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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://www.bioconductor.org/packages/release/bioc/html/ggbio.html
An R package for extending the grammar of graphics for genomic data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.
Proper citation: ggbio (RRID:SCR_003313) Copy
http://primerseq.sourceforge.net/
Software that designs RT-PCR primers that evaluate alternative splicing events by incorporating RNA-Seq data. It is particularly advantageous for designing a large number of primers for validating alternative splicing events found in RNA-Seq data. It incorporates RNA-Seq data in the design process to weight exons by their read counts. Essentially, the RNA-Seq data allows primers to be placed using actually expressed transcripts. This could be for a particular cell line or experimental condition, rather than using annotations that incorporate transcripts that are not expressed for the data. Alternatively, you can design primers that are always on constitutive exons. PrimerSeq does not limit the use of gene annotations and can be used for a wide array of species.
Proper citation: PrimerSeq (RRID:SCR_003295) Copy
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
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
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
https://github.com/BEETL/BEETL
Software tool that not only compresses FASTQ-formatted DNA reads more compactly than gzip but also permits rapid search for k-mer queries within the archived sequences. The full FASTQ record of each matching read or read pair is returned, allowing the search results to be piped directly to any of the many standard tools that accept FASTQ data as input. Searchable compressed archive for DNA reads.
Proper citation: BEETL-fastq (RRID:SCR_002341) Copy
Python module to parse mzML data in Python based on cElementTree. It is an extension to Python that offers (i) an easy access to mass spectrometry (MS) data that allows the rapid development of tools, (ii) a very fast parser for mzML data and (iii) a set of functions to compare or handle spectra., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: pymzML (RRID:SCR_002500) Copy
http://bioconductor.org/packages/release/bioc/html/sapFinder.html
An R software package, for detection of the variant peptides based on tandem mass spectrometry (MS/MS)-based proteomics data. It automates (1) variation-associated database construction, (2) database searching, (3) post-processing, (4) HTML-based report generation in shotgun proteomics.
Proper citation: sapFinder (RRID:SCR_002685) Copy
https://github.com/grenaud/leeHom
Software program for the Bayesian reconstruction of ancient DNA fragments. The algorithm removes the adaptors and reconstructs the original DNA sequences using a Bayesian maximum a posteriori probability approach.
Proper citation: leeHom (RRID:SCR_002710) Copy
http://www.bioconductor.org/packages/release/bioc/html/pathview.html
A tool set for pathway-based data integration and visualization. It maps and renders a wide variety of biological data on relevant pathway graphs. All users need is to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps user data to the pathway, and render pathway graph with the mapped data. In addition, Pathview also seamlessly integrates with pathway and gene set (enrichment) analysis tools for large-scale and fully automated analysis.
Proper citation: Pathview (RRID:SCR_002732) Copy
http://www.bioconductor.org/packages/release/bioc/html/rBiopaxParser.html
A software package that provides a comprehensive set of functions for parsing, viewing and modifying BioPAX pathway data within R. At the moment BioPAX level 2 and level 3 are supported.
Proper citation: rBiopaxParser (RRID:SCR_002744) Copy
http://cran.r-project.org/web/packages/MBCluster.Seq/index.html
Software to cluster genes based on Poisson or Negative-Binomial model for RNA-Seq or other digital gene expression (DGE) data.
Proper citation: MBCluster.Seq (RRID:SCR_005079) Copy
https://github.com/AlexeyG/GRASS
A generic algorithm for scaffolding next-generation sequencing assemblies.
Proper citation: GRASS (RRID:SCR_005071) Copy
http://www.comp.hkbu.edu.hk/~chxw/software/G-BLASTN.html
A GPU-accelerated nucleotide alignment tool based on the widely used NCBI-BLAST. It can produce exactly the same results as NCBI-BLAST, and it also has very similar user commands. It also supports a pipeline mode, which can fully utilize the GPU and CPU resources when handling a batch of medium to large sized queries.
Proper citation: G-BLASTN (RRID:SCR_005062) Copy
http://sourceforge.net/projects/viralfusionseq/
A versatile high-throughput sequencing (HTS) tool for discovering viral integration events and reconstruct fusion transcripts at single-base resolution. It combines soft-clipping information, read-pair analysis, and targeted de novo assembly to discover and annotate viral-human fusion events. A simple yet effective empirical statistical model is used to evaluate the quality of fusion breakpoints. Minimal user defined parameters are required.
Proper citation: VFS (RRID:SCR_005138) Copy
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