demort

DEmultiplexing MOnitoring Report Tool


Keywords
bioinformatics, demultiplexing, fastq, multithreading, ngs, parallelization, pypi-package, python3, vizualisation
License
MIT
Install
pip install demort==0.2.4

Documentation

PyPI version mit license

DEMORT

DEmultiplexing MOnitoring Report Tool. DEMORT evaluates demultiplexing fastq files by computing various metrics.

demort evaluates demultiplexed fastq files by computing various metrics. demort is a python3 program.

INSTALLATION

First, install dependencies, then you can perform a basic installation or PyPI installation.

Dependencies

You need to install python 3.7 and depencies. Check version by typing on:

python3 --version

python3 depencies :

see INSTALL.sh for details about installation of python3 dependencies

Basic installation

Simply download the python script

wget https://raw.githubusercontent.com/Grelot/demort/master/src/demort.py

then execute it

python3 demort.py -h

PyPI installation

Install demort on your system using :

pip3 install demort

check installation :

demort.py -h

USAGE

demort check fastq files into specified folder(s) then count number of reads for each fastq files for each folder and finally return a summary csv table and a pdf boxplot picture.

(process a list of folder as a strings)

demort.py -d folder/folder1,folder/folder2,folder/folder3 \           
        -t 8 \
        -p results.pdf \
        -o results.csv

(process a list of folder into a file)

demort.py -d example/folder_to_process.txt \           
        -t 8 \
        -p results.pdf \
        -o results.csv

(process folders into a folder)

demort.py -d <(ls folder) \
        -t 8 \
        -p results.pdf \
        -o results.csv

COMMAND-LINE ARGUMENTS

complete flag argument short flag Default value Summary
--inputFolder -d NA a string of folderpath separated by coma , OR a file containing a list (e.g. folder_to_process.txt)
--threads -t 1 Number of available cores
--output_pdf -p NA path of the file where to write a pdf boxplot picture
--output_csv -o NA path of the file where to write a csv table

INPUT

folder/
├── folder1
│   ├── fqfileA.fq.gz
│   ├── fqfileB.fq.gz
│   └── fqfileC.fq.gz
├── folder2
│   ├── fqfileD.fq.gz
│   └── fqfileE.fq.gz
└── folder3
    ├── fqfileF.fq.gz
    ├── fqfileG.fq.gz
    └── fqfileH.fq.gz

OUTPUTS

  • summary csv table [foldername, filename, number of reads]
folder1,fqfileA,2686166
folder1,fqfileB,1223937
folder1,fqfileC,934242
folder2,fqfileD,1947607
folder2,fqfileE,1658147
folder3,fqfileF,1699691
folder3,fqfileG,1293436
folder3,fqfileH,1470963
  • pdf boxplot picture

demort visualization

SYSTEM REQUIREMENTS

Linux (64-bit and 32-bit with slightly limited functionality) and macOS (OS X) are supported.

For the main pipeline:

  • Python3 (3.7 or higher)
  • zlib development files