NGS-QCbox

NOTE: I am working on a complete revamp of this pipeline inorder to simplify the pipeline.

Citation

NGS-QCbox and Raspberry for Parallel, Automated and Rapid Quality Control Analysis of Large-Scale Next Generation Sequencing (Illumina) Data cite: Katta, Mohan AVSK, Aamir W. Khan, Dadakhalandar Doddamani, Mahendar Thudi, and Rajeev K. Varshney. "NGS-QCbox and Raspberry for Parallel, Automated and Rapid Quality Control Analysis of Large-Scale Next Generation Sequencing (Illumina) Data." PloS one 10, no. 10 (2015): e0139868.

It is a QC tool box for processing Next generation sequencing data of Illumina HiSeq and MiSeq

NGS-QCbox is a commandline pipeline that enables NGS quality control to be performed with ease. The outputs include base and read level statistics, genome coverage and variant infomation.

REQUIREMENTS

- Java 1.7 (preferrably 1.7.0_11). Java 1.8 is not supported.
- bash >= v4(assuming that you are working on Linux environment)
- Python >= v2.6
(These are mostly  available on Linux platforms by default)

INSTALL

git clone https://github.com/CEG-ICRISAT/NGS-QCbox.git

OR

Download zip file from https://github.com/CEG-ICRISAT/NGS-QCbox/archive/master.zip

$ unzip  NGS-QCBox-master.zip

and then

$ cd NGS-QCbox
$ source sourceme.ngsqcbox (This sets $QCBIN shell variable)

Now navigate to the workspace containing data, data folder, (I assume the fastq files to be QCed are in a dir called samples) prepare a file called 'samples.txt' with the format:

sample1:500:700
sample2:550:800
sample3:300:600
sample4:450:760

This is sample id, min insert size and max insert size delimited by colon. Make sure you have the 'samples.txt' file in the current working dir. and then run

$ $QCBIN/NGS-QCbox-v0.1.py 
An example session:
        NGSQCBox toolkit v 0.1
        ~~~~~~~~~~~~~~~~~~~~~~
        1) Quick mode QC
        2) Complete mode QC
        Enter a choice:
        2
Enter reference fasta full path: <path to reference file>
Enter the reference genome size: <enter reference genome size>
Enter bowtie2 index full path: <provide bowtie index path>
Enter data folder path : <provide data folder containing samples in *.fastq.gz format>
Number of processors to use :  <provide number of processors to use>

Quick mode run is similar, just choose option 1, at menu (see above). NGSQCbox-v0.1.py, the Python script, is the main script that parallelizes the tasks for processing multiple samples generated from hiseq or miseq in batches. Note: While running quick mode, the sample sheet can be without min/max insert size values and so it looks as below

sample1::
sample2::
sample3::
sample4::

PREREQUISITES

Remember to set the path for reference (fasta format), bowtie2-index and genome size in the complete_qc.bpipe / quick_qc.bpipe in qcbin dir. Insert sizes need to be included in a formatted text file called ‘samples.txt’.

ASSUMPTIONS

• The samples to be analyzed are in a folder - this is "data path" option in the menu
• The quality range is assumed to be in phred+33 format.
• The input FASTQ format file names are in a specific format - for example, sample1_R1.fastq.gz and sample1_R2.fastq.gz. (It is this "sample1" prefix that goes into the samplesheet.txt file)

DATASETS USED FOR TESTING

The simulated paired end read datasets used for testing this software are available at the following public web-links

http://de.iplantcollaborative.org/dl/d/B1B7C2BB-0252-4B96-AA3C-2F28DA42A277/A_R1.fastq.gz http://de.iplantcollaborative.org/dl/d/655AE8D6-B88F-4612-A330-1EE747ECB1FF/A_R2.fastq.gz

RESULTS

Quick mode run generates a folder by name [sample]_QC_quick and complete mode generates [sample]_QC_complete in the data path folder containing samples.

-The pipeline generates two files namely, "detailed_qc_[complete|quick].txt" and "QC_final_[complete|quick].txt"; depending on the quick/complete mode of the pipeline run.

1. detailed_QC_[quick|complete].txt contains information on counts of reads, bases, read length range, counts of A/T/G/C/N, percentage of GC content and quality range.

2. QC_final_[quick|complete].txt summarizes the above information for all the samples. It contains in addition to the reads generated and retained after quality trimming, pecentage of alignment, genome coverage at 1X to 15X and mean read depth observed from alignment.

DOCKER image

A docker based image containing NGS-QCBox and Raspberry is provided for convenience to users. This image can be pulled from dadu/ngsqcbox:v0.2.1 or dadu:ngsqcbox_win:v0.2. Installation and usage of docker image could be found on the docker manual page (For Linux - https://docs.docker.com/linux/step_one/ , For windows- https://docs.docker.com/windows/step_one/). The docker image works well with the linux operating systems.

Note for Windows user:

1. The user must run the docker image as Administrator.

2. The user must create a copy of the input fastq/fastq.gz files before the QC run as the original files are renamed for the execution of the pipeline and restored back once the QC finishes.

3. The user must grant permission of read and write to folder used for QC.

4. The user must not halt the pipeline midway during the QC run as the original fastq/fastq.gz files.

The usage of the docker image is as follows:

docker pull dadu/ngsqcbox:v0.2.1 (for Linux versions)
docker run -it dadu/ngsqcbox:v0.2.1

docker pull dadu/ngsqcbox_win:v0.2 (for Windows)
docker run -it dadu/ngsqcbox_win:v0.2 

NGS-QCbox could be located in the /data directory
Follow the steps in the given order:
cd /data/NGS-QCbox/
source sourceme.ngsqcbox

and find the latest NGS-QCBox and Raspberry on /data partition in the docker image For more information on using docker images please refer to www.docker.com documentation.

DISCLAIMER

-This tool has been tested on Linux platform only (ubuntu 12.10 and 14.04). It should work on any other linux flavour provided you have the tools in REQUIREMENTS section.

LICENSE

GPL v3 A copy of GPLv3 is included in the package