Vagus. FASTQ quality analyzer tool

The tool allows one to analyze the quality of sequencing reads.

The Vagus report contains the following data:

0. Basic statistics - file encoding, number of reads, min and max read lenght, GC% in all reads.
1. Per base sequence quality - plots out the range of quality values across all bases at each position in the FastQ file.
   • Warning - if the lower quartile for any base is less than 10, or if the median for any base is less than 25.
   • Failure - if the lower quartile for any base is less than 5 or if the median for any base is less than 20.
2. Per sequence quality scores - plots out the quality scor distribution over all sequences.
   • Warning - if the most frequently observed mean quality is below 27.
   • Failure - if the most frequently observed mean quality is below 20.
3. Per base sequence content - plots out the proportion of each base position in a .fastq for which each of the four normal DNA bases has been called.
   • Warning - if the difference between A and T, or G and C is greater than 10% in any position.
   • Failure - if the difference between A and T, or G and C is greater than 20% in any position.
4. Per sequence GC content - plots out the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.
   • Warning - if the sum of the deviations from the normal distribution represents more than 15% of the reads.
   • Failure - if the sum of the deviations from the normal distribution represents more than 30% of the reads.
5. Per base N content - plots out the percentage of base calls at each position for which an N was called.
   • Warning - if any position shows an N content of >5%.
   • Failure - if any position shows an N content of >20%.
6. Sequence length distribution - generate plot showing the distribution of fragment sizes in the file which was analysed.
   • Warning - if all sequences are not the same length.
   • Failure - if any of the sequences have zero length.
7. Sequence duplication levels - counts the degree of duplication for every sequence in a library and creates a plot showing the relative number of sequences with different degrees of duplication.
   • Warning - if non-unique sequences make up more than 20% of the total.
   • Failure - if non-unique sequences make up more than 50% of the total.
8. Overrepresented sequences - lists all of the sequence which make up more than 0.1% of the total and write it to .csv file.
   • Warning - if any sequence is found to represent more than 0.1% of the total.
   • Failure - if any sequence is found to represent more than 1% of the total.
9. Adapter content - plots a cumulative percentage count of the proportion of library which has seen each of the adapter sequences at each position.
   • Warning - if any sequence is present in more than 5% of all reads.
   • Failure - if any sequence is present in more than 10% of all reads.

Try it!

The program analyzes only sequencing reads in the .fastq format, not .gz archives.

In addition to the required .fastq file, a directory path for saving analysis results can be transferred to the program input. Otherwise, the default prefix will be used.

Important! The time at which the report was generated will be added to output directory prefix.

As a quality check result of the program's work, a .html file will be generated. The .html report will work correctly only together with the generated .png and .csv files from the output folder.

You can test the Vagus with example .fastq file in ./Test_data directory. The Example report placed in ./Example_report.

See below for a description of how to install using pip or poetry and how to get started.

While the program is running, the progress of the work is displayed in the console.

Requiered dependencies

Required Python version [3.9-3.10].

All dependencies can be installed via pip or poetry.

Jinja2 = "3.0.2"
typer = "^0"
matplotlib = "3.5.0"
scipy="1.7.2"
numpy="1.21.4"
seaborn="0.11.2"
pandas="1.3.4"
click=="8.0.3"

Install and run with pip (Ubuntu)

git clone https://github.com/DmitriiPodgalo/Vagus.git
cd Vagus/

# Create and activate your virtual environment

# Install venv
sudo apt install python3-venv

# create virtual environment (with python 3.9 or 3.10)
python3 -m venv ./venv

# activate virtual environment
source ./venv/bin/activate

# required by pip to build wheels
pip install wheel==0.37.0 

# Install requirements
pip install -r ./requirements.txt

# Run file (with python 3.9 or 3.10)
python3 parsing_report.py --help
python3 parsing_report.py -i ./Test_data/amp_res_1.fastq -o ./results_dir/

# Exit fron venv:
deactivate

Install and run with poetry (Ubuntu)

# install poetry
# for details look for https://python-poetry.org/docs/
sudo apt-get install curl
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python3.10 -

# poetry will be accessible in current session
source $HOME/.poetry/env

# prepare project
git clone https://github.com/DmitriiPodgalo/Vagus.git
cd Vagus/

# Install requirements
poetry env use python3
poetry install 

# Run file (with python 3.9 or 3.10)
poetry run python parsing_report.py --help
poetry run python parsing_report.py -i ./Test_data/amp_res_1.fastq -o ./results_dir/

Install and run with pip (Windows)

git clone https://github.com/DmitriiPodgalo/Vagus.git
cd Vagus/

# Chech python version with 
python --version

# Create and activate your virtual environment

# create virtual environment (with python 3.9 or 3.10)
python -m venv ./venv

# activate virtual environment
.\venv\Scripts\activate

# If the command above does not work, please enable scripting and resubmit the command above after it.
Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

# required by pip to build wheels
pip install wheel==0.37.0 

# Install requirements
pip install -r ./requirements.txt

# Run file (with python 3.9 or 3.10)
python parsing_report.py --help
python parsing_report.py -i ./Test_data/amp_res_1.fastq -o ./results_dir/

# Exit fron venv:
deactivate

Install and run with poetry (Windows)

## run PowerShell as administrator!

# install poetry
# for details look for https://python-poetry.org/docs/
(Invoke-WebRequest -Uri https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py -UseBasicParsing).Content | python -

# Exit the PowerShell administrator mode.
# Restart command prompt as user.

# prepare project
git clone https://github.com/DmitriiPodgalo/Vagus.git

# Install requirements
poetry env use python
poetry install

# Run
poetry run python parsing_report.py --help
poetry run python parsing_report.py -i ./Test_data/amp_res_1.fastq -o ./results_dir/

Authors

1. Y. Burankova:
   • README;
   • console input parser via typer;
   • html report creation functions;
   • logging;
   • requiremets and .toml files;
   • correction of the plot design.
   • tested Vagus on Ubuntu 20.04 LTS, Python 3.9.5. and Windows 10 Pro 64x 20H2, Python 3.9.4.
2. A. Gorbonos:
   • draw_gc_content function checker and plot;
   • draw_N_content function checker and plot;
   • draw_deduplicated function checker and plot;
   • tested on MacOS Big Sur v.11.2.3, Python 3.9.8;
3. A. Tokareva:
   • plot_per_base_seq_quality function checker and plot;
   • plot_per_seq_quality_scores function checker and plot;
   • plot_per_base_seq_content checker and plot;
   • tested Vagus on WSL2, Ubuntu 20.04 LTS, Python 3.9.5.
4. D. Podgalo:
   • tool naming;
   • fastq file pasing function;
   • sequence_length_distribution function checker and plot;
   • overrepresented_sequences function checker and plot;
   • adapter_content function checker and plot;
   • correction of the plot design.
   • tested Vagus on MacOS v11.6(20G165), Python 3.9.7.

Tested on

Ubuntu 20.04 LTS, Python 3.9.5.
Windows 10 Pro 64x 20H2, Python 3.9.4.
MacOS v11.6 (20G165), Python 3.9.7.
MacOS v11.2.3 (20D91), Python 3.9.8.
WSL2, Ubuntu 20.04 LTS, Python 3.9.5.