pycoQC, interactive quality control for Oxford Nanopore Sequencing
pycoQC is a new tool to generate interactive quality control metrics and plots from basecalled nanopore reads or summary files generated by Albacore and Guppy. Although there are other open-source alternatives such as Nanoplot, MinionQC and toulligQC, pycoQC has several novel features:
- Integration with the plotly Python charting library to create dynamic D3.js visualizations
- Extensive Python API developed for interactive data exploration in Jupyter Notebooks
- Simple command line interface to generate customisable interactive HTML reports
- Multiprocessing FAST5 feature extraction program to generate a summary file directly from FAST5 files
- Support for data generated by ONT MinION, GridION and PromethION devices, basecalled by Albacore 1.3+, Guppy 2.1.3+ or MinKNOW 18.12+
pycoQC is available at https://github.com/a-slide/pycoQC together with extensive documentation and some example Jupyter notebooks. The source code has been archived on Zenodo with the linked DOI: 10.5281/zenodo.1116396.
