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ToolShed/Contributions/2016_09

Galaxy ToolShed

Tools contributed to the Galaxy Project Tool Shed in September 2016.

New Tools

unrestricted

  • From gdroc:

    • rave: RAVE (Rapid Allelic Variant Extractor) : Extract data from binary PLINK file

  • From iuc:

    • featurecounts: Counts reads aligned to annotated genes in a reference genome from SAM or BAM files.

    • quast: Quast (Quality ASsessment Tool) evaluates genome assemblies by computing various metrics, including - N50, length for which the collection of all contigs of that length or longer covers at least 50% of assembly length, - NG50, where length of the reference genome is being covered, - NA50 and NGA50, where aligned blocks instead of contigs are taken, - misassemblies, misassembled and unaligned contigs or contigs bases, - genes and operons covered.

    • scikit_bio_diversity_beta_diversity: Wrapper for the scikit-bio tool suite: Beta Diversity scikit-bio is an open-source, BSD-licensed, python package providing data structures, algorithms, and educational resources for bioinformatics

    • data_source_iris_tcga: Data source tool Retrieve data from Information Retrieval and Integration System for cancer genomic data from The Cancer Genome Atlas (IRIS-TCGA). IRIS-TCGA is an online web service for searching, retrieving and integrating genomic data: http://bioinf.iasi.cnr.it/iristcga/index.php.

    • bwameth: Fast and accurate alignment of BS-seq reads. Supports single-end and paired-end alignments and gapped alignments and is faster and more sensitive than many other tools

    • star_fusion: STAR Fusion detects fusion genes in RNA-Seq data after running RNA-STAR STAR-Fusion further processes the output generated by the STAR aligner to map junction reads and spanning reads to a reference annotation set (using a GTF file, ideally the same annotation file used during the STAR genome index building process during the intial STAR setup). https://github.com/STAR-Fusion/STAR-Fusion

  • From bgruening:

  • From saharlcc:

    • isoem2_isode2: Bootstrapping-Based Estimation of Confidence Intervals of Expression Levels and Differential Expression from RNA-Seq Data

  • From amadeo:

    • amadeo: This workflow can be applied to microarray data in order to find connections between genetic elements. This workflow extracts genetic information from this microarray data, and finds relationships between cis-regulatory elements located in the promoter under same regulation of gene expression.

  • From davidvanzessen:

    • prisca: PRISCA: PRecISe Clonal Analysis Comparison of clonal sequences in paired samples

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