Workflows

What is a Workflow?
9 Workflows visible to you, out of a total of 9
Stable

metaGOflow: A workflow for marine Genomic Observatories' data analysis

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An EOSC-Life project

The workflows developed in the framework of this project are based on pipeline-v5 of the MGnify resource.

This branch is a child of the pipeline_5.1 branch that contains all CWL descriptions of the MGnify ...

Type: Common Workflow Language

Creators: Haris Zafeiropoulos, Martin Beracochea

Submitter: Haris Zafeiropoulos

DOI: 10.48546/workflowhub.workflow.384.3

Stable

MGnify genomes analysis 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 ...

Type: Nextflow

Creators: None

Submitter: Martin Beracochea

Work-in-progress

MoMofy

Module for integrative Mobilome prediction

Bacteria can acquire genetic material through horizontal gene transfer, allowing them to rapidly adapt to changing environmental conditions. These mobile genetic elements can be classified into three main categories: plasmids, phages, and integrons. Autonomous elements are those capable of excising themselves from the chromosome, reintegrating elsewhere, and potentially modifying the host's physiology. Small integrative elements like insertion ...

Type: Nextflow

Creators: Alejandra Escobar, Martin Beracochea

Submitter: Alejandra Escobar

Stable

The containerised pipeline for profiling shotgun metagenomic data is derived from the MGnify pipeline raw-reads analyses, a well-established resource used for analyzing microbiome data. Key components:

  • Quality control and decontamination
  • rRNA and ncRNA detection using Rfam database
  • Taxonomic classification of SSU and LSU regions
  • Abundance analysis with mOTUs

Type: Nextflow

Creators: Ekaterina Sakharova, Martin Beracochea

Submitter: Ekaterina Sakharova

Stable

MGnify (http://www.ebi.ac.uk/metagenomics) provides a free to use platform for the assembly, analysis and archiving of microbiome data derived from sequencing microbial populations that are present in particular environments. Over the past 2 years, MGnify (formerly EBI Metagenomics) has more than doubled the number of publicly available analysed datasets held within the resource. Recently, an updated approach to data analysis has been unveiled (version 5.0), replacing the previous single pipeline ...

Type: Common Workflow Language

Creators: Ekaterina Sakharova, Varsha Kale, Martin Beracochea, Alex L Mitchell, Alexandre Almeida, Martin Beracochea, Miguel Boland, Josephine Burgin, Guy Cochrane, Michael R Crusoe, Varsha Kale, Simon C Potter, Lorna J Richardson, Ekaterina Sakharova, Maxim Scheremetjew, Anton Korobeynikov, Alex Shlemov, Olga Kunyavskaya, Alla Lapidus, Robert D Finn

Submitter: Martin Beracochea

DOI: 10.48546/workflowhub.workflow.362.1

Stable

MGnify (http://www.ebi.ac.uk/metagenomics) provides a free to use platform for the assembly, analysis and archiving of microbiome data derived from sequencing microbial populations that are present in particular environments. Over the past 2 years, MGnify (formerly EBI Metagenomics) has more than doubled the number of publicly available analysed datasets held within the resource. Recently, an updated approach to data analysis has been unveiled (version 5.0), replacing the previous single pipeline ...

Type: Common Workflow Language

Creator: Alex L Mitchell, Alexandre Almeida, Martin Beracochea, Miguel Boland, Josephine Burgin, Guy Cochrane, Michael R Crusoe, Varsha Kale, Simon C Potter, Lorna J Richardson, Ekaterina Sakharova, Maxim Scheremetjew, Anton Korobeynikov, Alex Shlemov, Olga Kunyavskaya, Alla Lapidus, Robert D Finn

Submitter: Martin Beracochea

Stable

MGnify (http://www.ebi.ac.uk/metagenomics) provides a free to use platform for the assembly, analysis and archiving of microbiome data derived from sequencing microbial populations that are present in particular environments. Over the past 2 years, MGnify (formerly EBI Metagenomics) has more than doubled the number of publicly available analysed datasets held within the resource. Recently, an updated approach to data analysis has been unveiled (version 5.0), replacing the previous single pipeline ...

Type: Common Workflow Language

Creator: Alex L Mitchell, Alexandre Almeida, Martin Beracochea, Miguel Boland, Josephine Burgin, Guy Cochrane, Michael R Crusoe, Varsha Kale, Simon C Potter, Lorna J Richardson, Ekaterina Sakharova, Maxim Scheremetjew, Anton Korobeynikov, Alex Shlemov, Olga Kunyavskaya, Alla Lapidus, Robert D Finn

Submitter: Martin Beracochea

Stable

VIRify

VIRify is a recently developed pipeline for the detection, annotation, and taxonomic classification of viral contigs in metagenomic and metatranscriptomic assemblies. The pipeline is part of the repertoire of analysis services offered by MGnify. VIRify’s taxonomic classification relies on the detection of taxon-specific profile hidden Markov models (HMMs), built upon a set of 22,014 orthologous protein domains and referred to as ViPhOGs. VIRify was implemented in CWL. What do I need? The ...

Type: Nextflow

Creators: Martin Beracochea, Martin Hölzer, Alexandre Almeida, Guillermo Rangel-Pineros and Ekaterina Sakharova

Submitter: Laura Rodriguez-Navas

Stable

VIRify

VIRify is a recently developed pipeline for the detection, annotation, and taxonomic classification of viral contigs in metagenomic and metatranscriptomic assemblies. The pipeline is part of the repertoire of analysis services offered by MGnify. VIRify’s taxonomic classification relies on the detection of taxon-specific profile hidden Markov models (HMMs), built upon a set of 22,014 orthologous protein domains and referred to as ViPhOGs. VIRify was implemented in CWL. What do I need? The ...

Type: Common Workflow Language

Creators: Martin Beracochea, Martin Hölzer, Alexandre Almeida, Guillermo Rangel-Pineros and Ekaterina Sakharova

Submitter: Laura Rodriguez-Navas

DOI: 10.48546/workflowhub.workflow.26.1

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