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

Project description

pycoQC

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


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 generates a summary file from basecalled fast5 files. The package supports 1D and 1D2 runs generated with Minion, Gridion and Promethion devices and basecalled with Albacore 1.2.1+ or Guppy 2.1.3+. PycoQC is written in pure Python3. Python 2 is not supported.

Great tutorial with detailed explanations by Tim Kahlke available at https://timkahlke.github.io/LongRead_tutorials/QC_P.html

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

Authors

  • Adrien Leger - aleg {at} ebi.ac.uk

  • Tommaso Leonardi - tom {at} tleo.io

Project details


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