PycoQC computes metrics and generates interactive QC plots for Oxford Nanopore technologies sequencing data


Keywords
computing-metrics, generates-plots, jupyter-notebook, nanopore
License
GPL-3.0
Install
pip install pycoQC==2.3.1.2

Documentation

pycoQC v2.5.2

pycoQC

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PycoQC computes metrics and generates interactive QC plots for Oxford Nanopore technologies sequencing data

PycoQC relies on the sequencing_summary.txt file generated by Albacore and Guppy, but if needed it can also generate a summary file from basecalled fast5 files. The package supports 1D and 1D2 runs generated with Minion, Gridion and Promethion devices, basecalled with Albacore 1.2.1+ or Guppy 2.1.3+. PycoQC is written in pure Python3. Python 2 is not supported. For a quick introduction see tutorial by Tim Kahlke available at https://timkahlke.github.io/LongRead_tutorials/QC_P.html

Full documentation is available at https://a-slide.github.io/pycoQC

Gallery

summary

reads_len_1D_example]

reads_len_1D_example]

reads_qual_len_2D_example

channels_activity

output_over_time

qual_over_time

len_over_time

align_len

align_score

align_score_len_2D

alignment_coverage

alignment_rate

alignment_summary

Example HTML reports

Example JSON reports

Disclaimer

Please be aware that pycoQC is a research package that is still under development.

It was tested under Linux Ubuntu 16.04 and in an HPC environment running under Red Hat Enterprise 7.1.

Thank you

Classifiers

  • Development Status :: 3 - Alpha
  • Intended Audience :: Science/Research
  • Topic :: Scientific/Engineering :: Bio-Informatics
  • License :: OSI Approved :: GNU General Public License v3 (GPLv3)
  • Programming Language :: Python :: 3

licence

GPLv3 (https://www.gnu.org/licenses/gpl-3.0.en.html)

Copyright © 2020 Adrien Leger & Tommaso Leonardi

Authors