Workflows

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736 Workflows visible to you, out of a total of 791
Cancer variant annotation (hg38 VEP-based)
Stable

This Galaxy workflow takes a list of tumor/normal sample pair variants in VCF format and

  1. annotates them using the ENSEMBL Variant Effect Predictor and custom annotation data
  2. turns the annotated VCF into a MAF file for import into cBioPortal
  3. generates human-readable variant- and gene-centric reports

The input VCF is expected to encode somatic status, somatic p-value and germline p-value of each variant in varscan somatic format, i.e., via SS, SPV and GPV INFO keys, respectively.

Type: Galaxy

Creator: Wolfgang Maier

Submitter: Wolfgang Maier

DOI: 10.48546/workflowhub.workflow.607.1

ERGA HiFi+HiC Assembly+QC Hifiasm v2309 (WF2)
Stable

The workflow takes a trimmed HiFi reads collection, Forward/Reverse HiC reads, and the max coverage depth (calculated from WF1) to run Hifiasm in HiC phasing mode. It produces both Pri/Alt and Hap1/Hap2 assemblies, and runs all the QC analysis (gfastats, BUSCO, and Merqury). The default Hifiasm purge level is Light (l1).

Type: Galaxy

Creators: Diego De Panis, ERGA

Submitter: Diego De Panis

DOI: 10.48546/workflowhub.workflow.605.1

CEITEC layer 2 workflow
Work-in-progress

The ultimate-level complexity workflow is one among a collection of workflows designed to address tasks up to CTF estimation. In addition to the functionalities provided by layer 0 and 1 workflows, this workflow aims to enhance the quality of both acquisition images and processing.

Quality control protocols

…

Combination of methods

  • CTF consensus
  • New methods to compare ctf estimations
  • CTF xmipp criteria (richer parameters i.e. ice detection)

Advantages: 

  • Control of ...

Type: Scipion

Creators: None

Submitter: Daniel Marchan

VVV2_align_PE
Stable

PAIRED-END workflow. Align reads on fasta reference/assembly using bwa mem, get a consensus, variants, mutation explanations.

IMPORTANT:

  • For "bcftools call" consensus step, the --ploidy file is in "Données partagées" (Shared Data) and must be imported in your history to use the worflow by providing this file (tells bcftools to consider haploid variant calling).
  • SELECT THE MOST ADAPTED VADR MODEL for annotation (see vadr parameters).

Type: Galaxy

Creator: Fabrice Touzain

Submitter: Fabrice Touzain

VVV2_align_SE
Stable

SINGLE-END workflow. Align reads on fasta reference/assembly using bwa mem, get a consensus, variants, mutation explanations.

IMPORTANT:

  • For "bcftools call" consensus step, the --ploidy file is in "Données partagées" (Shared Data) and must be imported in your history to use the worflow by providing this file (tells bcftools to consider haploid variant calling).
  • SELECT the mot ADAPTED VADR MODEL for annotation (see vadr parameters).

Type: Galaxy

Creator: Fabrice Touzain

Submitter: Fabrice Touzain

average-bigwig-between-replicates/main

We assume the identifiers of the input list are like: sample_name_replicateID. The identifiers of the output list will be: sample_name

Type: Galaxy

Creator: Lucille Delisle

Submitter: WorkflowHub Bot

ECP experiments

This repository contains the python code to reproduce the experiments in Dłotko, Gurnari "Euler Characteristic Curves and Profiles: a stable shape invariant for big data problems"

Type: Python

Creator: Davide Gurnari

Submitter: Davide Gurnari

DOI: 10.48546/workflowhub.workflow.576.1

repeatmasking/main

RepeatMasking Workflow

This workflow uses RepeatModeler and RepeatMasker for genome analysis.

  • RepeatModeler is a software package for identifying and modeling de novo families of transposable elements (TEs). At the heart of RepeatModeler are three de novo repeat search programs (RECON, RepeatScout and LtrHarvest/Ltr_retriever) which use complementary computational methods to identify repeat element boundaries and family relationships from sequence data.

  • RepeatMasker is a program that analyzes ...

Type: Galaxy

Creator: Romane Libouban

Submitter: WorkflowHub Bot

MLme: Machine Learning Made Easy

This workflow represents the Default ML Pipeline for AutoML feature from MLme. Machine Learning Made Easy (MLme) is a novel tool that simplifies machine learning (ML) for researchers. By integrating four essential functionalities, namely data exploration, AutoML, CustomML, and visualization, MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. MLme serves as a valuable resource that empowers researchers of all technical levels to leverage ...

Type: Workflow Description Language

Creator: Akshay Akshay

Submitter: Akshay Akshay

DOI: 10.48546/workflowhub.workflow.571.1

ERGA Protein-coding gene annotation workflow

ERGA Protein-coding gene annotation workflow.

Adapted from the work of Sagane Joye:

https://github.com/sdind/genome_annotation_workflow

Prerequisites

The following programs are required to run the workflow and the listed version were tested. It should be noted that older versions of snakemake are not compatible with newer versions of singularity as is noted here: https://github.com/nextflow-io/nextflow/issues/1659.

conda v 23.7.3 ...

Type: Snakemake

Creator: Sagane Joye-Dind

Submitter: Tom Brown

DOI: 10.48546/workflowhub.workflow.569.1

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