Workflows

What is a Workflow?
1205 Workflows visible to you, out of a total of 1289
Stable

Using:

  • vadr annotation (virus model must be selected in options)
  • vardict variant caller
  • coverage depth Provides summarizing files:
  • png image of variant calling with annotations and coverage depths
  • tsv file with all information of significant variants only (can be opened in Excel/LibreOffice)

Type: Galaxy

Creators: Fabrice Touzain, This study was founded by the French National Research Agency and by Santé publique France as part of the project "EMERGEN". Anses Ploufragan research was also supported by Agglomération de Saint-Brieuc, Département des Côtes d'Armor and Région Bretagne

Submitter: Fabrice Touzain

GitHub Actions CI Status GitHub Actions Linting StatusAWS CI[![Cite ...

Type: Nextflow

Creators: Danilo Di Leo, Emelie Nilsson & Daniel Lundin

Submitter: WorkflowHub Bot

This workflow performs the scaffolding of a genome assembly using HiC data with YAHS. Can be used on any assembly with Hi-C data, and the assembly in the gfa format. You can generate a gfa from a fasta using the gfastat tool. Part of the VGP set of workflows, it is meant to be run after the contigging (workflows 3,4, or 5), optional purging step (Workflow 6 or 6b), and an optionnal scaffolding with Bionano data (Workflow 7). This workflow includes QC with Assembly statistics, Busco, and Hi-C maps. ...

Type: Galaxy

Creator: VGP, Galaxy

Submitter: WorkflowHub Bot

Stable

Introduction

ebi-metagenomics/biosiftr is a bioinformatics pipeline that generates taxonomic and functional profiles for low-yield (shallow shotgun: < 10 M reads) short raw-reads using MGnify biome-specific genome catalogues as a reference.

The biome selection includes all the biomes available in the MGnify genome catalogues.

The main sections of the pipeline include the following ...

Stable

Mobilome Annotation Pipeline (former MoMofy)

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 integrative elements. Plasmids are mostly extrachromosmal; phages can be found extrachromosmal or as temperate phages (prophages); whereas integrons are stable inserted in the chromosome. Autonomous elements are ...

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Type: Nextflow

Creators: None

Submitter: WorkflowHub Bot

Work-in-progress
No description specified

Type: Galaxy

Creators: None

Submitter: Andrei Variu

Assembly of metagenomic sequencing data

Associated Tutorial

This workflows is part of the tutorial Assembly of metagenomic sequencing data, available in the GTN

Features

Type: Galaxy

Creators: None

Submitter: GTN Bot

DeepAnnotation can be used to perform genomic selection (GS), which is a promising breeding strategy for agricultural breeding. DeepAnnotation predicts phenotypes from comprehensive multi-omics functional annotations with interpretable deep learning framework. The effectiveness of DeepAnnotation has been demonstrated in predicting three pork production traits (lean meat percentage at 100 kg [LMP], loin muscle depth at 100 kg [LMD], back fat thickness at 100 kg [BF]) on a population of 1940 Duroc ...

Type: Python

Creators: Wenlong Ma, Weigang Zheng, Shenghua Qin, Chao Wang, Bowen Lei, Yuwen Liu

Submitter: Ma Wenlong

DOI: 10.48546/workflowhub.workflow.1732.1

Stable

High-throughput phenotyping is addressing the current bottleneck in phenotyping within breeding programs. Imaging tools are becoming the primary resource for improving the efficiency of phenotyping processes and providing large datasets for genomic selection approaches. The advent of AI brings new advantages by enhancing phenotyping methods using imaging, making them more accessible to breeding programs. In this context, we have developed an open Python workflow for analyzing morphology, colour ...

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