Workflows

What is a Workflow?
602 Workflows visible to you, out of a total of 646
Stable

ASPICov was developed to provide a rapid, reliable and complete analysis of NGS SARS-Cov2 samples to the biologist. This broad application tool allows to process samples from either capture or amplicon strategy and Illumina or Ion Torrent technology. To ensure FAIR data analysis, this Nextflow pipeline follows nf-core guidelines and use Singularity containers.

Availability and Implementation: https://gitlab.com/vtilloy/aspicov

Citation: Valentin Tilloy, Pierre Cuzin, Laura Leroi, Emilie Guérin, ...

Type: Nextflow

Creators: Valentin Tilloy, Pierre Cuzin, Laura Leroi, Patrick Durand, Sophie Alain

Submitter: Valentin Tilloy

Work-in-progress Tests Passing

Snakemake workflow: FAIR CRCC - send data

Snakemake GitHub actions status

A Snakemake workflow for securely sharing Crypt4GH-encrypted sensitive data from the CRC Cohort ...

Type: Snakemake

Creator: Luca Pireddu

Submitter: Luca Pireddu

Stable

polya_liftover - sc/snRNAseq Snakemake Workflow

A [Snakemake][sm] workflow for using PolyA_DB and UCSC Liftover with Cellranger.

Some genes are not accurately annotated in the reference genome. Here, we use information provide by the [PolyA_DB v3.2][polya] to update the coordinates, then the [USCS Liftover][liftover] tool to update to a more recent genome. Next, we use [Cellranger][cr] to create the reference and count matrix. Finally, by taking advantage of the integrated [Conda][conda] and ...

Type: Snakemake

Creator: Ryan Patterson-Cross

Submitter: Ryan Patterson-Cross

Stable

RNA-Seq pipeline

Here we provide the tools to perform paired end or single read RNA-Seq analysis including raw data quality control, differential expression (DE) analysis and functional annotation. As input files you may use either zipped fastq-files (.fastq.gz) or mapped read data (.bam files). In case of paired end reads, corresponding fastq files should be named using .R1.fastq.gz and .R2.fastq.gz suffixes.

Pipeline Workflow

All analysis steps are illustrated in the pipeline ...

Type: Bpipe

Creator: Sergi Sayols

Submitter: Sergi Sayols

Stable

ChIP-Seq pipeline

Here we provide the tools to perform paired end or single read ChIP-Seq analysis including raw data quality control, read mapping, peak calling, differential binding analysis and functional annotation. As input files you may use either zipped fastq-files (.fastq.gz) or mapped read data (.bam files). In case of paired end reads, corresponding fastq files should be named using .R1.fastq.gz and .R2.fastq.gz suffixes.

Pipeline Workflow

All analysis steps are illustrated in ...

Type: Bpipe

Creator: Sergi Sayols

Submitter: Sergi Sayols

Stable

DNA-Seq pipeline

Here we provide the tools to perform paired end or single read DNA-Seq analysis including raw data quality control, read mapping, variant calling and variant filtering.

Pipeline Workflow

All analysis steps are illustrated in the pipeline ...

Type: Bpipe

Creator: Sergi Sayols

Submitter: Sergi Sayols

Stable

scRNA-Seq pipelines

Here we forge the tools to analyze single cell RNA-Seq experiments. The analysis workflow is based on the Bioconductor packages scater and scran as well as the Bioconductor workflows by Lun ATL, McCarthy DJ, & Marioni JC [*A step-by-step workflow for low-level analysis of single-cell RNA-seq ...

Type: Bpipe

Creator: Sergi Sayols

Submitter: Sergi Sayols

Stable

scRNA-Seq pipelines

Here we forge the tools to analyze single cell RNA-Seq experiments. The analysis workflow is based on the Bioconductor packages scater and scran as well as the Bioconductor workflows by Lun ATL, McCarthy DJ, & Marioni JC [*A step-by-step workflow for low-level analysis of single-cell RNA-seq ...

Type: Bpipe

Creator: Sergi Sayols

Submitter: Sergi Sayols

Stable

This workflow performs the process of protein-ligand docking, step by step, using the BioExcel Building Blocks library (biobb).

Type: Common Workflow Language

Creators: Adam Hospital, Genís Bayarri

Submitter: Genís Bayarri

DOI: 10.48546/workflowhub.workflow.257.1

Work-in-progress

Abstract CWL Automatically generated from the Galaxy workflow file: GTN 'Pangeo 101 for everyone - Introduction to Xarray'.

In this tutorial, we analyze particle matter < 2.5 μm/m3 data from Copernicus Atmosphere Monitoring Service to understand Xarray Galaxy Tools:

  • Understand how an Xarray dataset is organized;
  • Get metadata from Xarray dataset such as variable names, units, coordinates (latitude, longitude, level), etc;
  • Plot an Xarray dataset on a geographical map and learn to customize ...

Type: Galaxy

Creators: None

Submitter: Anne Fouilloux

Powered by
(v.1.14.1)
Copyright © 2008 - 2023 The University of Manchester and HITS gGmbH