maxgreil/rnaseq

Proof of concept of a RNA-Seq pipeline from reads to count matrix (including quality control) with Nextflow and additional example RNA-Seq analysis in R

rnaseq

Proof of concept of a RNA-Seq pipeline from reads to count matrix (including quality control) with Nextflow and additional example RNA-Seq analysis in R.

Prerequisites

• Unix-like OS (Linux, macOS, etc.)
• Java version 8
• Docker engine 1.10.x (or later)

Necessary files

• Reads to be mapped must be stored in compressed .fastq.gz file format in folder data

Additional necessary files

If the reads to be analyzed originate from a human RNA-Seq experiment, these additional 3 files must be stored in folder data:

• Prebuild Hisat2 index for H. sapiens, release GRCh38

https://genome-idx.s3.amazonaws.com/hisat/grch38_snptran.tar.gz

• Gencode GTF file, release 38 (GRCh38.p13)

https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_38/gencode.v38.chr_patch_hapl_scaff.annotation.gtf.gz

• USCS BED file, assembly GRCh38/hg38, track GENCODE V38

http://genome.ucsc.edu/cgi-bin/hgTables

The BED file must be stored in *.annotation.bed.gz file format.

For the analysis of another species, the corresponding files for this organismus must be downloaded.

Table of Contents

• Quick start
• Installation
• Arguments
• Documentation

Quick start

Because this pipeline uses HISAT2 as the alignment program for mapping reads, this pipeline is for short reads only!

Example run:

nextflow run main.nf

The above example uses default parameter params.reads for single-end reads:

nextflow run main.nf --reads "data/*.fastq.gz"

For paired-end reads, additionally parameter params.singleEnd in nextflow.config must be changed to false. Then the input command must be:

nextflow run main.nf --reads "data/*_{1,2}*.fastq.gz"

Optionally, you can specify the Nextflow output directory with flag --outdir <folder>. By default, all resulting files will be saved in folder output and folder info will contain all information about the last run nextflow session.

Installation

Clone this repository with the following command:

git clone https://github.com/maxgreil/rnaseq && cd rnaseq

Then, install Nextflow by using the following command:

curl https://get.nextflow.io | bash

The above snippet creates the nextflow launcher in the current directory.

Finally pull the following Docker container:

docker pull maxgreil/rnaseq

Alternatively, you can build the Docker Image yourself using the following command:

cd docker && docker image build . -t maxgreil/rnaseq

Arguments

Optional Arguments

Argument	Usage	Description
--reads	<files>	Directory and glob pattern of input files
--outdir	<folder>	Directory to save output files

Documentation

This pipeline is designed to:

• map given reads to a genome
• create a count matrix of mapped reads for subsequent RNA-Seq analysis in R
• do a quality control of the created files

Pipeline overview

The pipeline is built using Nextflow and processes data using the following steps:

1. hisat2 - map given reads to genome
2. samtools - create sorted BAM files from HISAT2 SAM files
3. picard - mark duplicates in sorted BAM files
4. featureCounts - count mapped reads to genomic features (exons)
5. deeptools - create BIGWIG from BAM for IGV
6. preseq - predict and estimate the complexity of genomic sequencing library
7. reseqc - comprehensive evaluation of used RNA-Seq data
8. FastQC - BAM file quality control
9. MultiQC - aggregate report, describing results of the whole pipeline