June 2019 Tool Shed contributions

Tools contributed to the Galaxy Project ToolShed in June 2019.

• All monthly summaries

New Tools

• From lz_hust:

  • gatktools: The Genome Analysis Toolkit updated in 2019. Developed in the Data Sciences Platform at the Broad Institute, the toolkit offers a wide variety of tools with a primary focus on variant discovery and genotyping. Its powerful processing engine and high-performance computing features make it capable of taking on projects of any size.

• From iuc:

  • dropletutils: DropletUtils - Utilities for handling droplet-based single-cell RNA-seq data. Provides a number of utility functions for handling single-cell (RNA-seq) data from droplet technologies such as 10X Genomics. This includes data loading from count matrices or molecule information files, identification of cells from empty droplets, removal of barcode-swapped pseudo-cells, and downsampling of the count matrix.
  • compose_text_param: Compose a text parameter value using text, integer and float values. This tool can be used in workflows to create a text parameter from multiple individual parameters.
  • gfa_to_fa: gfa_to_fa - Converting GFA format to Fasta format. Convert GFA files to Fasta.
  • miniasm: Miniasm - Ultrafast de novo assembly for long noisy reads (though having no consensus step). Miniasm is a very fast OLC-based de novo assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by minimap) as input and outputs an assembly graph in the GFA format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final unitig sequences. Thus the per-base error rate is similar to the raw input reads.

• From fgiacomoni:

  • hr2: Init repository for [hr2]. [W4M][LC-MS] HR2 - in silico Annotation - Finding a chemical formula from a accurate mass. Part of the F.L.A.M.E. project. The process returns outputs files (CSV and HTML formats).

• From chemteam:

  • ambertools_parmchk2: Wrapper for the AmberTools package: ParmChk2. AmberTools is a set of packages than can be to create forcefields (antechamber), prepare molecules(tleap) and much more.
  • ambertools_antechamber: Wrapper for the AmberTools package: AnteChamber.
  • ambertools_acpype: Wrapper for the AmberTools package: Generate MD topologies for small molecules.

• From bgruening:

  • nanopolish_polya: Nanopolish tool: Nanopolish polyA. Nanopolish can calculate an improved consensus sequence for a draft genome assembly, detect base modifications, call SNPs and indels with respect to a reference genome and more.

• From ecology:

  • regionalgam_gls: Wrapper for regionalGAM application Model temporal trend.
  • regionalgam_flight_curve: Wrapper for regionalGAM application Flight curve.
  • regionalgam_autocor_acf: Wrapper for regionalGAM application Autocorrelation test.
  • regionalgam_glmmpql: Wrapper for regionalGAM application Expected temporal trend.
  • regionalgam_gls_adjusted: Wrapper for regionalGAM application Linear regression ajusted.
  • regionalgam_plot_trend: Wrapper for regionalGAM application Plot abundance.
  • regionalgam_ab_index: Wrapper for regionalGAM application Abundance index.

• From artbio:

  • gsc_cpm_tpm_rpk: Generate CPM,TPM or RPK from raw counts. Normalizes raw counts expression matrix on different parameters. - CPM : library-size normalization - TPM : gene length and library-size normalization - RPK : gene length normalization This tools derives from the non-longer supported artbio tool cpm_tpm_rpk.
  • gsc_filter_cells: Filter single cell RNAseq data on libray depth and number of detected genes. Filter single cell RNAseq datasets on - Absolute numbers of aligned reads or of detected genes and / or - relatively to percentile threshold in the datasets, for numbers of aligned reads or of detected genes.
  • gsc_filter_genes: Filter genes that are detected in less than a fraction of libraries in single cell RNAseq data.
  • gsc_gene_expression_correlations: Compute single-cell paire-wise gene expressions correlations. Compute single-cell paire-wise gene expressions correlations between genes or between genes and a signature of selected genes.
  • gsc_mannwhitney_de: Perform a mann-whitney differential testing between two sets of gene expression data.
  • gsc_signature_score: Compute signature scores from single cell RNAseq data. Compute signature scores from single cell RNAseq data.

• From petr-novak:

  • profrep: profrep. profrep.
  • package_profrep_1_0: Contains a tool dependency definition that downloads and prepare databases for profrep.
  • package_profrep_databases_1_0: Contains a tool dependency definition that downloads and prepare databases for profrep.