Workflows

Second part of the ecoregionalization

This workflow allows you to create an ecoregionalization map from occurrences and environmental data using a boosted regression trees model for predictions.

The workflow is intended for processing occurrence data, which should include latitude, longitude and species presence or absence. You can use example test data available with the workflow, highlighting a use case centered on the Dumont d'Urville sea region and benthic invertebrates. The primary goal of ...

Part 1 of ecoregionalization workflow

This workflow allows you to create an ecoregionalization map from occurrences and environmental data using a boosted regression trees model for predictions.

The workflow is intended for processing occurrence data, which should include latitude, longitude and species presence or absence. You can use example test data available with the workflow, highlighting a use case centered on the Dumont d'Urville sea region and benthic invertebrates. The primary goal of ...

This workflow uses the decoupler tool in Galaxy to generate pseudobulk counts from an annotated AnnData file obtained from scRNA-seq analysis. Following the pseudobulk step, differential expression genes (DEG) are calculated using the edgeR tool. The workflow also includes data sanitation steps to ensure smooth operation of edgeR and minimizing potential issues. Additionally, a Volcano plot tool is used to visualize the results after the DEG analysis.

This workflow can only work on an experimental setup with exactly 2 conditions. It takes two collections of count tables as input and performs differential expression analysis. Additionally it filters for DE genes based on adjusted p-value and log2 fold changes thresholds. It also generates informative plots.

This workflow is used for GO and KEGG enrichment analysis using GOseq tools.

Workflow for variant analysis against a reference genome in GenBank format

Subset data on the Mediterreanean see and extract and visualise the Phosphate variable

Clinical Metaproteomics 4: Quantitation

COVID-19: variation analysis on ARTIC PE data

The workflow for Illumina-sequenced ampliconic data builds on the RNASeq workflow for paired-end data using the same steps for mapping and variant calling, but adds extra logic for trimming amplicon primer sequences off reads with the ivar package. In addition, this workflow uses ivar also to identify amplicons affected by primer-binding site mutations and, if possible, excludes reads derived from such ...

Assembly of bacterial paired-end short read data with generation of quality metrics and reports