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BovReg nf-cage pipeline

This is a CAGE analysis pipeline used in BovReg consortium (https://www.bovreg.eu/) studies. This pipeline was wrapped using NextFlow DSL2 syntax from demultiplexing to base pair resolution and strand specific read counting
(i.e. compatible for import to CAGEfightR https://bioconductor.org/packages/release/bioc/html/CAGEfightR.html)

Pipeline has the following steps:

  1. Demultiplexing raw CAGE sequence data using FASTXtoolkit (allowed mismatch 1)
  2. Trimming CAGE tags using tagDust2 (HMM read architecture provided)
  3. QC before and after (FastQC and MultiQC)
  4. Mapping against reference genome ARS-UCD1.2_Btau5.0.1Y 1000 bull project using bowtie2
  5. BAM >>> bp resolution bedGraph for +ve and -ve strands >>>> bigWig

Installation

Install the latest NextFlow engine on your system following the instructions available at https://www.nextflow.io/
After a successful install you should be able to query the following without any errors:

~/nf-cage$ nextflow info
  Version: 21.04.0 build 5552
  Created: 02-05-2021 16:22 UTC (17:22 BST)
  System: Linux 5.10.43.3-microsoft-standard-WSL2
  Runtime: Groovy 3.0.7 on OpenJDK 64-Bit Server VM 11.0.9.1-internal+0-adhoc..src
  Encoding: UTF-8 (UTF-8)

You would need to use the docker container for reproducibility of the analysis. Please follow the installation guidelines of Docker on your system : https://docs.docker.com/get-docker/ or the desktop client (installs the engine and GUI as the same time) https://docs.docker.com/desktop/

Download this code repository and the respective docker image (Tested on WSL2 Windows 10 and Linux Ubuntu 18.04 LTS)


git clone https://github.com/MazdaX/nf-cage.git
docker pull mazdax/nf-cage:latest

NB. Running this pipeline without docker would require modification of module nf scripts and its not recommended

Quick Start

Sample FASTQ files are in the root folder (fastq_files) along with the barcodes per samples (barcode_files). Replace the files inside these 2 folders with your own experimental data in order to run the pipeline on your dataset.

nextflow run . -with-docker mazdax/nf-cage:latest 

or

nextflow run -profile docker .
N E X T F L O W  ~  version 21.04.3
Launching `./main.nf` [cranky_cantor] - revision: 9e652e725b

===============================================
        nf-cage BovReg's pipeline
        github.com/mazdax/nf-cage
        docker pull mazdax/nf-cage
===============================================
Input : Raw Illumina CAGE sequences
Input : Barcode list TSV (i.e. sample   barcode)
Input : Reference Genome FASTA (bowtie2 index)
Output : Strand specific bp resolution bigWig 
Running task: AIO CAGEfightR import ready
-----------------------------------------------

executor >  local (103)
[9b/f36040] process > qc_pre (FastQC...)                      [100%] 2 of 2 ✔
[f2/a8d4ee] process > demux (Demultiplexing...)               [100%] 2 of 2 ✔
[53/7323fa] process > merger (Gathering demux...)             [100%] 20 of 20 ✔
[37/e53393] process > qc_post (FastQC...)                     [100%] 20 of 20 ✔
[35/4590e7] process > multiqc (MultiQC...)                    [100%] 1 of 1 ✔
[87/7af88a] process > trimmer (Trimming by TagDust2...)       [100%] 19 of 19 ✔
[26/c6d571] process > mapKeeper (Sourcing the reference...)   [100%] 1 of 1 ✔
[0d/b0ce36] process > mapper (Mapping using bowtie2...)       [100%] 19 of 19 ✔
[c6/e7ddfb] process > bG2bW (BAM >>> bedGraph >>> BigWig ...) [100%] 19 of 19 ✔
Completed at: 04-Sep-2021 13:42:08
Duration    : 1d 2h 35m 41s
CPU hours   : 212.7
Succeeded   : 103

Container and toolset

This pipeline uses a docker container for all the tools required and the mamba environment. Please find the details at Docker hub public repository https://hub.docker.com/r/mazdax/nf-cage :

docker pull mazdax/nf-cage:latest

The list of the tools and versions are available in the environment.yml and the Dockerfile. The aria2c compilation was modified using https://registry.hub.docker.com/r/johngong/aria2/dockerfile .

docker build -t mazdax/nf-cage:aria2c .

NB. nf-core and pyinquirer packages were manually removed from the docker builds.

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