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834 Workflows visible to you, out of a total of 910
Racon polish with Illumina reads, x2

Assembly polishing subworkflow: Racon polishing with short reads

Inputs: short reads and assembly (usually pre-polished with other tools first, e.g. Racon + long reads; Medaka)

Workflow steps:

  • minimap2: short reads (R1 only) are mapped to the assembly => overlaps.paf. Minimap2 setting is for short reads.
  • overlaps + short reads + assembly => Racon => polished assembly 1
  • using polished assembly 1 as input; repeat minimap2 + racon => polished assembly 2
  • Racon short-read polished ...

Type: Galaxy

Creator: Anna Syme

Submitter: Anna Syme

DOI: 10.48546/workflowhub.workflow.228.1

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Assembly polishing

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

  • What it does: Polishes (corrects) an assembly, using long reads (with the tools Racon and Medaka) and short reads (with the tool Racon). (Note: medaka is only for nanopore reads, not PacBio reads).
  • Inputs: assembly to be polished: assembly.fasta; long reads - the same set used in the assembly (e.g. may be raw or filtered) fastq.gz format; short reads, R1 only, in fastq.gz format
  • Outputs: ...

Type: Galaxy

Creator: Anna Syme

Submitter: Anna Syme

DOI: 10.48546/workflowhub.workflow.226.1

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Preparing a data set for Deep Learning from zipped ABR raw data files

This notebook is about pre-processing the Auditory Brainstem Response (ABR) raw data files provided by Ingham et. al to create a data set for Deep Learning models.

The unprocessed ABR data files are available at Dryad.

Since the ABR raw data are available as zip-archives, these have to be unzipped and the extracted raw data files parsed so that the time ...

Type: Jupyter

Creator: Elida Schneltzer

Submitter: Elida Schneltzer

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Quality assessment, amplicon classification and functional prediction

Workflow for quality assessment of paired reads and classification using NGTax 2.0 and functional annotation using picrust2. In addition files are exported to their respective subfolders for easier data management in a later stage. Steps:

  • FastQC (read quality control)
  • NGTax 2.0
  • Picrust 2
  • Export module for ngtax

Type: Common Workflow Language

Creators: Bart Nijsse, Jasper Koehorst

Submitter: Jasper Koehorst

DOI: 10.48546/workflowhub.workflow.154.2

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Protein MD Setup tutorial using BioExcel Building Blocks (biobb) in KNIME
Work-in-progress

This is an experimental KNIME workflow of using the BioExcel building blocks to implement the Protein MD Setup tutorial for molecular dynamics with GROMACS.

Note that this workflow won't import in KNIME without the experimental KNIME nodes for BioBB - contact Adam Hospital for details.

Type: KNIME

Creator: Adam Hospital

Submitter: Stian Soiland-Reyes

DOI: 10.48546/workflowhub.workflow.201.1

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Protein MD Setup HPC tutorial using BioExcel Building Blocks (biobb) in PyCOMPSs
Stable

This PyCOMPSs workflow tutorial aims to illustrate the process of setting up a simulation system containing a protein, step by step, using the BioExcel Building Blocks library (biobb) in PyCOMPSs for execution on HPC. Three variants of the MD Setup workflows are included, supporting a list of structures, a list of mutations, or a cumulative set of mutations.

Type: COMPSs

Creators: Adam Hospital, Pau Andrio

Submitter: Stian Soiland-Reyes

DOI: 10.48546/workflowhub.workflow.200.1

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lncRNA
Stable

Analysis of RNA-seq data starting from BAM and focusing on mRNA, lncRNA and miRNA

Type: Galaxy

Creators: None

Submitter: Bianca Pasat

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Workflow of BioTranslator Comparative Analysis
Stable

This workflow is based on the idea of comparing different gene sets through their semantic interpretation. In many cases, the user studies a specific phenotype (e.g. disease) by analyzing lists of genes resulting from different samples or patients. Their pathway analysis could result in different semantic networks, revealing mechanistic and phenotypic divergence between these gene sets. The workflow of BioTranslator Comparative Analysis compares quantitatively the outputs of pathway analysis, ...

Type: Galaxy

Creators: None

Submitter: thodk

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BioTranslator Workflow
Stable

BioTranslator performs sequentially pathway analysis and gene prioritization: A specific operator is executed for each task to translate the input gene set into semantic terms and pinpoint the pivotal-role genes on the derived semantic network. The output consists of the set of statistically significant semantic terms and the associated hub genes (the gene signature), prioritized according to their involvement in the underlying semantic topology.

Type: Galaxy

Creators: None

Submitter: thodk

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entryTitleTest

Cryo-EM processing workflow

Type: Common Workflow Language

Creators: None

Submitter: Irene Sánchez

DOI: 10.48546/workflowhub.workflow.188.1

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