From 64d280e1b6a047159026d8c0f260dc6bde1fc926 Mon Sep 17 00:00:00 2001 From: github-actions Date: Wed, 7 Feb 2024 21:17:33 +0000 Subject: [PATCH 01/96] fetch all tools bot - step filter --- results/imaging/index.html | 2 +- results/imaging/tools.tsv | 2 +- results/microgalaxy/index.html | 8 ++++---- results/microgalaxy/tools.tsv | 22 +++++++++++----------- 4 files changed, 17 insertions(+), 17 deletions(-) diff --git a/results/imaging/index.html b/results/imaging/index.html index 1f3b1ef2..cfc71326 100644 --- a/results/imaging/index.html +++ b/results/imaging/index.html @@ -940,7 +940,7 @@ graphicsmagick - 1.3.40 + 1.3.42 1.3.26 graphicsmagick To update diff --git a/results/imaging/tools.tsv b/results/imaging/tools.tsv index 902f25bb..58b47573 100644 --- a/results/imaging/tools.tsv +++ b/results/imaging/tools.tsv @@ -42,7 +42,7 @@ wsi_extract_top_view 38.0 ip_wsi_extract_top_view WSI Extract Top View To cellprofiler cp_cellprofiler, cp_color_to_gray, cp_convert_objects_to_image, cp_display_data_on_image, cp_enhance_or_suppress_features, cp_export_to_spreadsheet, cp_gray_to_color, cp_identify_primary_objects, cp_image_math, cp_mask_image, cp_measure_granularity, cp_measure_image_area_occupied, cp_measure_image_intensity, cp_measure_image_quality, cp_measure_object_intensity, cp_measure_object_size_shape, cp_measure_texture, cp_overlay_outlines, cp_relate_objects, cp_save_images, cp_common, cp_tile, cp_track_objects cellProfiler wrapper CellProfiler CellProfiler Tool for quantifying data from biological images, particularly in high-throughput experiments. Quantification, Image analysis, Parsing Imaging, Microarray experiment, Genotype and phenotype To update Imaging cellprofiler bgruening https://github.com/bgruening/galaxytools/tree/master/tools (0/23) (23/23) (23/23) False cellprofiler_v4 cp_cellprofiler4 cellProfiler4 wrapper To update Imaging cellprofiler4 bgruening https://github.com/bgruening/galaxytools/tree/master/tools 4.2.6 (0/1) (0/1) (1/1) False bia-ftplinks bia_download Tool to query ftp links for study from bioimage archive To update Imaging bia_download bgruening https://github.com/bgruening/galaxytools/tree/master/tools 0.1.0 wget (0/1) (0/1) (1/1) False -graphicsmagick graphicsmagick_image_compare, graphicsmagick_image_convert, graphicsmagick_image_montage Contains tools based on GraphicsMagick To update http://www.graphicsmagick.org Imaging graphicsmagick bgruening https://github.com/bgruening/galaxytools/new/gm/tools/image_processing/image_processing/ 1.3.40 graphicsmagick 1.3.26 (1/3) (0/3) (3/3) False +graphicsmagick graphicsmagick_image_compare, graphicsmagick_image_convert, graphicsmagick_image_montage Contains tools based on GraphicsMagick To update http://www.graphicsmagick.org Imaging graphicsmagick bgruening https://github.com/bgruening/galaxytools/new/gm/tools/image_processing/image_processing/ 1.3.42 graphicsmagick 1.3.26 (1/3) (0/3) (3/3) False imagej2 imagej2_adjust_threshold_binary, imagej2_analyze_particles_binary, imagej2_analyze_skeleton, imagej2_binary_to_edm, imagej2_bunwarpj_adapt_transform, imagej2_bunwarpj_align, imagej2_bunwarpj_compare_elastic, imagej2_bunwarpj_compare_elastic_raw, imagej2_bunwarpj_compare_raw, imagej2_bunwarpj_compose_elastic, imagej2_bunwarpj_compose_raw, imagej2_bunwarpj_compose_raw_elastic, imagej2_bunwarpj_convert_to_raw, imagej2_bunwarpj_elastic_transform, imagej2_bunwarpj_raw_transform, imagej2_create_image, imagej2_enhance_contrast, imagej2_find_edges, imagej2_find_maxima, imagej2_make_binary, imagej2_math, imagej2_noise, imagej2_shadows, imagej2_sharpen, imagej2_skeletonize3d, imagej2_smooth, imagej2_watershed_binary ImageJ2 is a new version of ImageJ for the next generation of multidimensionalimage data, with a focus on scientific imaging. imagej ImageJ2 It is a public domain Java image processing program, which was designed with an open architecture. Custom acquisition, analysis and processing plugins can be developed using ImageJ’s built-in editor and a Java compiler. User-written plugins make it possible to solve many image processing and analysis problems, from three-dimensional live-cell imaging, to radiological image processing, multiple imaging system data comparisons to automated hematology systems. Image analysis, Image annotation, Visualisation Imaging To update http://fiji.sc Imaging imagej2 imgteam https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 (0/27) (0/27) (27/27) False spyboat 67.0 1.0 spyboat Wavelet analysis for 3d-image stacks To update http://github.com/tensionhead/spyboat Imaging, Graphics spyboat iuc https://github.com/galaxyproject/tools-iuc/tree/master/packages/spyboat 0.1.2 spyboat (0/1) (0/1) (1/1) False qupath_roi_splitter 59.0 5.0 qupath_roi_splitter Split ROI coordinates of QuPath TMA annotation by cell type To update https://github.com/npinter/ROIsplitter Imaging qupath_roi_splitter galaxyp hhttps://github.com/npinter/ROIsplitter 0.1.0+galaxy1 geojson (0/1) (0/1) (1/1) False diff --git a/results/microgalaxy/index.html b/results/microgalaxy/index.html index 0c96dc24..642c5255 100644 --- a/results/microgalaxy/index.html +++ b/results/microgalaxy/index.html @@ -1801,7 +1801,7 @@ diamond 2.0.15 - 2.1.8 + 2.1.9 diamond To update diamond @@ -2161,7 +2161,7 @@ gubbins 3.2.1 - 3.3.1 + 3.3.3 gubbins To update gubbins @@ -2901,7 +2901,7 @@ megan 6.21.7 - 6.24.20 + 6.25.9 megan To update megan @@ -3941,7 +3941,7 @@ seqkit 2.3.1 - 2.6.1 + 2.7.0 seqkit To update seqkit diff --git a/results/microgalaxy/tools.tsv b/results/microgalaxy/tools.tsv index fcbcc977..cc621202 100644 --- a/results/microgalaxy/tools.tsv +++ b/results/microgalaxy/tools.tsv @@ -1,6 +1,6 @@ Galaxy wrapper id Total tool usage (usegalaxy.eu) No. of tool users (2022-2023) (usegalaxy.eu) Galaxy tool ids Description bio.tool id bio.tool name bio.tool description EDAM operation EDAM topic Status Source ToolShed categories ToolShed id Galaxy wrapper owner Galaxy wrapper source Galaxy wrapper version Conda id Conda version https://usegalaxy.org https://usegalaxy.org.au https://usegalaxy.eu Reviewed To keep braker 109.0 17.0 braker BRAKER is a pipeline for fully automated prediction of protein coding gene structures with GeneMark-ES/ET and AUGUSTUS in novel eukaryotic genomes . To update https://github.com/Gaius-Augustus/BRAKER Genome annotation braker genouest https://github.com/genouest/galaxy-tools/tree/master/tools/braker 2.1.6 (0/1) (0/1) (1/1) True False -braker3 567.0 10.0 braker3 BRAKER3 is a pipeline for fully automated prediction of protein coding gene structures with GeneMark-ES/ET and AUGUSTUS in novel eukaryotic genomes . To update https://github.com/Gaius-Augustus/BRAKER Genome annotation braker3 genouest https://github.com/genouest/galaxy-tools/tree/master/tools/braker 3.0.6 (0/1) (1/1) (1/1) True False +braker3 567.0 10.0 braker3 BRAKER3 is a pipeline for fully automated prediction of protein coding gene structures with GeneMark-ES/ET and AUGUSTUS in novel eukaryotic genomes . To update https://github.com/Gaius-Augustus/BRAKER Genome annotation braker3 genouest https://github.com/genouest/galaxy-tools/tree/master/tools/braker 3.0.7 (0/1) (1/1) (1/1) True False helixer 93.0 1.0 helixer Gene calling with Deep Neural Networks To update https://github.com/weberlab-hhu/Helixer Genome annotation helixer genouest https://github.com/genouest/galaxy-tools/tree/master/tools/helixer 0.3.2 (0/1) (0/1) (1/1) True False logol logol_wrapper Logol is a pattern matching grammar language and a set of tools to search a pattern in a sequence Up-to-date http://logol.genouest.org/web/app.php/logol Sequence Analysis genouest https://github.com/genouest/galaxy-tools/tree/master/tools/logol 1.7.8 logol 1.7.8 (0/1) (0/1) (0/1) True False peptimapper peptimapper_clustqualify, peptimapper_clust_to_gff, peptimapper_pep_match, peptimapper_pep_novo_tag Proteogenomics workflow for the expert annotation of eukaryotic genomes To update https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-019-5431-9 Proteomics genouest 2.0 (0/4) (0/4) (0/4) True False @@ -180,7 +180,7 @@ compalignp 220.0 compalignp Compute fractional identity between trusted alignme coprarna coprarna Target prediction for prokaryotic trans-acting small RNAs To update https://github.com/PatrickRWright/CopraRNA RNA, Sequence Analysis coprarna rnateam https://github.com/PatrickRWright/CopraRNA 2.1.1 coprarna 2.1.4 (0/1) (0/1) (0/1) True False dewseq 72.0 11.0 dewseq DEWSeq is a sliding window based peak caller for eCLIP/iCLIP data To update https://github.com/EMBL-Hentze-group/DEWSeq_analysis_helpers Sequence Analysis, RNA, CLIP-seq dewseq rnateam https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/dewseq 0.1.0+galaxy0 python (0/1) (0/1) (1/1) True False dorina 1086.0 1.0 dorina_search data source for RNA interactions in post-transcriptional regulation To update RNA, Data Source dorina rnateam https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/dorina/ 1.0 (0/1) (0/1) (1/1) True False -dot2ct rnastructure_dot2ct Dot-Bracket to Connect Table (CT) To update Sequence Analysis, RNA dot2ct rnateam https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/dot2ct 5.7.a rnastructure 6.3 (0/1) (0/1) (0/1) True False +dot2ct rnastructure_dot2ct Dot-Bracket to Connect Table (CT) To update Sequence Analysis, RNA dot2ct rnateam https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/dot2ct 5.7.a rnastructure 6.4 (0/1) (0/1) (0/1) True False dotknot 83.0 1.0 dotknot DotKnot is a heuristic method for pseudoknot prediction in a given RNA sequence To update http://dotknot.csse.uwa.edu.au/ RNA, Proteomics dotknot bgruening https://github.com/bgruening/galaxytools/tree/master/tools/rna/dotknot 1.3.1 vienna_rna (0/1) (0/1) (1/1) True False exparna exparna ExpaRNA is a fast, motif-based comparison and alignment tool for RNA molecules. Up-to-date http://rna.informatik.uni-freiburg.de/ExpaRNA/Input.jsp RNA exparna rnateam https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/exparna 1.0.1 exparna 1.0.1 (0/1) (0/1) (0/1) True False graphprot graphprot_predict_profile GraphProt models binding preferences of RNA-binding proteins. To update https://github.com/dmaticzka/GraphProt Sequence Analysis, RNA, CLIP-seq graphprot rnateam https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/graphprot 1.1.7+galaxy1 graphprot 1.1.7 (0/1) (0/1) (1/1) True False @@ -275,7 +275,7 @@ baredsc baredsc_1d, baredsc_2d, baredsc_combine_1d, baredsc_combine_2d baredSC barrnap 3938.0 160.0 barrnap Contains the Barrnap tool for finding ribosomal RNAs in FASTA sequences. barrnap Barrnap Predict the location of ribosomal RNA genes in genomes. It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S), mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S). Gene prediction Genomics, Model organisms, Model organisms To update Sequence Analysis barrnap iuc 1.2.2 barrnap 0.9 (0/1) (1/1) (1/1) True False bax2bam 200.0 8.0 bax2bam BAX to BAM converter Up-to-date https://github.com/pacificbiosciences/bax2bam/ Convert Formats, Sequence Analysis bax2bam iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/pax2bam 0.0.11 bax2bam 0.0.11 (1/1) (0/1) (1/1) True False bayescan 64.0 8.0 BayeScan Detecting natural selection from population-based genetic data bayescan BayeScan BAYEsian genome SCAN for outliers, aims at identifying candidate loci under natural selection from genetic data, using differences in allele frequencies between populations. It is based on the multinomial-Dirichlet model. Statistical inference Genetics, Evolutionary biology, Statistics and probability, DNA polymorphism To update http://cmpg.unibe.ch/software/BayeScan/index.html Sequence Analysis bayescan iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/bayescan/ 2.1 bayescan 2.0.1 (0/1) (0/1) (1/1) True True -bbtools bbtools_bbduk, bbtools_bbmap, bbtools_bbmerge, bbtools_bbnorm, bbtools_callvariants, bbtools_tadpole BBTools is a suite of fast, multithreaded bioinformatics tools designed for analysis of DNA and RNA sequence data.BBTools can handle common sequencing file formats such as fastq, fasta, sam, scarf, fasta+qual, compressed or raw,with autodetection of quality encoding and interleaving. It is written in Java and works on any platform supportingJava, including Linux, MacOS, and Microsoft Windows and Linux; there are no dependencies other than Java (version7 or higher). Program descriptions and options are shown when running the shell scripts with no parameters. Up-to-date https://jgi.doe.gov/data-and-tools/bbtools/ Sequence Analysis bbtools iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/bbtools 39.01 bbmap 39.01 (1/6) (1/6) (5/6) True False +bbtools bbtools_bbduk, bbtools_bbmap, bbtools_bbmerge, bbtools_bbnorm, bbtools_callvariants, bbtools_tadpole BBTools is a suite of fast, multithreaded bioinformatics tools designed for analysis of DNA and RNA sequence data.BBTools can handle common sequencing file formats such as fastq, fasta, sam, scarf, fasta+qual, compressed or raw,with autodetection of quality encoding and interleaving. It is written in Java and works on any platform supportingJava, including Linux, MacOS, and Microsoft Windows and Linux; there are no dependencies other than Java (version7 or higher). Program descriptions and options are shown when running the shell scripts with no parameters. To update https://jgi.doe.gov/data-and-tools/bbtools/ Sequence Analysis bbtools iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/bbtools 39.01 bbmap 39.06 (1/6) (1/6) (5/6) True False bctools bctools_convert_to_binary_barcode, bctools_extract_crosslinked_nucleotides, bctools_extract_alignment_ends, bctools_extract_barcodes, bctools_merge_pcr_duplicates, bctools_remove_tail, bctools_remove_spurious_events bctools is a set of tools for handling barcodes and UMIs in NGS data.bctools can be used to merge PCR duplicates according to unique molecular barcodes (UMIs),to extract barcodes from arbitrary positions relative to the read starts,to clean up readthroughs into UMIs with paired-end sequencing andhandles binary barcodes as used with uvCLAP and FLASH.License: Apache License 2.0 Up-to-date https://github.com/dmaticzka/bctools Sequence Analysis, Transcriptomics iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/bedtools 0.2.2 bctools 0.2.2 (0/7) (0/7) (7/7) True False bellerophon 1194.0 123.0 bellerophon Filter mapped reads where the mapping spans a junction, retaining the 5-prime read. Up-to-date https://github.com/davebx/bellerophon Sequence Analysis bellerophon iuc https://github.com/davebx/bellerophon 1.0 bellerophon 1.0 (1/1) (1/1) (1/1) True False binning_refiner 81.0 21.0 bin_refiner Reconciles the outputs of different binning programs with the aim to improve the quality of genome bins,especially with respect to contamination levels. binning_refiner Binning_refiner Improving genome bins through the combination of different binning programs Read binning, Sequence clustering Metagenomics Up-to-date https://github.com/songweizhi/Binning_refiner Metagenomics binning_refiner iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/binning_refiner/ 1.4.3 binning_refiner 1.4.3 (0/1) (0/1) (1/1) True True @@ -315,7 +315,7 @@ das_tool 550.0 17.0 Fasta_to_Contig2Bin, das_tool DAS Tool for genome resolved m deepsig 5.0 deepsig Predictor of signal peptides in proteins based on deep learning Up-to-date https://github.com/BolognaBiocomp/deepsig Genome annotation deepsig iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/deepsig 1.2.5 deepsig 1.2.5 (0/1) (0/1) (1/1) True False deseq2 95752.0 4990.0 deseq2 Differential gene expression analysis based on the negative binomial distribution DESeq2 DESeq2 R/Bioconductor package for differential gene expression analysis based on the negative binomial distribution. Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution. Differential gene expression analysis Transcriptomics To update https://www.bioconductor.org/packages/release/bioc/html/DESeq2.html Transcriptomics, RNA, Statistics deseq2 iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/deseq2 2.11.40.8 bioconductor-deseq2 1.42.0 (1/1) (1/1) (1/1) True False dexseq 16064.0 218.0 dexseq, dexseq_count, plotdexseq Inference of differential exon usage in RNA-Seq dexseq DEXSeq The package is focused on finding differential exon usage using RNA-seq exon counts between samples with different experimental designs. It provides functions that allows the user to make the necessary statistical tests based on a model that uses the negative binomial distribution to estimate the variance between biological replicates and generalized linear models for testing. The package also provides functions for the visualization and exploration of the results. Enrichment analysis, Exonic splicing enhancer prediction RNA-Seq To update https://www.bioconductor.org/packages/release/bioc/html/DEXSeq.html Transcriptomics, RNA, Statistics dexseq iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/dexseq 1.44 bioconductor-dexseq 1.48.0 (3/3) (3/3) (3/3) True False -diamond 49711.0 963.0 bg_diamond, bg_diamond_makedb, bg_diamond_view DIAMOND is a new alignment tool for aligning short DNA sequencing reads to a protein reference database such as NCBI-NR. diamond Diamond Sequence aligner for protein and translated DNA searches and functions as a drop-in replacement for the NCBI BLAST software tools. It is suitable for protein-protein search as well as DNA-protein search on short reads and longer sequences including contigs and assemblies, providing a speedup of BLAST ranging up to x20,000. Sequence alignment analysis Sequence analysis, Proteins To update https://github.com/bbuchfink/diamond Sequence Analysis diamond bgruening https://github.com/galaxyproject/tools-iuc/tree/master/tools/diamond 2.0.15 diamond 2.1.8 (3/3) (3/3) (3/3) True True +diamond 49711.0 963.0 bg_diamond, bg_diamond_makedb, bg_diamond_view DIAMOND is a new alignment tool for aligning short DNA sequencing reads to a protein reference database such as NCBI-NR. diamond Diamond Sequence aligner for protein and translated DNA searches and functions as a drop-in replacement for the NCBI BLAST software tools. It is suitable for protein-protein search as well as DNA-protein search on short reads and longer sequences including contigs and assemblies, providing a speedup of BLAST ranging up to x20,000. Sequence alignment analysis Sequence analysis, Proteins To update https://github.com/bbuchfink/diamond Sequence Analysis diamond bgruening https://github.com/galaxyproject/tools-iuc/tree/master/tools/diamond 2.0.15 diamond 2.1.9 (3/3) (3/3) (3/3) True True disco 369.0 42.0 disco DISCO is a overlap-layout-consensus (OLC) metagenome assembler disco DISCO DISCO is software to perform structure determination of protein homo-oligomers with cyclic symmetry.DISCO computes oligomeric protein structures using geometric constraints derived from RDCs and intermolecular distance restraints such as NOEs or disulfide bonds. When a reliable subunit structure can be calculated from intramolecular restraints, DISCO guarantees that all satisfying oligomer structures will be discovered, yet can run in minutes to hours on only a single desktop-class computer. Protein sequence analysis Structure determination To update http://disco.omicsbio.org/ Metagenomics, Assembly disco iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/disco/ disco 1.2 (1/1) (0/1) (1/1) True True dram dram_annotate, dram_distill, dram_merge_annotations, dram_neighborhoods, dram_strainer DRAM for distilling microbial metabolism to automate the curation of microbiome function To update https://github.com/WrightonLabCSU/DRAM Metagenomics dram iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/dram 1.3.5 dram 1.4.6 (0/5) (0/5) (5/5) True True drep drep_compare, drep_dereplicate dRep compares and dereplicates genome sets drep dRep Fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. Genome comparison Metagenomics, Genomics, Sequence analysis Up-to-date https://github.com/MrOlm/drep Metagenomics drep iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/drep 3.4.5 drep 3.4.5 (0/2) (0/2) (2/2) True True @@ -362,12 +362,12 @@ goenrichment 5206.0 321.0 goenrichment, goslimmer Performs GO Enrichment analysi goseq 19167.0 1210.0 goseq goseq does selection-unbiased testing for category enrichment amongst differentially expressed (DE) genes for RNA-seq data goseq GOseq Detect Gene Ontology and/or other user defined categories which are over/under represented in RNA-seq data. Gene functional annotation RNA-Seq To update https://bioconductor.org/packages/release/bioc/html/goseq.html Statistics, RNA, Micro-array Analysis goseq iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq 1.50.0 bioconductor-goseq 1.54.0 (1/1) (1/1) (1/1) True True graphlan 5002.0 247.0 graphlan, graphlan_annotate GraPhlAn is a software tool for producing high-quality circular representations of taxonomic and phylogenetic trees To update https://bitbucket.org/nsegata/graphlan/overview Metagenomics, Graphics, Phylogenetics graphlan iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/humann2/ graphlan 1.1.3 (2/2) (2/2) (2/2) True True gtdbtk gtdbtk_classify_wf GTDB-Tk is a software tool kit for assigning objective taxonomic classifications to bacterial and archaeal genomesbased on the Genome Database Taxonomy GTDB. It is designed to work with recent advances that allow hundreds orthousands of metagenome-assembled genomes (MAGs) to be obtained directly from environmental samples. It can alsobe applied to isolate and single-cell genomes. To update https://github.com/Ecogenomics/GTDBTk Metagenomics gtdbtk iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/gtdbtk 2.2.2 gtdbtk 2.3.2 (0/1) (1/1) (0/1) True True -gubbins 3340.0 145.0 gubbins Gubbins - bacterial recombination detection gubbins Gubbins Gubbins is a tool for rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences. Genotyping, Phylogenetic inference, Ancestral reconstruction Phylogeny, Genotype and phenotype, Whole genome sequencing To update Sequence Analysis gubbins iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/gubbins 3.2.1 gubbins 3.3.1 (1/1) (1/1) (1/1) True True +gubbins 3340.0 145.0 gubbins Gubbins - bacterial recombination detection gubbins Gubbins Gubbins is a tool for rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences. Genotyping, Phylogenetic inference, Ancestral reconstruction Phylogeny, Genotype and phenotype, Whole genome sequencing To update Sequence Analysis gubbins iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/gubbins 3.2.1 gubbins 3.3.3 (1/1) (1/1) (1/1) True True gwastools gwastools_manhattan_plot gwastools GWASTools Classes for storing very large GWAS data sets and annotation, and functions for GWAS data cleaning and analysis. Deposition, Analysis, Annotation GWAS study To update https://bioconductor.org/packages/release/bioc/html/GWASTools.html Visualization, Variant Analysis iuc 0.1.0 bioconductor-gwastools 1.48.0 (0/1) (0/1) (0/1) True False hamronization hamronize_summarize, hamronize_tool Convert AMR gene detection tool output to hAMRonization specification format. To update https://github.com/pha4ge/hAMRonization Sequence Analysis hamronization iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/hamronization 1.0.3 hamronization 1.1.4 (0/2) (0/2) (2/2) True True hansel bio_hansel Heidelberg and Enteritidis SNP Elucidation Biohansel BioHansel BioHansel is a tool for performing high-resolution genotyping of bacterial isolates by identifying phylogenetically informative single nucleotide polymorphisms (SNPs), also known as canonical SNPs, in whole genome sequencing (WGS) data. The application uses a fast k-mer matching algorithm to map pathogen WGS data to canonical SNPs contained in hierarchically structured schemas and assigns genotypes based on the detected SNP profile. Genotyping, SNP detection, Genome assembly Whole genome sequencing, DNA polymorphism, Genotype and phenotype, Infectious disease, Agricultural science Up-to-date https://github.com/phac-nml/bio_hansel Sequence Analysis bio_hansel iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/hansel 2.6.1 bio_hansel 2.6.1 (1/1) (0/1) (1/1) True True hapcut2 hapcut2 Robust and accurate haplotype assembly for diverse sequencing technologies hapcut2 HapCUT2 "HapCUT2 is a maximum-likelihood-based tool for assembling haplotypes from DNA sequence reads, designed to ""just work"" with excellent speed and accuracy across a range of long- and short-read sequencing technologies.The output is in Haplotype block format described here: https://github.com/vibansal/HapCUT2/blob/master/outputformat.md" Haplotype mapping, Variant classification Up-to-date https://github.com/vibansal/HapCUT2 Assembly hapcut2 galaxy-australia https://github.com/galaxyproject/tools-iuc 1.3.3 hapcut2 1.3.3 (0/1) (1/1) (0/1) True False -hapog 295.0 36.0 hapog Hapo-G - Haplotype-Aware Polishing of Genomes To update https://github.com/institut-de-genomique/HAPO-G Assembly hapog iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/hapog 1.3.6 hapog 1.3.7 (0/1) (0/1) (1/1) True False +hapog 295.0 36.0 hapog Hapo-G - Haplotype-Aware Polishing of Genomes hapog Hapo-G Hapo-G is a tool that aims to improve the quality of genome assemblies by polishing the consensus with accurate reads. It capable of incorporating phasing information from high-quality reads (short or long-reads) to polish genome assemblies and in particular assemblies of diploid and heterozygous genomes. Genome assembly, Optimisation and refinement Sequence assembly, Genomics Up-to-date https://github.com/institut-de-genomique/HAPO-G Assembly hapog iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/hapog 1.3.7 hapog 1.3.7 (0/1) (0/1) (1/1) True False heatmap2 ggplot2_heatmap2 heatmap.2 function from the R gplots package To update https://github.com/cran/gplots Visualization ggplot2_heatmap2 iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/heatmap2 3.1.3 r-gplots 2.17.0 (1/1) (1/1) (1/1) True False heinz 1186.0 242.0 heinz_bum, heinz, heinz_scoring, heinz_visualization An algorithm for identification of the optimal scoring subnetwork. bionet BioNet This package provides functions for the integrated analysis of protein-protein interaction networks and the detection of functional modules. Different datasets can be integrated into the network by assigning p-values of statistical tests to the nodes of the network. By fitting a beta-uniform mixture model and calculating scores from these p-values, overall scores of network regions can be calculated and an integer linear programming algorithm identifies the maximum scoring subnetwork. Protein interaction analysis Molecular interactions, pathways and networks, Protein interactions To update https://github.com/ls-cwi/heinz Transcriptomics, Visualization, Statistics heinz iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/heinz 1.0 bioconductor-bionet 1.62.0 (4/4) (4/4) (4/4) True False hicexplorer hicexplorer_chicaggregatestatistic, hicexplorer_chicdifferentialtest, hicexplorer_chicexportdata, hicexplorer_chicplotviewpoint, hicexplorer_chicqualitycontrol, hicexplorer_chicsignificantinteractions, hicexplorer_chicviewpoint, hicexplorer_chicviewpointbackgroundmodel, hicexplorer_hicadjustmatrix, hicexplorer_hicaggregatecontacts, hicexplorer_hicaverageregions, hicexplorer_hicbuildmatrix, hicexplorer_hiccomparematrices, hicexplorer_hiccompartmentspolarization, hicexplorer_hicconvertformat, hicexplorer_hiccorrectmatrix, hicexplorer_hiccorrelate, hicexplorer_hicdetectloops, hicexplorer_hicdifferentialtad, hicexplorer_hicfindrestrictionsites, hicexplorer_hicfindtads, hicexplorer_hichyperoptDetectLoops, hicexplorer_hicinfo, hicexplorer_hicinterintratad, hicexplorer_hicmergedomains, hicexplorer_hicmergeloops, hicexplorer_hicmergematrixbins, hicexplorer_hicnormalize, hicexplorer_hicpca, hicexplorer_hicplotaverageregions, hicexplorer_hicplotdistvscounts, hicexplorer_hicplotmatrix, hicexplorer_hicplotsvl, hicexplorer_hicplotviewpoint, hicexplorer_hicquickqc, hicexplorer_hicsummatrices, hicexplorer_hictadclassifier, hicexplorer_hictraintadclassifier, hicexplorer_hictransform, hicexplorer_hicvalidatelocations HiCExplorer: Set of programs to process, analyze and visualize Hi-C data. To update https://github.com/deeptools/HiCExplorer Sequence Analysis, Visualization hicexplorer bgruening https://github.com/galaxyproject/tools-iuc/tree/master/tools/hicexplorer 3.7.2 hicexplorer 3.7.3 (0/40) (5/40) (40/40) True False @@ -376,7 +376,7 @@ hifiasm_meta 137.0 12.0 hifiasm_meta A hifiasm fork for metagenome assembly usin hisat2 299104.0 4183.0 hisat2 HISAT2 is a fast and sensitive spliced alignment program. hisat2 HISAT2 Alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Sequence alignment RNA-seq Up-to-date http://ccb.jhu.edu/software/hisat2/ Assembly hisat2 iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/hisat2 2.2.1 hisat2 2.2.1 (1/1) (1/1) (1/1) True False hmmer3 21049.0 111.0 hmmer_alimask, hmmer_hmmalign, hmmer_hmmbuild, hmmer_hmmconvert, hmmer_hmmemit, hmmer_hmmfetch, hmmer_hmmscan, hmmer_hmmsearch, hmmer_jackhmmer, hmmer_nhmmer, hmmer_nhmmscan, hmmer_phmmer HMMER is used for searching sequence databases for homologs of proteinsequences, and for making protein sequence alignments. It implementsmethods using probabilistic models called profile hidden Markov models(profile HMMs). hmmer3 HMMER3 This tool is used for searching sequence databases for homologs of protein sequences, and for making protein sequence alignments. It implements methods using probabilistic models called profile hidden Markov models. The new HMMER3 project, HMMER is now as fast as BLAST for protein search. Formatting, Multiple sequence alignment, Sequence profile generation, Format validation, Conversion, Sequence generation, Data retrieval, Statistical calculation, Database search, Formatting, Database search, Database search, Probabilistic sequence generation, Statistical calculation, Statistical calculation, Sequence database search, Formatting, Sequence database search, Database search, Sequence database search Sequence analysis, Sequence sites, features and motifs, Gene and protein families To update http://hmmer.org/ Sequence Analysis iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/hmmer3 3.3.2 hmmer 3.4 (0/12) (12/12) (12/12) True True homer homer_annotatePeaks, homer_findMotifs, homer_findMotifsGenome, homer_gtf_to_annotations, homer_scanMotifGenomeWide HOMER (Hypergeometric Optimization of Motif EnRichment) is a suite of tools for Motif Discovery and next-gen sequencing analysis. homer homer HOMER contains a novel motif discovery algorithm that was designed for regulatory element analysis in genomics applications (DNA only, no protein). It is a differential motif discovery algorithm, which means that it takes two sets of sequences and tries to identify the regulatory elements that are specifically enriched in on set relative to the other. It uses ZOOPS scoring (zero or one occurrence per sequence) coupled with the hypergeometric enrichment calculations (or binomial) to determine motif enrichment. HOMER also tries its best to account for sequenced bias in the dataset. It was designed with ChIP-Seq and promoter analysis in mind, but can be applied to pretty much any nucleic acids motif finding problem. Sequence motif discovery Up-to-date http://homer.ucsd.edu/homer/index.html Sequence Analysis data_manager_homer_preparse iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/homer 4.11 homer 4.11 (0/5) (0/5) (5/5) True False -htseq_count 154533.0 1419.0 htseq_count Count aligned reads (SAM/BAM) that overlap genomic features (GFF) htseq HTSeq Python framework to process and analyse high-throughput sequencing (HTS) data Nucleic acid sequence analysis Sequence analysis To update https://readthedocs.org/projects/htseq/ Genomic Interval Operations, SAM, Sequence Analysis, RNA htseq_count lparsons https://github.com/galaxyproject/tools-iuc/tree/master/tools/htseq_count 0.9.1+galaxy1 htseq 2.0.5 (1/1) (1/1) (1/1) True False +htseq_count 154533.0 1419.0 htseq_count Count aligned reads (SAM/BAM) that overlap genomic features (GFF) htseq HTSeq Python framework to process and analyse high-throughput sequencing (HTS) data Nucleic acid sequence analysis Sequence analysis Up-to-date https://readthedocs.org/projects/htseq/ Genomic Interval Operations, SAM, Sequence Analysis, RNA htseq_count lparsons https://github.com/galaxyproject/tools-iuc/tree/master/tools/htseq_count 2.0.5 htseq 2.0.5 (1/1) (1/1) (1/1) True False humann 5856.0 247.0 humann, humann_associate, humann_barplot, humann_join_tables, humann_reduce_table, humann_regroup_table, humann_rename_table, humann_renorm_table, humann_rna_dna_norm, humann_split_stratified_table, humann_split_table, humann_strain_profiler, humann_unpack_pathways HUMAnN for functionally profiling metagenomes and metatranscriptomes at species-level resolution humann humann HUMAnN is a pipeline for efficiently and accurately profiling the presence/absence and abundance of microbial pathways in a community from metagenomic or metatranscriptomic sequencing data (typically millions of short DNA/RNA reads). This process, referred to as functional profiling, aims to describe the metabolic potential of a microbial community and its members. More generally, functional profiling answers the question “What are the microbes in my community-of-interest doing (or are capable of doing)?” Species frequency estimation, Taxonomic classification, Phylogenetic analysis Metagenomics, Phylogenomics Up-to-date http://huttenhower.sph.harvard.edu/humann Metagenomics humann iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/humann 3.8 humann 3.8 (6/13) (6/13) (13/13) True True hybpiper hybpiper Analyse targeted sequence capture data HybPiper HybPiper Paralogs and off-target sequences improve phylogenetic resolution in a densely-sampled study of the breadfruit genus (Artocarpus, Moraceae).Recovering genes from targeted sequence capture data.Current version: 1.3.1 (August 2018).-- Read our article in Applications in Plant Sciences (Open Access).HybPiper was designed for targeted sequence capture, in which DNA sequencing libraries are enriched for gene regions of interest, especially for phylogenetics. HybPiper is a suite of Python scripts that wrap and connect bioinformatics tools in order to extract target sequences from high-throughput DNA sequencing reads. Sequence trimming, Sequence assembly, Read mapping Phylogenetics, Plant biology, Gene transcripts, Sequence assembly, Phylogenomics Up-to-date https://github.com/mossmatters/HybPiper Sequence Analysis, Phylogenetics hybpiper iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/hybpiper 2.1.6 hybpiper 2.1.6 (0/1) (1/1) (0/1) True False hyphy hyphy_absrel, hyphy_annotate, hyphy_bgm, hyphy_busted, hyphy_cfel, hyphy_conv, hyphy_fade, hyphy_fel, hyphy_fubar, hyphy_gard, hyphy_meme, hyphy_prime, hyphy_relax, hyphy_slac, hyphy_sm19, hyphy_strike_ambigs, hyphy_summary Hypothesis Testing using Phylogenies HyPhy HyPhy Software package for the analysis of genetic sequences using techniques in phylogenetics, molecular evolution, and machine learning. Statistical calculation Phylogeny, Small molecules, Molecular interactions, pathways and networks To update http://www.hyphy.org Phylogenetics iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/hyphy/ 2.5.47 hyphy 2.5.59 (17/17) (2/17) (17/17) True True @@ -403,7 +403,7 @@ kraken_biom 1444.0 182.0 kraken_biom Create BIOM-format tables (http://biom-form kraken_taxonomy_report 2527.0 354.0 kraken_taxonomy_report Kraken taxonomy report To update https://github.com/blankenberg/Kraken-Taxonomy-Report Metagenomics kraken_taxonomy_report iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/kraken_taxonomy_report 0.0.3 biopython 1.70 (1/1) (0/1) (1/1) True True krakentools krakentools_alpha_diversity, krakentools_beta_diversity, krakentools_combine_kreports, krakentools_extract_kraken_reads, krakentools_kreport2krona, krakentools_kreport2mpa KrakenTools is a suite of scripts to be used alongside the Kraken krakentools KrakenTools KrakenTools provides individual scripts to analyze Kraken/Kraken2/Bracken/KrakenUniq output files Visualisation, Aggregation Taxonomy, Metagenomics Up-to-date https://github.com/jenniferlu717/KrakenTools Metagenomics krakentools iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/krakentools 1.2 krakentools 1.2 (1/6) (2/6) (6/6) True True krocus krocus Predict MLST directly from uncorrected long reads To update https://github.com/quadram-institute-bioscience/krocus Sequence Analysis krocus iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/krocus 1.0.1 krocus 1.0.3 (0/1) (0/1) (0/1) True True -last 227.0 41.0 last_al, last_db, last_split, last_train, last_maf_convert LAST finds similar regions between sequences. last LAST Short read alignment program incorporating quality scores Sequence alignment Genomics, Comparative genomics To update http://last.cbrc.jp/ Sequence Analysis last iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/last 1205 last 1526 (0/5) (0/5) (5/5) True False +last 227.0 41.0 last_al, last_db, last_split, last_train, last_maf_convert LAST finds similar regions between sequences. last LAST Short read alignment program incorporating quality scores Sequence alignment Genomics, Comparative genomics To update http://last.cbrc.jp/ Sequence Analysis last iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/last 1205 last 1540 (0/5) (0/5) (5/5) True False legsta 55.0 7.0 legsta Performs in silico Legionella pneumophila sequence based typing. Up-to-date https://github.com/tseemann/legsta Sequence Analysis legsta iuc https://github.com/tseemann/legsta 0.5.1 legsta 0.5.1 (0/1) (0/1) (1/1) True True length_and_gc_content 4090.0 322.0 length_and_gc_content Gets gene length and gc content from a fasta and a GTF file To update https://github.com/galaxyproject/tools-iuc/tree/master/tools/length_and_gc_content Fasta Manipulation, Statistics, RNA, Micro-array Analysis length_and_gc_content iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/length_and_gc_content 0.1.2 r-optparse 1.3.2 (1/1) (1/1) (1/1) True False limma_voom 20344.0 1012.0 limma_voom Perform RNA-Seq differential expression analysis using limma voom pipeline limma limma Data analysis, linear models and differential expression for microarray data. RNA-Seq analysis Molecular biology, Genetics To update http://bioconductor.org/packages/release/bioc/html/limma.html Transcriptomics, RNA, Statistics limma_voom iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/limma_voom 3.50.1 bioconductor-limma 3.58.1 (1/1) (1/1) (1/1) True False @@ -422,7 +422,7 @@ mcl 29.0 10.0 mcl The Markov Cluster Algorithm, a cluster algorithm for graphs m medaka medaka_consensus, medaka_consensus_pipeline, medaka_snp, medaka_variant Sequence correction provided by ONT Research medaka Medaka medaka is a tool to create consensus sequences and variant calls from nanopore sequencing data. This task is performed using neural networks applied a pileup of individual sequencing reads against a draft assembly. Base-calling, Variant calling, Sequence assembly Sequence assembly, Machine learning To update https://github.com/nanoporetech/medaka Sequence Analysis iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/medaka 1.7.2 medaka 1.11.3 (3/4) (3/4) (3/4) True True megahit 9530.0 548.0 megahit An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. megahit MEGAHIT Single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct de Bruijn graph to achieve low memory usage, whereas its goal is not to make memory usage as low as possible. Genome assembly Metagenomics, Sequencing, Ecology, Sequence assembly Up-to-date https://github.com/voutcn/megahit Sequence Analysis, Assembly, Metagenomics megahit iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/megahit 1.2.9 megahit 1.2.9 (1/1) (1/1) (1/1) True True megahit_contig2fastg 475.0 54.0 megahit_contig2fastg A subprogram within the Megahit toolkit for converting contigs to assembly graphs (fastg) megahit MEGAHIT Single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct de Bruijn graph to achieve low memory usage, whereas its goal is not to make memory usage as low as possible. Genome assembly Metagenomics, Sequencing, Ecology, Sequence assembly To update https://github.com/voutcn/megahit/blob/master/tools/toolkit.cpp Sequence Analysis, Assembly, Metagenomics megahit_contig2fastg iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/megahit_contig2fastg 1.1.3 megahit 1.2.9 (1/1) (0/1) (1/1) True True -megan megan_blast2lca, megan_blast2rma, megan_daa2info, megan_daa2rma, megan_daa_meganizer, megan_read_extractor, megan_sam2rma MEGAN Community Edition - Interactive exploration and analysis of large-scale microbiome sequencing data. MEGAN is a tool for studying the taxonomic content of a set of DNA reads, typically collected in a metagenomics project.In a preprocessing step, a sequence alignment of all reads against a suitable database of reference DNA or proteinsequences must be performed to produce an input file for the program. MEGAN is suitable for DNA reads (metagenomedata), RNA reads (metatranscriptome data), peptide sequences (metaproteomics data) and, using a suitable synonymsfile that maps SILVA ids to taxon ids, for 16S rRNA data (amplicon sequencing). megan MEGAN Metagenome Analysis Software - MEGAN (MEtaGenome ANalyzer) is a new computer program that allows laptop analysis of large metagenomic datasets. In a preprocessing step, the set of DNA reads (or contigs) is compared against databases of known sequences using BLAST or another comparison tool. MEGAN can then be used to compute and interactively explore the taxonomical content of the dataset, employing the NCBI taxonomy to summarize and order the results. Sequence analysis, Taxonomic classification Sequence analysis To update https://github.com/husonlab/megan-ce Sequence Analysis megan iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/megan 6.21.7 megan 6.24.20 (0/7) (0/7) (7/7) True True +megan megan_blast2lca, megan_blast2rma, megan_daa2info, megan_daa2rma, megan_daa_meganizer, megan_read_extractor, megan_sam2rma MEGAN Community Edition - Interactive exploration and analysis of large-scale microbiome sequencing data. MEGAN is a tool for studying the taxonomic content of a set of DNA reads, typically collected in a metagenomics project.In a preprocessing step, a sequence alignment of all reads against a suitable database of reference DNA or proteinsequences must be performed to produce an input file for the program. MEGAN is suitable for DNA reads (metagenomedata), RNA reads (metatranscriptome data), peptide sequences (metaproteomics data) and, using a suitable synonymsfile that maps SILVA ids to taxon ids, for 16S rRNA data (amplicon sequencing). megan MEGAN Metagenome Analysis Software - MEGAN (MEtaGenome ANalyzer) is a new computer program that allows laptop analysis of large metagenomic datasets. In a preprocessing step, the set of DNA reads (or contigs) is compared against databases of known sequences using BLAST or another comparison tool. MEGAN can then be used to compute and interactively explore the taxonomical content of the dataset, employing the NCBI taxonomy to summarize and order the results. Sequence analysis, Taxonomic classification Sequence analysis To update https://github.com/husonlab/megan-ce Sequence Analysis megan iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/megan 6.21.7 megan 6.25.9 (0/7) (0/7) (7/7) True True meningotype meningotype Assign sequence type to N. meningitidis genome assemblies Up-to-date https://github.com/MDU-PHL/meningotype Sequence Analysis meningotype iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/meningotype 0.8.5 meningotype 0.8.5 (0/1) (0/1) (0/1) True True merqury 2483.0 244.0 merqury Merqury is a tool for evaluating genomes assemblies based of k-mer operations. merqury Merqury Reference-free quality, completeness, and phasing assessment for genome assemblies.Evaluate genome assemblies with k-mers and more.Often, genome assembly projects have illumina whole genome sequencing reads available for the assembled individual.Merqury provides a set of tools for this purpose. Genome assembly, k-mer counting, Scaffolding, Phasing, De-novo assembly Sequence assembly, Whole genome sequencing, Plant biology Up-to-date https://github.com/marbl/merqury Assembly merqury iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/merqury 1.3 merqury 1.3 (1/1) (1/1) (1/1) True True meryl 6785.0 350.0 meryl Meryl a k-mer counter. meryl Meryl Meryl is a tool for counting and working with sets of k-mers that was originally developed for use in the Celera Assembler and has since been migrated and maintained as part of Canu. k-mer counting Whole genome sequencing, Genomics, Sequence analysis, Sequencing Up-to-date https://github.com/marbl/meryl Assembly meryl iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/meryl 1.3 merqury 1.3 (1/1) (1/1) (1/1) True True @@ -519,7 +519,7 @@ scpipe 628.0 11.0 scpipe A flexible preprocessing pipeline for single-cell RNA-s semibin 183.0 10.0 semibin_bin, semibin_concatenate_fasta, semibin_generate_cannot_links, semibin_generate_sequence_features, semibin, semibin_train SemiBin: Semi-supervised Metagenomic Binning Using Siamese Neural Networks semibin SemiBin Command tool for metagenomic binning with semi-supervised deep learning using information from reference genomes. Sequence assembly, Read binning Metagenomics, Machine learning, Microbial ecology, Sequence assembly Up-to-date https://semibin.readthedocs.io/en/latest/ Metagenomics semibin iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/semibin 2.0.2 semibin 2.0.2 (0/6) (0/6) (6/6) True True seq2hla 288.0 16.0 seq2hla Precision HLA typing and expression from RNAseq data seq2hla Seq2HLA seq2HLA is a computational tool to determine Human Leukocyte Antigen (HLA) directly from existing and future short RNA-Seq reads. It takes standard RNA-Seq sequence reads in fastq format as input, uses a bowtie index comprising known HLA alleles and outputs the most likely HLA class I and class II types, a p-value for each call, and the expression of each class. Read mapping, Genetic variation analysis Transcriptomics, Mapping Up-to-date https://github.com/TRON-Bioinformatics/seq2HLA Sequence Analysis seq2hla iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/seq2hla 2.3 seq2hla 2.3 (0/1) (0/1) (1/1) True False seqcomplexity 68.0 16.0 seqcomplexity Sequence complexity for raw reads Up-to-date https://github.com/stevenweaver/seqcomplexity Sequence Analysis iuc https://github.com/stephenshank/tools-iuc/tree/seqcomplexity/tools/seqcomplexity/ 0.1.2 seqcomplexity 0.1.2 (1/1) (0/1) (1/1) True False -seqkit seqkit_fx2tab, seqkit_locate, seqkit_stats A cross-platform and ultrafast toolkit for FASTA/Q file manipulation seqkit seqkit FASTA and FASTQ are basic and ubiquitous formats for storing nucleotide and protein sequences. Common manipulations of FASTA/Q file include converting, searching, filtering, deduplication, splitting, shuffling, and sampling. Existing tools only implement some of these manipulations, and not particularly efficiently, and some are only available for certain operating systems. Furthermore, the complicated installation process of required packages and running environments can render these programs less user friendly. SeqKit demonstrates competitive performance in execution time and memory usage compared to similar tools. The efficiency and usability of SeqKit enable researchers to rapidly accomplish common FASTA/Q file manipulations. DNA transcription, Sequence trimming, DNA translation, Sequence conversion Database management, Sequence analysis To update https://bioinf.shenwei.me/seqkit/ Sequence Analysis seqkit iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/seqkit 2.3.1 seqkit 2.6.1 (0/3) (0/3) (3/3) True True +seqkit seqkit_fx2tab, seqkit_locate, seqkit_stats A cross-platform and ultrafast toolkit for FASTA/Q file manipulation seqkit seqkit FASTA and FASTQ are basic and ubiquitous formats for storing nucleotide and protein sequences. Common manipulations of FASTA/Q file include converting, searching, filtering, deduplication, splitting, shuffling, and sampling. Existing tools only implement some of these manipulations, and not particularly efficiently, and some are only available for certain operating systems. Furthermore, the complicated installation process of required packages and running environments can render these programs less user friendly. SeqKit demonstrates competitive performance in execution time and memory usage compared to similar tools. The efficiency and usability of SeqKit enable researchers to rapidly accomplish common FASTA/Q file manipulations. DNA transcription, Sequence trimming, DNA translation, Sequence conversion Database management, Sequence analysis To update https://bioinf.shenwei.me/seqkit/ Sequence Analysis seqkit iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/seqkit 2.3.1 seqkit 2.7.0 (0/3) (0/3) (3/3) True True seqsero2 12.0 seqsero2 Salmonella serotype prediction from genome sequencing data Up-to-date https://github.com/denglab/SeqSero2 Sequence Analysis seqsero2 iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/seqsero2 1.2.1 seqsero2 1.2.1 (0/1) (0/1) (1/1) False seqtk 59668.0 753.0 seqtk_comp, seqtk_cutN, seqtk_dropse, seqtk_fqchk, seqtk_hety, seqtk_listhet, seqtk_mergefa, seqtk_mergepe, seqtk_mutfa, seqtk_randbase, seqtk_sample, seqtk_seq, seqtk_subseq, seqtk_telo, seqtk_trimfq Toolkit for processing sequences in FASTA/Q formats seqtk seqtk A tool for processing sequences in the FASTA or FASTQ format. It parses both FASTA and FASTQ files which can also be optionally compressed by gzip. Data handling, Sequence file editing Data management Up-to-date https://github.com/lh3/seqtk Sequence Analysis seqtk iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/seqtk 1.4 seqtk 1.4 (15/15) (15/15) (15/15) True False seqwish 271.0 seqwish Alignment to variation graph inducer To update https://github.com/ekg/seqwish Sequence Analysis, Variant Analysis iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/seqwish/ 0.7.5 seqwish 0.7.9 (0/1) (0/1) (1/1) True False @@ -573,7 +573,7 @@ unicycler 65732.0 1558.0 unicycler Unicycler is a hybrid assembly pipeline for b usher 1060.0 5.0 usher_matutils, usher UShER toolkit wrappers To update https://github.com/yatisht/usher Phylogenetics usher iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/usher 0.2.1 usher 0.6.3 (0/2) (0/2) (2/2) True True valet 637.0 20.0 valet A pipeline for detecting mis-assemblies in metagenomic assemblies. To update https://github.com/marbl/VALET Metagenomics valet iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/valet valet 1.0 (1/1) (0/1) (1/1) True True vapor 3164.0 94.0 vapor Classify Influenza samples from raw short read sequence data vapor VAPOR VAPOR is a tool for classification of Influenza samples from raw short read sequence data for downstream bioinformatics analysis. VAPOR is provided with a fasta file of full-length sequences (> 20,000) for a given segment, a set of reads, and attempts to retrieve a reference that is closest to the sample strain. Data retrieval, De-novo assembly, Read mapping Whole genome sequencing, Mapping, Sequence assembly Up-to-date https://github.com/connor-lab/vapor Sequence Analysis vapor iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/vapor 1.0.2 vapor 1.0.2 (1/1) (0/1) (1/1) True True -varvamp varvamp Variable VirusAMPlicons (varVAMP) is a tool to design primers for highly diverse viruses varvamp varVAMP variable VirusAMPlicons (varVAMP) is a tool to design primers for highly diverse viruses. The input is an alignment of your viral (full-genome) sequences. PCR primer design Virology Up-to-date https://github.com/jonas-fuchs/varVAMP/ Sequence Analysis varvamp iuc https://github.com/jonas-fuchs/varVAMP 1.1.1 varvamp 1.1.1 (0/1) (0/1) (0/1) False +varvamp varvamp Variable VirusAMPlicons (varVAMP) is a tool to design primers for highly diverse viruses varvamp varVAMP variable VirusAMPlicons (varVAMP) is a tool to design primers for highly diverse viruses. The input is an alignment of your viral (full-genome) sequences. PCR primer design Virology Up-to-date https://github.com/jonas-fuchs/varVAMP/ Sequence Analysis varvamp iuc https://github.com/jonas-fuchs/varVAMP 1.1.1 varvamp 1.1.1 (0/1) (0/1) (1/1) False vegan vegan_diversity, vegan_fisher_alpha, vegan_rarefaction To update https://cran.r-project.org/package=vegan Metagenomics iuc https://github.com/galaxyproject/tools-iuc/tree/master/tools/vegan/ 2.4-3 r-vegan 2.3_4 (3/3) (0/3) (3/3) True True velvet 12218.0 1280.0 velvetg, velveth de novo genomic assembler specially designed for short read sequencing technologies velvet Velvet A de novo genomic assembler specially designed for short read sequencing technologies, such as Solexa or 454 or SOLiD. Formatting, De-novo assembly Sequence assembly To update https://www.ebi.ac.uk/~zerbino/velvet/ Assembly velvet devteam https://github.com/galaxyproject/tools-iuc/tree/master/tools/velvet velvet 1.2.10 (2/2) (2/2) (2/2) True True velvet_optimiser velvetoptimiser Automatically optimize Velvet assemblies velvetoptimiser VelvetOptimiser This tool is designed to run as a wrapper script for the Velvet assembler (Daniel Zerbino, EBI UK) and to assist with optimising the assembly. Optimisation and refinement, Sequence assembly Genomics, Sequence assembly To update Assembly velvetoptimiser simon-gladman https://github.com/galaxyproject/tools-iuc/tree/master/tools/velvetoptimiser 2.2.6+galaxy2 velvet 1.2.10 (1/1) (1/1) (1/1) True True From 66b0a0fbe1c59cdcd6d8df6c27272098870a6a82 Mon Sep 17 00:00:00 2001 From: Johan Gustafsson Date: Mon, 12 Feb 2024 09:14:49 +1030 Subject: [PATCH 02/96] Add paper.bib --- docs/publications/BioHackrXiv/paper.bib | 71 +++++++++++++++++++++++++ 1 file changed, 71 insertions(+) create mode 100644 docs/publications/BioHackrXiv/paper.bib diff --git a/docs/publications/BioHackrXiv/paper.bib b/docs/publications/BioHackrXiv/paper.bib new file mode 100644 index 00000000..3d6e8b1b --- /dev/null +++ b/docs/publications/BioHackrXiv/paper.bib @@ -0,0 +1,71 @@ +@article{10.1093/nar/gkac247, + author = {The Galaxy Community }, + title = "{The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update}", + journal = {Nucleic Acids Research}, + volume = {50}, + number = {W1}, + pages = {W345-W351}, + year = {2022}, + month = {04}, + abstract = "{Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with \\>230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.}", + issn = {0305-1048}, + doi = {10.1093/nar/gkac247}, + url = {https://doi.org/10.1093/nar/gkac247}, + eprint = {https://academic.oup.com/nar/article-pdf/50/W1/W345/45189566/gkac247.pdf}, +} + +@article{rost2016openms, + title={OpenMS: a flexible open-source software platform for mass spectrometry data analysis}, + author={R{\"o}st, Hannes L and Sachsenberg, Timo and Aiche, Stephan and Bielow, Chris and Weisser, Hendrik and Aicheler, Fabian and Andreotti, Sandro and Ehrlich, Hans-Christian and Gutenbrunner, Petra and Kenar, Erhan and others}, + journal={Nature methods}, + volume={13}, + number={9}, + pages={741--748}, + year={2016}, + publisher={Nature Publishing Group} +} + +@article{doi:10.1128/AEM.01541-09, +author = {Patrick D. Schloss and Sarah L. Westcott and Thomas Ryabin and Justine R. Hall and Martin Hartmann and Emily B. Hollister and Ryan A. Lesniewski and Brian B. Oakley and Donovan H. Parks and Courtney J. Robinson and Jason W. Sahl and Blaz Stres and Gerhard G. Thallinger and David J. Van Horn and Carolyn F. Weber}, +title = {Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities}, +journal = {Applied and Environmental Microbiology}, +volume = {75}, +number = {23}, +pages = {7537-7541}, +year = {2009}, +doi = {10.1128/AEM.01541-09}, +URL = {https://journals.asm.org/doi/abs/10.1128/aem.01541-09}, +eprint = {https://journals.asm.org/doi/pdf/10.1128/aem.01541-09}, +abstract = { mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the α and β diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer. } +} + +@article{black2021edam, + title={EDAM: The bioscientific data analysis ontology (update 2021)[version 1; not peer reviewed]}, + author={Black, Melissa and Lamothe, Lucie and Eldakroury, Hager and Kierkegaard, Mads and Priya, Ankita and Machinda, Anne and Singh Khanduja, Uttam and Patoliya, Drashti and Rathi, Rashika and Che Nico, Tawah Peggy and others}, + year={2021}, + publisher={F1000} +} + +@article{ison2016tools, + title={Tools and data services registry: a community effort to document bioinformatics resources}, + author={Ison, Jon and Rapacki, Kristoffer and M{\'e}nager, Herv{\'e} and Kala{\v{s}}, Mat{\'u}{\v{s}} and Rydza, Emil and Chmura, Piotr and Anthon, Christian and Beard, Niall and Berka, Karel and Bolser, Dan and others}, + journal={Nucleic acids research}, + volume={44}, + number={D1}, + pages={D38--D47}, + year={2016}, + publisher={Oxford University Press} +} + +@article {Bray2022.03.13.483965, + author = {Simon Bray and Matthias Bernt and Nicola Soranzo and Marius van den Beek and B{\'e}r{\'e}nice Batut and Helena Rasche and Martin {\v C}ech and Peter Cock and Anton Nekrutenko and Bj{\"o}rn Gr{\"u}ning and John Chilton}, + title = {Planemo: a command-line toolkit for developing, deploying, and executing scientific data analyses}, + elocation-id = {2022.03.13.483965}, + year = {2022}, + doi = {10.1101/2022.03.13.483965}, + publisher = {Cold Spring Harbor Laboratory}, + abstract = {There are thousands of well-maintained high-quality open-source software utilities for all aspects of scientific data analysis. For over a decade, the Galaxy Project has been providing computational infrastructure and a unified user interface for these tools to make them accessible to a wide range of researchers. In order to streamline the process of integrating tools and constructing workflows as much as possible, we have developed Planemo, a software development kit for tool and workflow developers and Galaxy power users. Here we outline Planemo{\textquoteright}s implementation and describe its broad range of functionality for designing, testing and executing Galaxy tools, workflows and training material. In addition, we discuss the philosophy underlying Galaxy tool and workflow development, and how Planemo encourages the use of development best practices, such as test-driven development, by its users, including those who are not professional software developers. Planemo is a mature project widely used within the Galaxy community which has been downloaded over 80,000 times.Competing Interest StatementThe authors have declared no competing interest.}, + URL = {https://www.biorxiv.org/content/early/2022/03/14/2022.03.13.483965}, + eprint = {https://www.biorxiv.org/content/early/2022/03/14/2022.03.13.483965.full.pdf}, + journal = {bioRxiv} +} From 96120c3bca2743013880b9b0a9828f96e298d0fa Mon Sep 17 00:00:00 2001 From: Johan Gustafsson Date: Mon, 12 Feb 2024 09:20:22 +1030 Subject: [PATCH 03/96] Add paper.md --- docs/publications/BioHackrXiv/paper.md | 105 +++++++++++++++++++++++++ 1 file changed, 105 insertions(+) create mode 100644 docs/publications/BioHackrXiv/paper.md diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md new file mode 100644 index 00000000..8018b500 --- /dev/null +++ b/docs/publications/BioHackrXiv/paper.md @@ -0,0 +1,105 @@ +--- +title: 'How to increase the findability, visibility, and impact of Galaxy tools for your scientific community' +title_short: 'BioHackEU23 project #25: Finding Galaxy tools' +tags: + - Findability + - Galaxy + - Community specific +authors: + - name: Paul Zierep* + orcid: + affiliation: 1 + - name: Berenice Batut + orcid: + affiliation: 2 + - name: Nicola Soranzo + orcid: 0000-0003-3627-5340 + affiliation: 3 + - name: Matúš Kalaš + orcid: + affiliation: 4 + - name: Ove Johan Ragnar Gustafsson + orcid: 0000-0002-2977-5032 + affiliation: 5 +affiliations: + - name: + index: 1 + - name: + index: 2 + - name: Earlham Institute, Norwich Research Park, Norwich, UK + index: 3 + - name: + index: 4 + - name: Australian BioCommons, University of Melbourne, Melbourne, Victoria, Australia + index: 5 +date: 12 February 2024 +bibliography: paper.bib +event: BioHackathon Europe 2023 +biohackathon_name: "BioHackathon Europe 2023" +biohackathon_url: "https://biohackathon-europe.org/" +biohackathon_location: "Barcelona, Spain, 2023" +group: BioHackrXiv +git_url: https://github.com/galaxyproject/galaxy_tool_metadata_extractor/tree/e604ffd9866f9c32f797ceee45062b4d6f2a1513/docs/publications/BioHackrXiv +authors_short: Zierep, P., Batut, B. \emph{et al.} (2024) BioHackEU23 project #25: Finding Galaxy tools + + +--- + +# Introduction or Background + +Add to this section a couple of paragraphs introducing the work done dring the BioHackathon, CodeFest, VoCamp or Sprint event. Please add references whenever needed, for instance [@Katayama:2010]. + +Please separate paragraphs with a double line. + +## Subsection level 2 + +Please keep sections to a maximum of three levels, even better if only two levels. + +### Subsection level 3 + +Please keep sections to a maximum of three levels. + +## Tables, figures and so on + +Please remember to introduce tables (see Table 1) before they appear on the document. We recommend to center tables, formulas and figure but not the corresponding captions. Feel free to modify the table style as it better suits to your data. + +Table 1 +| Header 1 | Header 2 | +| -------- | -------- | +| item 1 | item 2 | +| item 3 | item 4 | + +Remember to introduce figures (see Figure 1) before they appear on the document. + +![BioHackrXiv logo](./biohackrxiv.png) + +Figure 1. A figure corresponding to the logo of our BioHackrXiv preprint. + +# Other main section on your manuscript level 1 + +Feel free to use numbered lists or bullet points as you need. +* Item 1 +* Item 2 + +# Discussion and/or Conclusion + +We recommend to include some discussion or conclusion about your work. Feel free to modify the section title as it fits better to your manuscript. + +# Future work + +And maybe you want to add a sentence or two on how you plan to continue. Please keep reading to learn about citations and references. + +For citations of references, we prefer the use of parenthesis, last name and year. If you use a citation manager, Elsevier – Harvard or American Psychological Association (APA) will work. If you are referencing web pages, software or so, please do so in the same way. Whenever possible, add authors and year. We have included a couple of citations along this document for you to get the idea. Please remember to always add DOI whenever available, if not possible, please provide alternative URLs. You will end up with an alphabetical order list by authors’ last name. + +# Jupyter notebooks, GitHub repositories and data repositories + +* Please add a list here +* Make sure you let us know which of these correspond to Jupyter notebooks. Although not supported yet, we plan to add features for them +* And remember, software and data need a license for them to be used by others, no license means no clear rules so nobody could legally use a non-licensed research object, whatever that object is + +# Acknowledgements +Please always remember to acknowledge the BioHackathon, CodeFest, VoCamp, Sprint or similar where this work was (partially) developed. + +# References + +Leave thise section blank, create a paper.bib with all your references. \ No newline at end of file From 1c26565ed7e4a5b6d24585d1fc8fcac396caf0be Mon Sep 17 00:00:00 2001 From: Johan Gustafsson Date: Mon, 12 Feb 2024 09:22:23 +1030 Subject: [PATCH 04/96] Add intro to paper.md --- docs/publications/BioHackrXiv/paper.md | 15 +++++++++++++-- 1 file changed, 13 insertions(+), 2 deletions(-) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index 8018b500..6366b183 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -47,9 +47,20 @@ authors_short: Zierep, P., Batut, B. \emph{et al.} (2024) BioHackEU23 project #2 # Introduction or Background -Add to this section a couple of paragraphs introducing the work done dring the BioHackathon, CodeFest, VoCamp or Sprint event. Please add references whenever needed, for instance [@Katayama:2010]. +Galaxy[@10.1093/nar/gkac247] offers almost 10,000 tools that are developed across different Git repositories. Furthermore, Galaxy also embraces granular implementation of software tools as sub-modules. In practice, this means that tool suites are separated into Galaxy tools, also known as wrappers, that capture their component operations. Some key examples of suites include [Mothur](https://bio.tools/mothur)[@doi:10.1128/AEM.01541-09] and [OpenMS](https://bio.tools/openms)[@rost2016openms], which translate to tens and even hundreds of Galaxy tools. While granularity supports the sustainable development of rich domain-specific workflows, the reality is that this decentralized development and sub-module architecture makes it difficult for Galaxy users to find and reuse tools. It may also result in Galaxy developers replicating efforts by simultaneously wrapping new tools. This is further complicated by a lack of tool metadata, which prevents filtering for all tools in a specific research community or domain, and makes it all but impossible to employ advanced filtering with ontology terms and operations like EDAM[@black2021edam]. The final challenge is also an opportunity: the global nature of Galaxy means that it is a big community. Solving the visibility of tools across this ecosystem and the potential benefits are far-reaching for global collaboration on tool and workflow development. + + +To provide the research community with a comprehensive list of available Galaxy tools, a pipeline was developed at the ELIXIR BioHackathon Europe 2023 that collects Galaxy wrappers from a list of Git repositories and automatically extracts their metadata (including Conda version, bio.tools[@ison2016tools] identifiers, and EDAM annotations). The workflow also queries the availability of the tools and usage statistics from the three main Galaxy servers (usegalaxy.*). + + +Crucially, the pipeline can filter its inputs to only include tools that are relevant to a specific research community. Based on the selected filters, a community-specific interactive table is generated that can be embedded, e.g. into the respective Galaxy Hub page or Galaxy subdomain. This table allows further filtering and searching for fine-grained tool selection. The pipeline is fully automated and executes on a weekly basis. Any research community can apply the pipeline to create a table specific to their community. + + +An interactive table that presents metadata is only as useful as the metadata annotations it is capturing. To improve the metadata coverage for the interactive table, the project also directly addressed the quality of tool annotations in bio.tools for the microGalaxy community: a community with a focus on tools related to microbial research. Annotation guidelines were established for this purpose, the process of updating Galaxy tool wrappers to include bio.tools identifiers was started and the outcome of these activities was evaluated using a crowdsourced approach. During the BioHackathon Europe week, the annotation practices were applied to the tools selected from the microGalaxy community. This effort allowed the team to connect more than 50 tools to their respective bio.tools entry, update the registry entry, and peer-review the result. + + +The established pipeline and the annotation guidelines can support any research community to improve the findability, visibility, comparability, and accessibility of their Galaxy tools. Here we describe the methods and processes that resulted from this project and highlight how this will now allow the microGalaxy community to confidently navigate an ever-expanding landscape of research software in the Galaxy framework. -Please separate paragraphs with a double line. ## Subsection level 2 From 7963f6775b6a23801edf10a66aff938d693aae2c Mon Sep 17 00:00:00 2001 From: Johan Gustafsson Date: Mon, 12 Feb 2024 09:25:52 +1030 Subject: [PATCH 05/96] Add methods to paper.md --- docs/publications/BioHackrXiv/paper.md | 34 +++++++++++++++++++++++--- 1 file changed, 30 insertions(+), 4 deletions(-) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index 6366b183..40a42170 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -86,11 +86,37 @@ Remember to introduce figures (see Figure 1) before they appear on the document. Figure 1. A figure corresponding to the logo of our BioHackrXiv preprint. -# Other main section on your manuscript level 1 -Feel free to use numbered lists or bullet points as you need. -* Item 1 -* Item 2 + +# Methods + +## Domain-specific interactive tools table + +Galaxy tool wrapper suites are first parsed from multiple GitHub repositories. In effect, the repositories monitored by the planemo-monitor [@Bray2022.03.13.483965] are scraped using a custom script. The planemo-monitor is part of the Galaxy tool update infrastructure and keeps track of the most up-to-date tool development repositories. +Metadata is extracted from each tool wrapper suite. This includes: wrapper suite ID, scientific category, BioConda dependency, and a bio.tools repository URL. As a tool suite can be composed of multiple individual tools, the tool IDs for each tool are also extracted. +The bio.tools reference is used to request annotations via the bio.tools API, including bio.tools description, EDAM function, and EDAM operation[@black2021edam]. The conda package version is retrieved via the BioConda API and compared to the tool wrapper API to determine a tool’s update state (i.e. to update, no update required). +The Galaxy API is used to query if each tool is installed on one of the three large Galaxy servers ([usegalaxy.eu](https://usegalaxy.eu/), [usegalaxy.org](https://usegalaxy.org/), [usegalaxy.org.au](https://usegalaxy.org.au/)). Furthermore, the tool usage statistics can be retrieved from an SQL query that needs to be executed by Galaxy admins. The query used in the current implementation shows how many users executed a tool in the last 2 years on the european server ([usegalaxy.eu](https://usegalaxy.eu/)). +The output of the pipeline is a table that combines Galaxy wrappers with their metadata. The complete table can then be filtered to include only tools with relevance for specific communities. The initial filtering step is based on the scientific category, which is defined for every Galaxy wrapper. These categories are high-level and cannot distinguish between specific tool functions. However, they allow for the isolation of a subgroup of the initial table for further curation. The filtered table can be manually curated by community curators. The curation step involves annotating which of the extracted tools should be kept in the final table. Curators can use the EDAM annotations and tool descriptions to assist with this curation step. The labels for each tool are stored to reduce replication of effort even further. The practical outcome is that for repeat executions of the workflow, only new tools require curation. +The curated tools are transformed into an interactive web table using the data tables framework (**cite**). The table is hosted on GitHub and deployed via GitHub pages for each community. This implementation enables complex queries and filtering without the need for a database backend. The table can be embedded in any website via an iframe: examples include the Galaxy community Hub page for microGalaxy (**cite**) or a specific Galaxy subdomain (**cite**). Furthermore, a word cloud based on the usage statistics of the tools is created. +The workflow is scheduled via GitHub actions to run on a weekly basis, providing an up-to-date table for each community. The usage of an iframe enables updates for the table to propagate automatically to any website where it is deployed. Any Galaxy community can use the pipeline by adding a folder in the [GitHub repository](https://github.com/galaxyproject/galaxy_tool_extractor/data/communities). To initialize the pipeline for a new community you need to add a list of categories to a file called categories. Additionally tools that should be excluded or included after filtering can be added to respective files as well. A working example of the community configuration files can be found in the folder for the microgalaxy community. + +![Workflow of the Galaxy tool metadata extractor pipeline. Tool wrappers are parsed from different repositories and additional metadata is retrieved from bio.tools, BioConda, and the main public Galaxy servers. Upon filtering and manual curation of the data for specific scientific communities, the data is transformed into interactive web tables and a tool usage statistic-base word cloud, that can be integrated into any website. \label{metadata_extractor_pipeline}](./figures/________.png) + + +## Annotation workflow + +The annotation process begins by selecting a tool from a Galaxy community. This step can make use of the interactive table created by the Galaxy tool extractor scripts presented above. A curator then needs to visit the development repository of the Galaxy tool wrapper and check the *.xml file for a bio.tools xref snippet (Figure \ref{xref_snippet}). + +![xref snippet example for a Galaxy tool wrapper that contains the tool [Racon](https://bio.tools/Racon). \label{xref_snippet}](./figures/________.png) + +bio.tools is then checked to confirm that a bio.tools identifier does, or does not, exist. The reason for this is that even if a bio.tools identifier exists in a tool wrapper, it may not necessarily exist in bio.tools. This is an observation based on real-world annotation errors and serves as a useful supporting step to improve Galaxy wrapper annotations and the completeness of the bio.tools registry. In addition, if a bio.tools identifier is not included in the wrapper, this does not mean that there is not a bio.tools identifier available in the registry. +There are then two curation paths to choose from, depending on if a bio.tools identifier exists in the XML wrapper. In both cases, if no bio.tools entry exists, a new entry should be created and updated using the bio.tools wizard. The creation and update of an entry includes adding EDAM ontology topics and operations. This annotation process can be simplified through the use of [EDAM browser](https://edamontology.github.io/edam-browser/). + + +In the case where no bio.tools identifier exists in the Galaxy *.xml wrapper, the development repository needs to be forked and a new branch created. A new xref snippet can then be added, and a pull request (PR) generated against the original repository. +Figure \ref{annotation_workflow} shows a step-by-step breakdown of the above process. +![Step-by-step workflow for systematically improving metadata annotations across bio.tools registry entries and Galaxy tool wrappers. After selecting a Galaxy tool and checking for the presence of a bio.tools ID in its XML file, a curator needs to review bio.tools, create a new bio.tools entry (if needed), and then ensure that both this entry and the Galaxy tool XML file are up-to-date. Updating bio.tools makes use of the registry wizard, and updating a Galaxy tool wrapper to include a bio.tools xref snippet requires a pull request against the development repository. \label{annotation_workflow}](./figures/________.png) + # Discussion and/or Conclusion From c6001133ed6ea38028a5b066a055c0939dc8cadd Mon Sep 17 00:00:00 2001 From: Johan Gustafsson Date: Mon, 12 Feb 2024 09:28:56 +1030 Subject: [PATCH 06/96] Add results and conclusion to paper.md --- docs/publications/BioHackrXiv/paper.md | 36 +++++++++++++++++--------- 1 file changed, 24 insertions(+), 12 deletions(-) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index 40a42170..23bf9715 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -62,14 +62,6 @@ An interactive table that presents metadata is only as useful as the metadata an The established pipeline and the annotation guidelines can support any research community to improve the findability, visibility, comparability, and accessibility of their Galaxy tools. Here we describe the methods and processes that resulted from this project and highlight how this will now allow the microGalaxy community to confidently navigate an ever-expanding landscape of research software in the Galaxy framework. -## Subsection level 2 - -Please keep sections to a maximum of three levels, even better if only two levels. - -### Subsection level 3 - -Please keep sections to a maximum of three levels. - ## Tables, figures and so on Please remember to introduce tables (see Table 1) before they appear on the document. We recommend to center tables, formulas and figure but not the corresponding captions. Feel free to modify the table style as it better suits to your data. @@ -118,13 +110,33 @@ Figure \ref{annotation_workflow} shows a step-by-step breakdown of the above pro ![Step-by-step workflow for systematically improving metadata annotations across bio.tools registry entries and Galaxy tool wrappers. After selecting a Galaxy tool and checking for the presence of a bio.tools ID in its XML file, a curator needs to review bio.tools, create a new bio.tools entry (if needed), and then ensure that both this entry and the Galaxy tool XML file are up-to-date. Updating bio.tools makes use of the registry wizard, and updating a Galaxy tool wrapper to include a bio.tools xref snippet requires a pull request against the development repository. \label{annotation_workflow}](./figures/________.png) -# Discussion and/or Conclusion +# Outcomes and results + +There were multiple concrete outcomes from this BioHackathon project, including the interactive Galaxy tools table, a process for updating bio.tools, an in development GTN tutorial describing this process, and an update to the Galaxy IUC standards for tool wrapping. These are described in more detail below. + + +## Prototype interactive table for Galaxy communities + +The described workflow for the Galaxy tool metadata extractor (see Figure \ref{metadata_extractor_pipeline}) was successfully implemented (cite GitHub) and could collect 1,294 Galaxy tools suits (cite output). Of those tools suits, only 267 had a bio.tools identifier, which highlights the importance of performing the annotation process in parallel and complementing the tools with additional metadata. An example view of the created interactive table is shown in Figure \ref{web_table}. The filtered table for the microGalaxy community is embedded in the microGalaxy Galaxy Hub (cite) page as well as the dedicated microGalaxy subdomain (cite). + +![Screenshot of the interactive web table. The table provides comprehensive metadata for all Galaxy wrappers of a specific community and allows for custom searches based on logic filters over all columns. In the shown example, the user queries for all up-to-date tools that are annotated with the EDAM Operation assembly. \label{web_table}](./figures/________.png) + + +## bio.tools and EDAM annotations for microbiome community +During the week of the Biohackathon the microGalaxy community executed the annotation workflow as described in the Methods Section (see also Figure \ref{annotation_workflow}). The initial filtered tool table of the microGalaxy included 218 tool suites, of which 61 had corresponding bio.tools identifiers. The process of the work was tracked using a GitHub project board. After the annotation process, the number of tools with bio.tools annotations was increased to 107. The added annotations for each respective bio.tools entry was also collectively reviewed by the team. A rerun of the Galaxy tool metadata extractor pipeline collected the additional information, and the metadata is now included in the interactive microGalaxy tool table. + + +## Training materials and updates to standards +In order to provide the Galaxy research communities with simple and straightforward how-to to annotate their respective tool stacks, the described annotation workflow is currently being transformed into a Galaxy Training Network (GTN) tutorial. The guidelines created were also used to update the [best practices of the IUC repository](https://galaxy-iuc-standards.readthedocs.io/en/latest/best_practices/tool_xml.html). + + +# Conclusion and outlook + +The project was able to successfully meet its aim of creating reusable prototypes and processes that make the richness of the Galaxy tools ecosystem more discoverable and understandable. Central to this work was the Galaxy tool metadata extractor pipeline, which is currently generating comprehensive and interactive tabular summaries of Galaxy tools for the microbiome analysis and imaging domains within Galaxy, and which at publication can be reused by any Galaxy group or community. A set of updates to standards and processes was also created. These will support the on-going growth of the metadata hosted by the interactive tables: primarily by helping communities to maintain and extend the annotations of Galaxy tool wrappers, and the bio.tools ecosystem on which these wrapper annotations depend. + -We recommend to include some discussion or conclusion about your work. Feel free to modify the section title as it fits better to your manuscript. -# Future work -And maybe you want to add a sentence or two on how you plan to continue. Please keep reading to learn about citations and references. For citations of references, we prefer the use of parenthesis, last name and year. If you use a citation manager, Elsevier – Harvard or American Psychological Association (APA) will work. If you are referencing web pages, software or so, please do so in the same way. Whenever possible, add authors and year. We have included a couple of citations along this document for you to get the idea. Please remember to always add DOI whenever available, if not possible, please provide alternative URLs. You will end up with an alphabetical order list by authors’ last name. From de3ec4cc056af38a14cdcf93c395e555b2cfd6a6 Mon Sep 17 00:00:00 2001 From: Johan Gustafsson Date: Mon, 12 Feb 2024 09:32:36 +1030 Subject: [PATCH 07/96] Add acknowledgements to paper.md --- docs/publications/BioHackrXiv/paper.md | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index 23bf9715..55f43dff 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -147,8 +147,11 @@ For citations of references, we prefer the use of parenthesis, last name and yea * And remember, software and data need a license for them to be used by others, no license means no clear rules so nobody could legally use a non-licensed research object, whatever that object is # Acknowledgements -Please always remember to acknowledge the BioHackathon, CodeFest, VoCamp, Sprint or similar where this work was (partially) developed. + +This work was developed as part of BioHackathon Europe 2023. + +This work is supported by the Australian BioCommons which is enabled by NCRIS via Bioplatforms Australia funding. + # References -Leave thise section blank, create a paper.bib with all your references. \ No newline at end of file From f19a85602f6b3f85f6360a53ec22b549b9f4f73c Mon Sep 17 00:00:00 2001 From: Johan Gustafsson Date: Mon, 12 Feb 2024 09:39:07 +1030 Subject: [PATCH 08/96] Update paper.md --- docs/publications/BioHackrXiv/paper.md | 35 ++++++-------------------- 1 file changed, 8 insertions(+), 27 deletions(-) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index 55f43dff..ce423dfc 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -41,10 +41,9 @@ biohackathon_location: "Barcelona, Spain, 2023" group: BioHackrXiv git_url: https://github.com/galaxyproject/galaxy_tool_metadata_extractor/tree/e604ffd9866f9c32f797ceee45062b4d6f2a1513/docs/publications/BioHackrXiv authors_short: Zierep, P., Batut, B. \emph{et al.} (2024) BioHackEU23 project #25: Finding Galaxy tools - - --- + # Introduction or Background Galaxy[@10.1093/nar/gkac247] offers almost 10,000 tools that are developed across different Git repositories. Furthermore, Galaxy also embraces granular implementation of software tools as sub-modules. In practice, this means that tool suites are separated into Galaxy tools, also known as wrappers, that capture their component operations. Some key examples of suites include [Mothur](https://bio.tools/mothur)[@doi:10.1128/AEM.01541-09] and [OpenMS](https://bio.tools/openms)[@rost2016openms], which translate to tens and even hundreds of Galaxy tools. While granularity supports the sustainable development of rich domain-specific workflows, the reality is that this decentralized development and sub-module architecture makes it difficult for Galaxy users to find and reuse tools. It may also result in Galaxy developers replicating efforts by simultaneously wrapping new tools. This is further complicated by a lack of tool metadata, which prevents filtering for all tools in a specific research community or domain, and makes it all but impossible to employ advanced filtering with ontology terms and operations like EDAM[@black2021edam]. The final challenge is also an opportunity: the global nature of Galaxy means that it is a big community. Solving the visibility of tools across this ecosystem and the potential benefits are far-reaching for global collaboration on tool and workflow development. @@ -59,25 +58,7 @@ Crucially, the pipeline can filter its inputs to only include tools that are rel An interactive table that presents metadata is only as useful as the metadata annotations it is capturing. To improve the metadata coverage for the interactive table, the project also directly addressed the quality of tool annotations in bio.tools for the microGalaxy community: a community with a focus on tools related to microbial research. Annotation guidelines were established for this purpose, the process of updating Galaxy tool wrappers to include bio.tools identifiers was started and the outcome of these activities was evaluated using a crowdsourced approach. During the BioHackathon Europe week, the annotation practices were applied to the tools selected from the microGalaxy community. This effort allowed the team to connect more than 50 tools to their respective bio.tools entry, update the registry entry, and peer-review the result. -The established pipeline and the annotation guidelines can support any research community to improve the findability, visibility, comparability, and accessibility of their Galaxy tools. Here we describe the methods and processes that resulted from this project and highlight how this will now allow the microGalaxy community to confidently navigate an ever-expanding landscape of research software in the Galaxy framework. - - -## Tables, figures and so on - -Please remember to introduce tables (see Table 1) before they appear on the document. We recommend to center tables, formulas and figure but not the corresponding captions. Feel free to modify the table style as it better suits to your data. - -Table 1 -| Header 1 | Header 2 | -| -------- | -------- | -| item 1 | item 2 | -| item 3 | item 4 | - -Remember to introduce figures (see Figure 1) before they appear on the document. - -![BioHackrXiv logo](./biohackrxiv.png) - -Figure 1. A figure corresponding to the logo of our BioHackrXiv preprint. - +The established pipeline and the annotation guidelines can support any research community to improve the findability, visibility, comparability, and accessibility of their Galaxy tools. Here we describe the methods and processes that resulted from this project and highlight how this will now allow the microGalaxy community to confidently navigate an ever-expanding landscape of research software in the Galaxy framework. # Methods @@ -138,13 +119,13 @@ The project was able to successfully meet its aim of creating reusable prototype -For citations of references, we prefer the use of parenthesis, last name and year. If you use a citation manager, Elsevier – Harvard or American Psychological Association (APA) will work. If you are referencing web pages, software or so, please do so in the same way. Whenever possible, add authors and year. We have included a couple of citations along this document for you to get the idea. Please remember to always add DOI whenever available, if not possible, please provide alternative URLs. You will end up with an alphabetical order list by authors’ last name. - -# Jupyter notebooks, GitHub repositories and data repositories +- For citations of references, we prefer the use of parenthesis, last name and year. +- If you use a citation manager, Elsevier – Harvard or American Psychological Association (APA) will work. If you are referencing web pages, software or so, please do so in the same way. +- Whenever possible, add authors and year. +- We have included a couple of citations along this document for you to get the idea. +- Please remember to always add DOI whenever available, if not possible, please provide alternative URLs. +- You will end up with an alphabetical order list by authors’ last name. -* Please add a list here -* Make sure you let us know which of these correspond to Jupyter notebooks. Although not supported yet, we plan to add features for them -* And remember, software and data need a license for them to be used by others, no license means no clear rules so nobody could legally use a non-licensed research object, whatever that object is # Acknowledgements From d8a7770bcd3826ee79857a4031de891e53c49c64 Mon Sep 17 00:00:00 2001 From: Johan Gustafsson <50811354+supernord@users.noreply.github.com> Date: Wed, 14 Feb 2024 13:22:05 +1030 Subject: [PATCH 09/96] Update docs/publications/BioHackrXiv/paper.md MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Bérénice Batut --- docs/publications/BioHackrXiv/paper.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index ce423dfc..586ec0a9 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -9,9 +9,9 @@ authors: - name: Paul Zierep* orcid: affiliation: 1 - - name: Berenice Batut - orcid: - affiliation: 2 + - name: Bérénice Batut + orcid: 0000-0001-9852-1987 + affiliation: 1, 2 - name: Nicola Soranzo orcid: 0000-0003-3627-5340 affiliation: 3 From ce71ddae181e3dd15f4f0c8df11c7290a6dad512 Mon Sep 17 00:00:00 2001 From: Johan Gustafsson <50811354+supernord@users.noreply.github.com> Date: Wed, 14 Feb 2024 13:22:19 +1030 Subject: [PATCH 10/96] Update docs/publications/BioHackrXiv/paper.md MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Bérénice Batut --- docs/publications/BioHackrXiv/paper.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index 586ec0a9..edfa3056 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -22,9 +22,9 @@ authors: orcid: 0000-0002-2977-5032 affiliation: 5 affiliations: - - name: + - name: Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany index: 1 - - name: + - name: Institut français de Bioinformatique, CNRS UAR 3601, Évry, France & Mésocentre Clermont-Auvergne, Université Clermont Auvergne, Aubiere, France index: 2 - name: Earlham Institute, Norwich Research Park, Norwich, UK index: 3 From 8a4aa30da1638a67c9ac84c7db0f9d902d3d9520 Mon Sep 17 00:00:00 2001 From: Johan Gustafsson <50811354+supernord@users.noreply.github.com> Date: Wed, 14 Feb 2024 13:23:24 +1030 Subject: [PATCH 11/96] Update docs/publications/BioHackrXiv/paper.md MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Bérénice Batut --- docs/publications/BioHackrXiv/paper.md | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index edfa3056..a68a770c 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -66,6 +66,7 @@ The established pipeline and the annotation guidelines can support any research ## Domain-specific interactive tools table Galaxy tool wrapper suites are first parsed from multiple GitHub repositories. In effect, the repositories monitored by the planemo-monitor [@Bray2022.03.13.483965] are scraped using a custom script. The planemo-monitor is part of the Galaxy tool update infrastructure and keeps track of the most up-to-date tool development repositories. + Metadata is extracted from each tool wrapper suite. This includes: wrapper suite ID, scientific category, BioConda dependency, and a bio.tools repository URL. As a tool suite can be composed of multiple individual tools, the tool IDs for each tool are also extracted. The bio.tools reference is used to request annotations via the bio.tools API, including bio.tools description, EDAM function, and EDAM operation[@black2021edam]. The conda package version is retrieved via the BioConda API and compared to the tool wrapper API to determine a tool’s update state (i.e. to update, no update required). The Galaxy API is used to query if each tool is installed on one of the three large Galaxy servers ([usegalaxy.eu](https://usegalaxy.eu/), [usegalaxy.org](https://usegalaxy.org/), [usegalaxy.org.au](https://usegalaxy.org.au/)). Furthermore, the tool usage statistics can be retrieved from an SQL query that needs to be executed by Galaxy admins. The query used in the current implementation shows how many users executed a tool in the last 2 years on the european server ([usegalaxy.eu](https://usegalaxy.eu/)). From 96882185eef1b329dd4ab523e2f34e281a2b8677 Mon Sep 17 00:00:00 2001 From: Johan Gustafsson <50811354+supernord@users.noreply.github.com> Date: Wed, 14 Feb 2024 13:24:09 +1030 Subject: [PATCH 12/96] Update docs/publications/BioHackrXiv/paper.md MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Bérénice Batut --- docs/publications/BioHackrXiv/paper.md | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index a68a770c..172d09cf 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -69,6 +69,7 @@ Galaxy tool wrapper suites are first parsed from multiple GitHub repositories. I Metadata is extracted from each tool wrapper suite. This includes: wrapper suite ID, scientific category, BioConda dependency, and a bio.tools repository URL. As a tool suite can be composed of multiple individual tools, the tool IDs for each tool are also extracted. The bio.tools reference is used to request annotations via the bio.tools API, including bio.tools description, EDAM function, and EDAM operation[@black2021edam]. The conda package version is retrieved via the BioConda API and compared to the tool wrapper API to determine a tool’s update state (i.e. to update, no update required). + The Galaxy API is used to query if each tool is installed on one of the three large Galaxy servers ([usegalaxy.eu](https://usegalaxy.eu/), [usegalaxy.org](https://usegalaxy.org/), [usegalaxy.org.au](https://usegalaxy.org.au/)). Furthermore, the tool usage statistics can be retrieved from an SQL query that needs to be executed by Galaxy admins. The query used in the current implementation shows how many users executed a tool in the last 2 years on the european server ([usegalaxy.eu](https://usegalaxy.eu/)). The output of the pipeline is a table that combines Galaxy wrappers with their metadata. The complete table can then be filtered to include only tools with relevance for specific communities. The initial filtering step is based on the scientific category, which is defined for every Galaxy wrapper. These categories are high-level and cannot distinguish between specific tool functions. However, they allow for the isolation of a subgroup of the initial table for further curation. The filtered table can be manually curated by community curators. The curation step involves annotating which of the extracted tools should be kept in the final table. Curators can use the EDAM annotations and tool descriptions to assist with this curation step. The labels for each tool are stored to reduce replication of effort even further. The practical outcome is that for repeat executions of the workflow, only new tools require curation. The curated tools are transformed into an interactive web table using the data tables framework (**cite**). The table is hosted on GitHub and deployed via GitHub pages for each community. This implementation enables complex queries and filtering without the need for a database backend. The table can be embedded in any website via an iframe: examples include the Galaxy community Hub page for microGalaxy (**cite**) or a specific Galaxy subdomain (**cite**). Furthermore, a word cloud based on the usage statistics of the tools is created. From bdcc8bc6b2404eefbd1c46de0187c2a0ff3c4cf9 Mon Sep 17 00:00:00 2001 From: Johan Gustafsson <50811354+supernord@users.noreply.github.com> Date: Wed, 14 Feb 2024 13:24:30 +1030 Subject: [PATCH 13/96] Update docs/publications/BioHackrXiv/paper.md MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Bérénice Batut --- docs/publications/BioHackrXiv/paper.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index 172d09cf..a11efac2 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -71,7 +71,8 @@ Metadata is extracted from each tool wrapper suite. This includes: wrapper suite The bio.tools reference is used to request annotations via the bio.tools API, including bio.tools description, EDAM function, and EDAM operation[@black2021edam]. The conda package version is retrieved via the BioConda API and compared to the tool wrapper API to determine a tool’s update state (i.e. to update, no update required). The Galaxy API is used to query if each tool is installed on one of the three large Galaxy servers ([usegalaxy.eu](https://usegalaxy.eu/), [usegalaxy.org](https://usegalaxy.org/), [usegalaxy.org.au](https://usegalaxy.org.au/)). Furthermore, the tool usage statistics can be retrieved from an SQL query that needs to be executed by Galaxy admins. The query used in the current implementation shows how many users executed a tool in the last 2 years on the european server ([usegalaxy.eu](https://usegalaxy.eu/)). -The output of the pipeline is a table that combines Galaxy wrappers with their metadata. The complete table can then be filtered to include only tools with relevance for specific communities. The initial filtering step is based on the scientific category, which is defined for every Galaxy wrapper. These categories are high-level and cannot distinguish between specific tool functions. However, they allow for the isolation of a subgroup of the initial table for further curation. The filtered table can be manually curated by community curators. The curation step involves annotating which of the extracted tools should be kept in the final table. Curators can use the EDAM annotations and tool descriptions to assist with this curation step. The labels for each tool are stored to reduce replication of effort even further. The practical outcome is that for repeat executions of the workflow, only new tools require curation. + +The output of the pipeline is a table that combines Galaxy wrappers with their metadata. The complete table can then be filtered to include only tools with relevance for specific communities. The initial filtering step is based on the scientific category, which is defined for every Galaxy wrapper. These categories are high-level and cannot distinguish between specific tool functions. However, they allow for the isolation of a subgroup of the initial table for further curation. The filtered table can be manually curated by community curators. The curation step involves annotating which of the extracted tools should be kept in the final table. Curators can use the EDAM annotations and tool descriptions to assist with this curation step. The labels for each tool are stored to reduce the replication of effort even further. The practical outcome is that for repeat executions of the workflow, only new tools require curation. The curated tools are transformed into an interactive web table using the data tables framework (**cite**). The table is hosted on GitHub and deployed via GitHub pages for each community. This implementation enables complex queries and filtering without the need for a database backend. The table can be embedded in any website via an iframe: examples include the Galaxy community Hub page for microGalaxy (**cite**) or a specific Galaxy subdomain (**cite**). Furthermore, a word cloud based on the usage statistics of the tools is created. The workflow is scheduled via GitHub actions to run on a weekly basis, providing an up-to-date table for each community. The usage of an iframe enables updates for the table to propagate automatically to any website where it is deployed. Any Galaxy community can use the pipeline by adding a folder in the [GitHub repository](https://github.com/galaxyproject/galaxy_tool_extractor/data/communities). To initialize the pipeline for a new community you need to add a list of categories to a file called categories. Additionally tools that should be excluded or included after filtering can be added to respective files as well. A working example of the community configuration files can be found in the folder for the microgalaxy community. From 51612e3abc2c7bae174c03ade780cb24c80f7d0e Mon Sep 17 00:00:00 2001 From: Johan Gustafsson <50811354+supernord@users.noreply.github.com> Date: Wed, 14 Feb 2024 13:24:39 +1030 Subject: [PATCH 14/96] Update docs/publications/BioHackrXiv/paper.md MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Bérénice Batut --- docs/publications/BioHackrXiv/paper.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index a11efac2..a48ba53f 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -90,7 +90,9 @@ There are then two curation paths to choose from, depending on if a bio.tools id In the case where no bio.tools identifier exists in the Galaxy *.xml wrapper, the development repository needs to be forked and a new branch created. A new xref snippet can then be added, and a pull request (PR) generated against the original repository. + Figure \ref{annotation_workflow} shows a step-by-step breakdown of the above process. + ![Step-by-step workflow for systematically improving metadata annotations across bio.tools registry entries and Galaxy tool wrappers. After selecting a Galaxy tool and checking for the presence of a bio.tools ID in its XML file, a curator needs to review bio.tools, create a new bio.tools entry (if needed), and then ensure that both this entry and the Galaxy tool XML file are up-to-date. Updating bio.tools makes use of the registry wizard, and updating a Galaxy tool wrapper to include a bio.tools xref snippet requires a pull request against the development repository. \label{annotation_workflow}](./figures/________.png) From 3e18aa05cac52b0881e2030f2ebe531101b07362 Mon Sep 17 00:00:00 2001 From: Johan Gustafsson <50811354+supernord@users.noreply.github.com> Date: Wed, 14 Feb 2024 13:24:49 +1030 Subject: [PATCH 15/96] Update docs/publications/BioHackrXiv/paper.md MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Bérénice Batut --- docs/publications/BioHackrXiv/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index a48ba53f..d22b70c0 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -103,7 +103,7 @@ There were multiple concrete outcomes from this BioHackathon project, including ## Prototype interactive table for Galaxy communities -The described workflow for the Galaxy tool metadata extractor (see Figure \ref{metadata_extractor_pipeline}) was successfully implemented (cite GitHub) and could collect 1,294 Galaxy tools suits (cite output). Of those tools suits, only 267 had a bio.tools identifier, which highlights the importance of performing the annotation process in parallel and complementing the tools with additional metadata. An example view of the created interactive table is shown in Figure \ref{web_table}. The filtered table for the microGalaxy community is embedded in the microGalaxy Galaxy Hub (cite) page as well as the dedicated microGalaxy subdomain (cite). +The described workflow for the Galaxy tool metadata extractor (see Figure \ref{metadata_extractor_pipeline}) was successfully implemented (cite GitHub) and could collect 1,294 Galaxy tool suites (cite output). Of those tool suites, only 267 had a bio.tools identifier, which highlights the importance of performing the annotation process in parallel and complementing the tools with additional metadata. An example view of the created interactive table is shown in Figure \ref{web_table}. The filtered table for the microGalaxy community is embedded in the microGalaxy Galaxy Hub (cite) page as well as the dedicated microGalaxy subdomain (cite). ![Screenshot of the interactive web table. The table provides comprehensive metadata for all Galaxy wrappers of a specific community and allows for custom searches based on logic filters over all columns. In the shown example, the user queries for all up-to-date tools that are annotated with the EDAM Operation assembly. \label{web_table}](./figures/________.png) From 23ea0ae01f15db7eaf8772fea390c33c804daca0 Mon Sep 17 00:00:00 2001 From: Johan Gustafsson <50811354+supernord@users.noreply.github.com> Date: Wed, 14 Feb 2024 13:24:58 +1030 Subject: [PATCH 16/96] Update docs/publications/BioHackrXiv/paper.md MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Bérénice Batut --- docs/publications/BioHackrXiv/paper.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index d22b70c0..7ac50e3f 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -109,7 +109,8 @@ The described workflow for the Galaxy tool metadata extractor (see Figure \ref{m ## bio.tools and EDAM annotations for microbiome community -During the week of the Biohackathon the microGalaxy community executed the annotation workflow as described in the Methods Section (see also Figure \ref{annotation_workflow}). The initial filtered tool table of the microGalaxy included 218 tool suites, of which 61 had corresponding bio.tools identifiers. The process of the work was tracked using a GitHub project board. After the annotation process, the number of tools with bio.tools annotations was increased to 107. The added annotations for each respective bio.tools entry was also collectively reviewed by the team. A rerun of the Galaxy tool metadata extractor pipeline collected the additional information, and the metadata is now included in the interactive microGalaxy tool table. + +During the week of the Biohackathon the microGalaxy community executed the annotation workflow as described in the Methods Section (see also Figure \ref{annotation_workflow}). The initial filtered tool table of the microGalaxy included 218 tool suites, of which 61 had corresponding bio.tools identifiers. The process of the work was tracked using a GitHub project board. After the annotation process, the number of tools with bio.tools annotations was increased to 107. The added annotations for each respective bio.tools entry were also collectively reviewed by the team. A rerun of the Galaxy tool metadata extractor pipeline collected the additional information, and the metadata is now included in the interactive microGalaxy tool table. ## Training materials and updates to standards From fc13cdfe1632ee0bf61c9980e0d3bdf02bbac78b Mon Sep 17 00:00:00 2001 From: Johan Gustafsson <50811354+supernord@users.noreply.github.com> Date: Wed, 14 Feb 2024 13:25:13 +1030 Subject: [PATCH 17/96] Update docs/publications/BioHackrXiv/paper.md MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Bérénice Batut --- docs/publications/BioHackrXiv/paper.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index 7ac50e3f..83b26479 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -114,7 +114,8 @@ During the week of the Biohackathon the microGalaxy community executed the annot ## Training materials and updates to standards -In order to provide the Galaxy research communities with simple and straightforward how-to to annotate their respective tool stacks, the described annotation workflow is currently being transformed into a Galaxy Training Network (GTN) tutorial. The guidelines created were also used to update the [best practices of the IUC repository](https://galaxy-iuc-standards.readthedocs.io/en/latest/best_practices/tool_xml.html). + +To provide the Galaxy research communities with simple and straightforward how-to to annotate their respective tool stacks, the described annotation workflow is currently being transformed into a Galaxy Training Network (GTN) tutorial. The guidelines created were also used to update the [best practices of the IUC repository](https://galaxy-iuc-standards.readthedocs.io/en/latest/best_practices/tool_xml.html). # Conclusion and outlook From d67f0bf1757ae6b5b5ae9cdeee8a7764e44284d0 Mon Sep 17 00:00:00 2001 From: Johan Gustafsson <50811354+supernord@users.noreply.github.com> Date: Wed, 14 Feb 2024 13:25:28 +1030 Subject: [PATCH 18/96] Update docs/publications/BioHackrXiv/paper.md MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Bérénice Batut --- docs/publications/BioHackrXiv/paper.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/docs/publications/BioHackrXiv/paper.md b/docs/publications/BioHackrXiv/paper.md index 83b26479..1723ffc8 100644 --- a/docs/publications/BioHackrXiv/paper.md +++ b/docs/publications/BioHackrXiv/paper.md @@ -5,6 +5,10 @@ tags: - Findability - Galaxy - Community specific + - Tools + - EDAM + - bio.tools + - Metadata authors: - name: Paul Zierep* orcid: From afea4c98a8d7cbd46d34fd3d53bc868a2e439d5b Mon Sep 17 00:00:00 2001 From: Johan Gustafsson Date: Wed, 14 Feb 2024 13:37:22 +1030 Subject: [PATCH 19/96] Add figures --- docs/publications/BioHackrXiv/annotation.png | Bin 0 -> 237016 bytes docs/publications/BioHackrXiv/paper.md | 4 ++-- docs/publications/BioHackrXiv/xref.png | Bin 0 -> 314910 bytes 3 files changed, 2 insertions(+), 2 deletions(-) create mode 100644 docs/publications/BioHackrXiv/annotation.png create mode 100644 docs/publications/BioHackrXiv/xref.png diff --git a/docs/publications/BioHackrXiv/annotation.png b/docs/publications/BioHackrXiv/annotation.png new file mode 100644 index 0000000000000000000000000000000000000000..6664d268a3e0bcd3ce92a946c3ee8951ffe056ec GIT binary patch literal 237016 zcmeFZbyU<{`#uVaN=SzS64KI*)X?3HQqm359n#$$A{`1yOG|fyID|+`ch}kD^S(aM zI_G!R_x=6WIsd(^HO|MG`Rv(o@9Vy=>%RAdD#}ZsA`>9P!NH+QNs21N!6Amh!66VJ zJ_N5&S;O1G!NF^ri-;&niHMLY+S{6#TN%T_(Zm|Qd1D|&Pt&Wf|K?5a5Zw!8dl%)9 zkO<{BK5bt+zxI4>BON4tpQ5e(^C`y9`>O45xk_zymX9MyFDn^)KLxzyU;pr+mM|AG z+^XtSAP1+ykNi_wib4M2xR0+UUHylmfOqed?)Re6Fuj1Qp!2ngCHs);yG@M2OVq9l zXFx6VUF)lbuwTZzZEV3>L3?on*4GlKMCRe_`4ud5&6s1>?i=6- zy?H3{P>&S9|7Xunw8w`# zusIyUzdj=mo?(A6-~qemujl)5L2!@2|FFQr^~1e?e;P6D!~K6>BM^Z1;Dl5}q@=*J zilM!+v5kY7tz-3^5IT4P>8<1|2RJx9O4tKlN||CGwEx{)Rnt*ZPL{{e)|ye@$kxD^ z(bf7btQ|N$R~~R_ZS1H|>S}Fes7dA#)ds8MBZfzLv zRtE411_w7AM}1cY8wc{g8u@oSqQ(w}_U3OL&24Q+VeRT0*g84#laax`=+EC@{WNwp z|NEP49R4*dFhC~QJ4`H$%uIjU2DkFTUgc3VcQv+pC2DRB<_vrXgoT-dneX=v|Btu+ z{>p#cs`>Y=tSm1%|9R^_-ul1as^(y9FJfyAzSI%&_k#WF=6}BVuN(Q8U}OKsT>LfB zzh4D24MFB(`m<^fEG$oJTTt_S%2@ampby}if`*^<9+kA?()(5tKHd|g_|<0yA%ovL_xTF z7`|`_q;T;6)8)Ib*fj4HDfT%{{Qko`K$Bmw1Zmoz!2hS;0gt$X1Rp@=W?)u;^gnj! z&j&EV_KE(pG5o&8O&Bg)^8M2^bK(DZ?4VDckN$%>`d60(-(v{U#8C&Cr2XeJ1(%Ju z@MlE-^H;@CBVdHBgl4Bw{U>YpSHoZ_T>kSR|92_=L#zGoQv7Ei^50$YKZERl0qVa1 zCHQp&!TaLEQ~*7zLImy}CIanVt(GWSp%AHWIhr4Csy_+hPm!B9`JFu>=yDnO9HcRi z;XTb*C!6#hk!*SqvIrxd2g02pwQ7dh75Kvm$2uzJq5kdM-$h`(8Kcg1HGg*R74_G4 znQyVC`68Z9>dX^J2nZwugG}%c_7rDh^&jNE=qK;x##zWb&3I_WA0m)`K=`7t&)-XZ z4^ix}Z)Onp4?LbHz=cB~9M3v}1Rvj{Z|a0wKC<$x8A0vc_Y#34*(6k^^LG|MTPX>HleQ?pwaVw?Z=#Apjl-ENvD7GbPyZ#^eAEj{vMP9^pw-w zw4BM)=~Qz<#T)x;@WYAQ^U*gmiLczE;UJS9oKig@``H^GBndHmeX)K*+RjL`5J_?R zs4dwv{iOT>nN`78ENhUh;1QxxJRAxW zG%vHcWq%54D5r2C2S-96d$la$Z?0jo%75=%aSuvCMBW};;7?`^a8ug%3Sq(Dlgw9< zBJ0zT_MbL=6_7svT2|>`u|n)51%rRg3>oRxxSI2QyugL9pWVWuCVamum?|K=9YZn= z4#IBk_`WOz{iNFM=`#dRG2g3z^1-e*DiokuF<;f-zXQBpK6pGY){zuq(il0gRz~s8 zrjC~gz{@nv;u0+=jRyyVDKzo&-n=Tb{y`rdM;pm4ZiGFMMA|PNyA`779lmicRrdo z=GH(4nVeYDe~Yn?3mR=v{eiI*HHg!sQ)$8|03#t5%s@_`d`=of9U!PlTY?B$&JT%EoFMY>v(__7_Ce5eMJgCNnA)h?LKnED zIoX_&DQc5Wr0qL29>6Mzw^)=n&0?4+R7lo7&fNTdqfJ7xX}Z-#%nM=XBrFpo%>?d$ zBX1+Kc0c<^#RKwpz6(fiv-TSw;QNpPQG`M`yz(Ei3-|M{ISTThCte`1iu(p8M`RC~ zcbsn?FWy;fD4Rno^Q}MI%r}gGdR1jWIDM$o==h>mn+L^_Z;L*a#W2YFa6QXg+H|5? 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