Workflows

What is a Workflow?
738 Workflows visible to you, out of a total of 793
Work-in-progress

atavide is a complete workflow for metagenomics data analysis, including QC/QA, optional host removal, assembly and cross-assembly, and individual read based annotations. We have also built in some advanced analytics including tools to assign annotations from reads to contigs, and to generate metagenome-assembled genomes in several different ways, giving you the power to explore your data!

atavide is 100% snakemake and conda, so you only need to install the snakemake workflow, and then ...

Type: Snakemake

Creators: None

Submitter: Rob Edwards

DOI: 10.48546/workflowhub.workflow.241.1

Stable

Exome SAMtools Workflow

Type: Nextflow

Creator: Laura Rodriguez-Navas

Submitter: Laura Rodriguez-Navas

Stable

Exome Alignment Workflow

Type: Common Workflow Language

Creator: Laura Rodriguez-Navas

Submitter: Laura Rodriguez-Navas

Stable

Summary

This notebook demonstrates how to retrieve metadata associated to the paper A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection and available in IDR at idr0094-ellinger-sarscov2. Over 300 compounds were used in this investigation. This notebook allows the user to calculate the half maximal inhibitory concentration (IC50) for ...

Type: Jupyter

Creators: Jean-Marie Burel, Andrea Zaliani

Submitter: Jean-Marie Burel

DOI: 10.48546/workflowhub.workflow.238.1

Work-in-progress

This is a genomics pipeline to do a single germline sample variant-calling, adapted from GATK Best Practice Workflow.

This workflow is a reference pipeline for using the Janis Python framework (pipelines assistant).

  • Alignment: bwa-mem
  • Variant-Calling: GATK HaplotypeCaller
  • Outputs the final variants in the VCF format.

Resources

This pipeline has been tested using the HG38 reference set, available on Google Cloud Storage through:

Type: Janis

Creators: Richard Lupat, Michael Franklin; Jiaan Yu; Juny Kesumadewi

Submitter: Richard Lupat

Combined workflow for large genome assembly

The tutorial document for this workflow is here: https://doi.org/10.5281/zenodo.5655813

What it does: A workflow for genome assembly, containing subworkflows:

  • Data QC
  • Kmer counting
  • Trim and filter reads
  • Assembly with Flye
  • Assembly polishing
  • Assess genome quality

Inputs:

  • long reads and short reads in fastq format
  • reference genome for Quast

Outputs:

  • Data information - QC, kmers
  • Filtered, trimmed reads
  • Genome assembly, assembly graph, ...

Type: Galaxy

Creator: Anna Syme

Submitter: Anna Syme

DOI: 10.48546/workflowhub.workflow.230.1

Stable
No description specified

Type: Galaxy

Creators: None

Submitter: Mike Thang

Stable

MetaDEGalaxy: Galaxy workflow for differential abundance analysis of 16s metagenomic data

Type: Galaxy

Creators: None

Submitter: Mike Thang

Assess genome quality; can run alone or as part of a combined workflow for large genome assembly.

  • What it does: Assesses the quality of the genome assembly: generate some statistics and determine if expected genes are present; align contigs to a reference genome.
  • Inputs: polished assembly; reference_genome.fasta (e.g. of a closely-related species, if available).
  • Outputs: Busco table of genes found; Quast HTML report, and link to Icarus contigs browser, showing contigs aligned to a reference ...

Type: Galaxy

Creator: Anna Syme

Submitter: Anna Syme

DOI: 10.48546/workflowhub.workflow.229.1

Assembly polishing subworkflow: Racon polishing with long reads

Inputs: long reads and assembly contigs

Workflow steps:

  • minimap2 : long reads are mapped to assembly => overlaps.paf.
  • overaps, long reads, assembly => Racon => polished assembly 1
  • using polished assembly 1 as input; repeat minimap2 + racon => polished assembly 2
  • using polished assembly 2 as input, repeat minimap2 + racon => polished assembly 3
  • using polished assembly 3 as input, repeat minimap2 + racon => ...

Type: Galaxy

Creator: Anna Syme

Submitter: Anna Syme

DOI: 10.48546/workflowhub.workflow.227.1

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