Workflows

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738 Workflows visible to you, out of a total of 793
1: Plant virus detection with kraken2 (SE)
Stable

Metagenomic dataset taxonomic classification using kraken2

Type: Galaxy

Creators: None

Submitter: johan Rollin

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1: Plant virus detection with kraken2 (PE)
Stable

Metagenomic dataset taxonomic classification using kraken2

Type: Galaxy

Creators: None

Submitter: johan Rollin

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Spliced RNAseq workflow
Work-in-progress

Workflow for Spliced RNAseq data Steps:

  • workflow_quality.cwl:
  • FastQC (Read Quality Control)
  • fastp (Read Trimming)
  • STAR (Read mapping)
  • featurecounts (transcript read counts)
  • kallisto (transcript [pseudo]counts)

Type: Common Workflow Language

Creators: Bart Nijsse, Jasper Koehorst

Submitter: Bart Nijsse

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NonSpliced RNAseq workflow
Work-in-progress

Workflow for NonSpliced RNAseq data with multiple aligners.

Steps:

  • workflow_quality.cwl:
  • FastQC (control)
  • fastp (trimming)
  • bowtie2 (read mapping)
  • sam_to_sorted-bam
  • featurecounts (transcript read counts)
  • kallisto (transcript [pseudo]counts)

Type: Common Workflow Language

Creators: Bart Nijsse, Jasper Koehorst

Submitter: Bart Nijsse

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NGTax
Stable

Amplicon analysis workflow using NG-Tax

Steps:

  • Quality control on the reads
  • Execute NGTax for ASV detection and classification

For more information about NG-Tax 2.0 have a look at https://doi.org/10.3389/fgene.2019.01366

Type: Common Workflow Language

Creators: Jasper Koehorst, Bart Nijsse, Jesse van Dam, Peter Schaap,

Submitter: Jasper Koehorst

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SPARQL query (in a file) on graph database
Work-in-progress

A workflow querying on an endpoint of a graph database by a file containing a SPARQL query.

Type: Common Workflow Language

Creators: None

Submitter: Qinqin Long

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Compute daily and monthly mean from meteorological station measurements
Stable

This workflow is used to process timeseries from meteorological stations in Finland but can be applied to any timeseries according it follows the same format.

Take a temperature timeseries from any meteorological station. Input format is csv and it must be standardized with 6 columns:

  1. Year (ex: 2021)
  2. month (ex: 1)
  3. day (ex: 15)
  4. Time (ex: 16:56)
  5. Time zone (such as UTC)
  6. Air temperature (degC)

Type: Galaxy

Creators: None

Submitter: Anne Fouilloux

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VariantCaller_GATK3.6
Stable

Rare disease researchers workflow is that they submit their raw data (fastq), run the mapping and variant calling RD-Connect pipeline and obtain unannotated gvcf files to further submit to the RD-Connect GPAP or analyse on their own.

This demonstrator focuses on the variant calling pipeline. The raw genomic data is processed using the RD-Connect pipeline (Laurie et al., 2016) running on the standards (GA4GH) compliant, interoperable container ...

Type: Nextflow

Creator: José Mª Fernández

Submitters: Laura Rodriguez-Navas, José Mª Fernández

DOI: 10.48546/workflowhub.workflow.106.3

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Molecular Dynamics Simulation
Work-in-progress

CWL version of the md_list.py workflow for HPC. This performs a system setup and runs a molecular dynamics simulation on the structure passed to this workflow. This workflow uses the md_gather.cwl sub-workflow to gather the outputs together to return these. To work with more than one structure this workflow can be called from either the md_launch.cwl workflow, or the md_launch_mutate.cwl workflow. These use scatter for parallelising the workflow. md_launch.cwl operates on a list of individual ...

Type: Common Workflow Language

Creators: None

Submitter: Douglas Lowe

DOI: 10.48546/workflowhub.workflow.121.1

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COSIFER
Stable

COnSensus Interaction Network InFErence Service

Inference framework for reconstructing networks using a consensus approach between multiple methods and data sources.

alt text

Reference

[Manica, Matteo, Charlotte, Bunne, Roland, Mathis, Joris, Cadow, Mehmet Eren, Ahsen, Gustavo A, Stolovitzky, and María Rodríguez, Martínez. "COSIFER: a python package for the consensus inference of molecular ...

Type: Nextflow

Creators: Laura Rodriguez-Navas, José Mª Fernández

Submitter: Laura Rodriguez-Navas

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