Workflows

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817 Workflows visible to you, out of a total of 891
Swedish Earth Biogenome Project Genome Assembly Workflow
Work-in-progress

Swedish Earth Biogenome Project - Genome Assembly Workflow

The primary genome assembly workflow for the Earth Biogenome Project at NBIS.

Workflow overview

General aim:

flowchart LR 
hifi[/ HiFi reads /] --> data_inspection 
ont[/ ONT reads /] --> data_inspection 
hic[/ Hi-C reads /] --> data_inspection 
data_inspection[[ Data inspection ]] --> preprocessing 
preprocessing[[ Preprocessing ]] --> assemble 
assemble[[ Assemble ]] --> validation 
validation[[ Assembly
...

Type: Nextflow

Creators: Mahesh Binzer-Panchal, Martin Pippel

Submitter: Mahesh Binzer-Panchal

Marine Omics identifying biosynthetic gene clusters

Secondary metabolite biosynthetic gene cluster (SMBGC) Annotation using Neural Networks Trained on Interpro Signatures

Type: Galaxy

Creator: Marie Jossé

Submitter: Marie Jossé

Scaffolding-Bionano-VGP7/main

Scaffolding with Bionano

Scaffolding using Bionano optical map data

Inputs

  1. Bionano data [cmap]
  2. Estimated genome size [txt]
  3. Phased assembly generated by Hifiasm [gfa1]

Outputs

  1. Scaffolds
  2. Non-scaffolded contigs
  3. QC: Assembly statistics
  4. QC: Nx plot
  5. QC: Size plot

Type: Galaxy

Creator: Galaxy, VGP

Submitter: WorkflowHub Bot

RiboSnake: 16S rRNA analysis workflow with QIIME2 and Snakemake

RiboSnake: 16S rRNA analysis workflow with QIIME2 and Snakemake

Snakemake Build Status

Qiime2 workflow for 16S analysis created with snakemake.

Authors

  • Ann-Kathrin Dörr (@AKBrueggemann)

Usage

If you use this workflow in a paper, don't forget to give credits to the authors ...

Type: Snakemake

Creator: Ann-Kathrin Dörr

Submitter: Ann-Kathrin Dörr

DOI: 10.48546/workflowhub.workflow.1102.1

Random Forest Classifier executed in 3 nodes, 1 master and 2 workers, with a generated dataset, using 1 Million rows x 100 features

Name: Random Forest Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum4 This is an example of Random Forest algorithm from dislib. To show the usage, the code generates a synthetical input matrix. The results are printed by screen. This application used dislib-0.9.0

Type: COMPSs

Creator: Fernando Vázquez-Novoa

Submitter: Fernando Vázquez-Novoa

DOI: 10.48546/workflowhub.workflow.748.1

GridSearch on kNN non data persistence

Name: GridSearchCV Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum5

GridSearch of kNN algorithm for the iris.csv dataset (https://gist.githubusercontent.com/netj/8836201/raw/6f9306ad21398ea43cba4f7d537619d0e07d5ae3/iris.csv). This application used dislib-0.9.0

Type: COMPSs

Creator: Fernando Vázquez-Novoa

Submitter: Fernando Vázquez-Novoa

DOI: 10.48546/workflowhub.workflow.1095.1

GridSearch on kNN

Name: GridSearchCV Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum5

GridSearch of kNN algorithm for the iris.csv dataset (https://gist.githubusercontent.com/netj/8836201/raw/6f9306ad21398ea43cba4f7d537619d0e07d5ae3/iris.csv). This application used dislib-0.9.0

Type: COMPSs

Creator: Fernando Vázquez-Novoa

Submitter: Fernando Vázquez-Novoa

DOI: 10.48546/workflowhub.workflow.1094.1

qiime2-III-VI-downsteam/QIIME2-III-V-Phylogeny-Rarefaction-Taxonomic-Analysis

This workflow

  • Reconstruct phylogeny (insert fragments in a reference)
  • Alpha rarefaction analysis
  • Taxonomic analysis

Type: Galaxy

Creators: Debjyoti Ghosh, Helmholtz-Zentrum für Umweltforschung - UFZ

Submitter: WorkflowHub Bot

End-to-end EI+ mass spectra prediction workflow using QCxMS
Stable

High-Performance Computing (HPC) environments are integral to quantum chemistry and computationally intense research, yet their complexity poses challenges for non-HPC experts. Navigating these environments proves challenging for researchers lacking extensive computational knowledge, hindering efficient use of domain specific research software. The prediction of mass spectra for in silico annotation is therefore inaccessible for many wet lab scientists. Our main goal is to facilitate non-experts ...

Type: Galaxy

Creators: Zargham Ahmad, Helge Hecht, Wudmir Rojas, RECETOX SpecDat

Submitters: Helge Hecht, Wudmir Rojas

DOI: 10.48546/workflowhub.workflow.897.2

Differential peak analysis with SnapATAC2

This workflow takes a cell-type-annotated AnnData object (processed with SnapATAC2) and performs peak calling with MACS3 on the cell types. Next, a cell-by-peak matrix is constructed and differential accessibility tests are performed for comparison of either two cell types or one cell type with a background of all other cells. Lastly, differentially accessible marker regions for each cell type are identified.

Type: Galaxy

Creator: Timon Schlegel

Submitter: Timon Schlegel

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