script. This implementation, developed at the Lewis-Sigler Institute at Princeton, depends on the GO-TermFinder software written by Gavin Sherlock and Shuai Weng at Stanford University and the GO:View module written by Shuai Weng. It is made publicly available through the GMOD project. The full source code and documentation for GO:TermFinder are freely available from http://search.cpan.org/dist/GO-TermFinder/. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: Generic GO Term Finder (RRID:SCR_008870) Copy
http://plantgrn.noble.org/LegumeIP/
LegumeIP is an integrative database and bioinformatics platform for comparative genomics and transcriptomics to facilitate the study of gene function and genome evolution in legumes, and ultimately to generate molecular based breeding tools to improve quality of crop legumes. LegumeIP currently hosts large-scale genomics and transcriptomics data, including: * Genomic sequences of three model legumes, i.e. Medicago truncatula, Glycine max (soybean) and Lotus japonicus, including two reference plant species, Arabidopsis thaliana and Poplar trichocarpa, with the annotation based on UniProt TrEMBL, InterProScan, Gene Ontology and KEGG databases. LegumeIP covers a total 222,217 protein-coding gene sequences. * Large-scale gene expression data compiled from 104 array hybridizations from L. japonicas, 156 array hybridizations from M. truncatula gene atlas database, and 14 RNA-Seq-based gene expression profiles from G. max on different tissues including four common tissues: Nodule, Flower, Root and Leaf. * Systematic synteny analysis among M. truncatula, G. max, L. japonicus and A. thaliana. * Reconstruction of gene family and gene family-wide phylogenetic analysis across the five hosted species. LegumeIP features comprehensive search and visualization tools to enable the flexible query on gene annotation, gene family, synteny, relative abundance of gene expression.
Proper citation: LegumeIP (RRID:SCR_008906) Copy
https://CRAN.R-project.org/package=gma
Software package to perform Granger mediation analysis for time series. Includes single level GMA model and two-level GMA model, for time series with hierarchically nested structure.
Proper citation: GMA (RRID:SCR_009212) Copy
http://hymenopteragenome.org/beebase/
Gene sequences and genomes of Bombus terrestris, Bombus impatiens, Apis mellifera and three of its pathogens, that are discoverable and analyzed via genome browsers, blast search, and apollo annotation tool. The genomes of two additional species, Apis dorsata and A. florea are currently under analysis and will soon be incorporated.BeeBase is an archive and will not be updated. The most up-to-date bee genome data is now available through the navigation bar on the HGD Home page.
Proper citation: BeeBase (RRID:SCR_008966) Copy
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