# Research Object Crate for rnaseq from github

Original URL: https://dev.workflowhub.eu/workflows/246/ro_crate?version=1

# ![nfcore/rnaseq](docs/images/nfcore-rnaseq_logo.png) [![Build Status](https://travis-ci.org/nf-core/rnaseq.svg?branch=master)](https://travis-ci.org/nf-core/rnaseq) [![Nextflow](https://img.shields.io/badge/nextflow-%E2%89%A50.31.1-brightgreen.svg)](https://www.nextflow.io/) [![Gitter](https://img.shields.io/badge/gitter-%20join%20chat%20%E2%86%92-4fb99a.svg)](https://gitter.im/nf-core/Lobby) [![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg)](http://bioconda.github.io/) [![Docker Container available](https://img.shields.io/docker/automated/nfcore/rnaseq.svg)](https://hub.docker.com/r/nfcore/rnaseq/) ![Singularity Container available]( https://img.shields.io/badge/singularity-available-7E4C74.svg) ### Introduction **nfcore/rnaseq** is a bioinformatics analysis pipeline used for RNA sequencing data. The workflow processes raw data from FastQ inputs ([FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/), [Trim Galore!](https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/)), aligns the reads ([STAR](https://github.com/alexdobin/STAR) or [HiSAT2](https://ccb.jhu.edu/software/hisat2/index.shtml)), generates gene counts ([featureCounts](http://bioinf.wehi.edu.au/featureCounts/), [StringTie](https://ccb.jhu.edu/software/stringtie/)) and performs extensive quality-control on the results ([RSeQC](http://rseqc.sourceforge.net/), [dupRadar](https://bioconductor.org/packages/release/bioc/html/dupRadar.html), [Preseq](http://smithlabresearch.org/software/preseq/), [edgeR](https://bioconductor.org/packages/release/bioc/html/edgeR.html), [MultiQC](http://multiqc.info/)). See the [output documentation](docs/output.md) for more details of the results. The pipeline is built using [Nextflow](https://www.nextflow.io), a bioinformatics workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker / singularity containers making installation trivial and results highly reproducible. ### Documentation The nfcore/rnaseq pipeline comes with documentation about the pipeline, found in the `docs/` directory: 1. [Installation](docs/installation.md) 2. Pipeline configuration * [Local installation](docs/configuration/local.md) * [Amazon Web Services (aws)](docs/configuration/aws.md) * [Swedish UPPMAX clusters](docs/configuration/uppmax.md) * [Swedish cs3e Hebbe cluster](docs/configuration/c3se.md) * [Tübingen QBiC](docs/configuration/qbic.md) * [CCGA Kiel](docs/configuration/ccga.md) * [Adding your own system](docs/configuration/adding_your_own.md) 3. [Running the pipeline](docs/usage.md) 4. [Output and how to interpret the results](docs/output.md) 5. [Troubleshooting](docs/troubleshooting.md) ### Credits These scripts were originally written for use at the [National Genomics Infrastructure](https://portal.scilifelab.se/genomics/), part of [SciLifeLab](http://www.scilifelab.se/) in Stockholm, Sweden, by Phil Ewels ([@ewels](https://github.com/ewels)) and Rickard Hammarén ([@Hammarn](https://github.com/Hammarn)). Many thanks to other who have helped out along the way too, including (but not limited to): [@Galithil](https://github.com/Galithil), [@pditommaso](https://github.com/pditommaso), [@orzechoj](https://github.com/orzechoj), [@apeltzer](https://github.com/apeltzer), [@colindaven](https://github.com/colindaven).

Author
License
  https://spdx.org/licenses/Apache-2.0

## Contents

Main Workflow: rnaseq from github
Size: 49030 bytes