Galaxy

This team and associated Galaxy workflows are maintained by the European Galaxy Team.

The Galaxy Training Network (GTN) is a collection of hands-on tutorials that are designed to be interactive and are built around Galaxy.

These tutorials can be used for learning and teaching how to use Galaxy for general data analysis, as well as a wide array of hands-on tutorials covering specific domains such as assembly, RNA-Seq analysis, deep learning, climate analysis, and more!

The Intergalactic Workflow Commission releases vetted analysis pipelines for the Galaxy platform.

You can contribute too!

Reference data to beused with https://workflowhub.eu/workflows/1260

Generate a genome assembly based on PacBio HiFi reads. Part of the VGP suite, it needs to be run after the VGP1 k-mer profiling workflow. The assembly contigs are built using HiFiasm, and the workflow generates assembly statistics, BUSCO reports, Merqury plots, and the contigs in fasta and GFA formats.

Evaluation of Pacbio Hifi Reads and genome profiling. Create Meryl Database used for the estimation of assembly parameters and quality control with Merqury. Part of the VGP pipeline.

Purge contigs marked as duplicates by purge_dups in a single haplotype (could be haplotypic duplication or overlap duplication). If you think the purged contigs might belong to the other haplotype, use the workflow VGP6 instead. This workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5).

Purge contigs marked as duplicates by purge_dups (could be haplotypic duplication or overlap duplication). The contigs are purged from the first assembly (hap1, pri...), added to the second assembly (hp2, alt... ), then the 2nd assembly is purged as well. If you think only one of the assemblies needs purging, use the VGP6b workflow. This workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5).

This workflow applies text mining to a museum collection in tabular format to extract from which year most objects derive and what they are. The first steps are filtering and data cleaning to put the data in correct format. Datamash allows showing how many documents from what year the museum catalogue contains. The output is a chronological table which is visualised as a bar chart. From that, the year where most items derived from is extracted. The next step filters items only from that year. The ...

This workflow performs quality and contamination control analysis on assembled contigs to assess bacterial genome quality and taxonomic assignment

Short paired-end read analysis to provide quality analysis, read cleaning and taxonomy assignation directly from raw reads

This workflow processes the CMO fastqs with CITE-seq-Count and include the translation step required for cellPlex processing. In parallel it processes the Gene Expresion fastqs with STARsolo, filter cells with DropletUtils and reformat all outputs to be easily used by the function 'Read10X' from Seurat.

Complete ChIP-seq analysis for single-end sequencing data. Processes raw FASTQ files through adapter removal (cutadapt), alignment to reference genome (Bowtie2), and quality filtering (MAPQ >= 30). Peak calling with MACS2 uses either a fixed extension parameter or built-in model to identify protein-DNA binding sites. Generates alignment files, peak calls, and quality metrics for downstream analysis.

Complete ChIP-seq analysis for paired-end sequencing data. Processes raw FASTQ files through adapter removal (cutadapt), alignment to reference genome (Bowtie2), and stringent quality filtering (MAPQ >= 30, concordant pairs only). Peak calling with MACS2 optimized for paired-end reads identifies protein-DNA binding sites. Generates alignment files, peak calls, and quality metrics for downstream analysis.

Find and annotate variants in ampliconic SARS-CoV-2 Illumina sequencing data and classify samples with pangolin and nextclade

COVID-19: variation analysis on WGS PE data

This workflows performs paired end read mapping with bwa-mem followed by sensitive variant calling across a wide range of AFs with lofreq and variant annotation with snpEff 4.5covid19.

Variant calling and consensus sequence generation for batches of Illumina PE sequenced viruses with uncomplicated and stable genome structure (like e.g. Morbilliviruses).

COVID-19: variation analysis on ARTIC ONT data

This workflow for ONT-sequenced ARTIC data is modeled after the alignment/variant-calling steps of the ARTIC pipeline. It performs, essentially, the same steps as that pipeline’s minion command, i.e. read mapping with minimap2 and variant calling with medaka. Like the Illumina ARTIC workflow it uses ivar for primer trimming. Since ONT-sequenced reads have a much ...

This workflow takes as input a SRA_manifest from SRA Run Selector and will generate one fastq file or fastq pair of file for each experiment (concatenated multiple runs if necessary). Output will be relabelled to match the column specified by the user.

This workflow performs subtyping and consensus sequence generation for batches of Illumina PE sequenced Influenza A isolates.

A workflow for the analysis of pox virus genomes sequenced as half-genomes (for ITR resolution) in a tiled-amplicon approach

This workflows performs single end read mapping with bowtie2 followed by sensitive variant calling across a wide range of AFs with lofreq

Build a consensus sequence from FILTER PASS variants with intrasample allele-frequency above a configurable consensus threshold. Hard-mask regions with low coverage (but not consensus variants within them) and ambiguous sites.

This workflow takes a VCF dataset of variants produced by any of the *-variant-calling workflows in https://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling and generates tabular lists of variants by Samples and by Variant, and an overview plot of variants and their allele-frequencies.