Workflows

What is a Workflow?
793 Workflows visible to you, out of a total of 868
Stable

MGnify genomes catalogue pipeline

MGnify A pipeline to perform taxonomic and functional annotation and to generate a catalogue from a set of isolate and/or metagenome-assembled genomes (MAGs) using the workflow described in the following publication:

Gurbich TA, Almeida A, Beracochea M, Burdett T, Burgin J, Cochrane G, Raj S, Richardson L, Rogers AB, Sakharova E, Salazar GA and Finn RD. (2023) [MGnify Genomes: A Resource for Biome-specific Microbial Genome ...

EnrichDO

EnrichDO is a double weighted iterative model by integrating the DO graph topology on a global scale. It was based on the latest annotations of the human genome with DO terms, and double weighted the annotated protein-coding genes. On one hand, to reinforce the saliency of direct gene-DO annotations, different initial weights were assigned to directly annotated genes and indirectly annotated genes, respectively. On the other hand, to detect locally most significant node between ...

Type: R markdown

Creator: Liang Cheng

Submitter: Liang Cheng

DOI: 10.48546/workflowhub.workflow.1221.1

This workflow will perform taxonomic and functional annotations using Unipept and statistical analysis using MSstatsTMT.

Type: Galaxy

Creator: GalaxyP

Submitter: WorkflowHub Bot

In proteomics research, verifying detected peptides is essential for ensuring data accuracy and biological relevance. This tutorial continues from the clinical metaproteomics discovery workflow, focusing on verifying identified microbial peptides using the PepQuery tool.

Type: Galaxy

Creator: Pratik Jagtap

Submitter: WorkflowHub Bot

From metagenomes to peptides

Type: Nextflow

Creators: Sabrina Krakau, Leon Kuchenbecker and Till Englert

Submitter: WorkflowHub Bot

The workflow begins with the Database Generation process. The Galaxy-P team has developed a workflow that collects protein sequences from known disease-causing microorganisms to build a comprehensive database. This extensive database is then refined into a smaller, more relevant dataset using the Metanovo tool.

Type: Galaxy

Creator: Subina Mehta

Submitter: WorkflowHub Bot

No description specified

Type: COMPSs

Creator: Daniele Lezzi

Submitter: Daniele Lezzi

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 is part of a series of workflows to annotate a genome, tagged with TSI-annotation. These workflows are based on command-line code by Luke Silver, converted into Galaxy Australia workflows.

The workflows can be run in this order:

  • Repeat masking
  • RNAseq QC and read trimming
  • Find transcripts
  • Combine transcripts
  • Extract transcripts
  • Convert formats
  • Fgenesh annotation

Inputs required: assembled-genome.fasta, hard-repeat-masked-genome.fasta, and (because this workflow maps known mRNA ...

Type: Galaxy

Creator: Luke Silver

Submitter: Anna Syme

DOI: 10.48546/workflowhub.workflow.881.5

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