Workflows

Workflow for processing amplicon pool sequencing data without reference sequence.

This workflow allows you to reconstruct a sequence from an amplicon pool without a reference sequence. To run this workflow, you need the reads from the pool library you want to analyse in FASTQ format, separated into two files: forward and reverse. You will also need the primers used during sequencing. This workflow creates one or two contigs (depending on whether your primers were used once or twice) and a metadata ...

Workflow for processing amplicon pool sequencing data with reference.

This workflow allows you to reconstruct a sequence from an amplicon pool using a reference sequence. To run this workflow, you need the reads from the pool library you want to analyse in FASTQ format, separated into two files: forward and reverse. You will also need your reference sequence in FASTA format. This workflow creates a consensus sequence and a metadata file containing the length of the consensus sequence, the number ...

Reference-based RNA-Seq data analysis

Associated Tutorial

This workflows is part of the tutorial Reference-based RNA-Seq data analysis, available in the GTN

Features

• Includes Galaxy Workflow Tests
• Includes a [Galaxy Workflow ...

Reference-based RNA-Seq data analysis

Associated Tutorial

This workflows is part of the tutorial Reference-based RNA-Seq data analysis, available in the GTN

Features

• Includes Galaxy Workflow Tests
• Includes a [Galaxy Workflow ...

This workflow performs genome annotation using Braker3 and evaluates the quality of the annotation with BUSCO and genome annotation statistics.

Binning workflows that uses abundance information and performs binning of metagenomic contigs using 4 different binners as well as bin refinement.

Associated Tutorial

This workflows is part of the tutorial Binning of metagenomic sequencing data, available in the GTN

Features

• Includes [Galaxy Workflow ...

This workflow takes Nanopore fastq(.gz) files and runs Minimap2 to map the reads against a reference genome (human, by default). It filters the output to keep only the unmapped reads and generates mapping statistics that are aggregated into a MultiQC report.

This workflow takes paired-end Illumina fastq(.gz) files and runs Bowtie to map the reads against a reference genome (human, by default) and keep only the reads that do not align. MultiQC is used to aggregate the mapping reports.

This workflow performs quality control and trimming on paired-end Illumina fastq(.gz) files using fastp and aggregates the quality control reports with MultiQC

Associated Tutorial

This workflows is part of the tutorial Visualization of RNA-Seq results with heatmap2, available in the GTN

Features

• Includes Galaxy Workflow Tests
• Includes a [Galaxy Workflow ...