pycoqc-ng

Interactive QC metrics and plots for Oxford Nanopore sequencing data

pycoqc-ng is a maintained continuation of pycoQC by Adrien Leger and Tommaso Leonardi, which is no longer developed. It keeps the original reports and adds support for the current Oxford Nanopore toolchain.

What this fork adds

• Dorado / unaligned BAM input via Bam_to_seq_summary
• POD5 input via Pod5_to_seq_summary
• FASTQ input via Fastq_to_seq_summary, including %GC metrics and plots
• Per-barcode length and %GC boxplots, and a basecall summary broken down by barcode
• Runs on current dependencies: numpy 2.x, pandas 2.x and 3.x, plotly 5 to 7, pysam 0.22+, Python 3.9 to 3.13
• No compiled extension, so it installs as a pure Python package

Installation

pip install git+https://github.com/duceppemo/pycoqc-ng.git

PyPI and bioconda releases are planned; see issues for progress.

To work on the code:

git clone https://github.com/duceppemo/pycoqc-ng.git
cd pycoqc-ng
pip install -e ".[dev]"
pytest

Usage

Generate a report from a basecaller summary:

pycoQC -f sequencing_summary.txt -o pycoQC_report.html

With a Guppy barcoding file, plus a machine-readable summary:

pycoQC -f sequencing_summary.txt -b barcoding_summary.txt \
       -o pycoQC_report.html -j pycoQC_report.json

If you have no summary file, build one from the basecaller output first:

# Dorado unaligned BAM
Bam_to_seq_summary -f bam_dir/ -s sequencing_summary.txt

# POD5
Pod5_to_seq_summary -f pod5_dir/ -s sequencing_summary.txt

# FASTQ (adds %GC)
Fastq_to_seq_summary -f fastq_dir/ -s sequencing_summary.txt

# legacy FAST5
Fast5_to_seq_summary -f fast5_dir/ -s sequencing_summary.txt

Split a summary by barcode:

Barcode_split -f sequencing_summary.txt -o split_dir/

Every command takes --help. pycoQC --default_config prints the plot configuration, which you can edit and pass back with --config_file.

The API mirrors the CLI:

from pycoQC.pycoQC import pycoQC

pycoQC(summary_file="sequencing_summary.txt",
       html_outfile="pycoQC_report.html",
       json_outfile="pycoQC_report.json")

Documentation

The original documentation covers the plots and options in detail, and still applies to the shared functionality: https://a-slide.github.io/pycoQC

Example reports built from the bundled test data live in docs/pycoQC/results/.

Citing

The method and the original implementation are published in JOSS. If you use this tool, please cite the original authors:

Leger A. and Leonardi T. (2019). pycoQC, interactive quality control for Oxford Nanopore Sequencing. Journal of Open Source Software, 4(34), 1236. https://doi.org/10.21105/joss.01236

Disclaimer

This is research software under active development. It is tested on Linux and macOS.

Licence

GPLv3, unchanged from the original project. See LICENSE.

Copyright © 2019-2024 Adrien Leger & Tommaso Leonardi Copyright © 2023-2026 Marc-Olivier Duceppe

Authors

• Adrien Leger and Tommaso Leonardi — original pycoQC
• Marc-Olivier Duceppe — this fork