plot-nanopore-run

Generates plots reporting on nanopore runs

Requirements

1. Python 2.7
2. matplotlib 2.0.0 + dependencies

Installation

git clone https://github.com/jopineda/plot-nanopore-run.git
virtualenv plot-nanopore-run-venv
# check setuptools installed
pip list
# set up matplotlib
python setup.py install

General usage

usage: plot_nanopore_run.py [-h] -s SEQ_SUMMARIES [SEQ_SUMMARIES ...]
                            [-o OUTPUT_PREFIX] -r RUN_ID
                            [--yield_units {bp,Mbp,Gbp}]

Calculate nanopore run report

optional arguments:
  -h, --help            show this help message and exit
  -s SEQ_SUMMARIES [SEQ_SUMMARIES ...], --summary SEQ_SUMMARIES [SEQ_SUMMARIES ...]
                        sequencing summary tab-separated file(s)
  -o OUTPUT_PREFIX, --output OUTPUT_PREFIX
                        prefix of output directory
  -r RUN_ID, --run_id RUN_ID
                        run id will be displayed as part of titles of plots.
                        NOTE: If plotting multiple runs, use multiple flags in the
                        same order of sequence summary flag. 
                        NOTE: wrap in quotes if spaces included.
  --yield_units {bp,Mbp,Gbp}
                        units for the y-axis of the Total yield plot. {bp,
                        Mbp, Gbp}

Input

Sequencing summmary files were generated using the albacore basecaller. This plotting script takes as input one or more of these text files that come from the same run thus the run_id column should be the same for all of these files.

Example sequence summary file:

filename                        read_id    run_id      channel start_time    duration    num_events    passes_filtering    template_start    num_events_template    template_duration    num_called_template    sequence_length_template    mean_qscore_template    strand_score_template    calibration_strand_genome_template    calibration_strand_identity_template    calibration_strand_accuracy_template    aligned_speed_bps_template
read_1_ch_1531_strand.fast5     read_id_1  run_id_1    1531    6548.61575    1.11875     895            False              0.0               895                    1.11875              895                    443                         5.091                   -0.0013                  filtered_out                          -1.0                                    -1.0                                    0.0
read_2_ch1223_strand.fast5      read_id_2  run_id_1    1531    6545.75575    1.14        912            False              0.0               912                    1.14                 912                    511                         4.7                     -0.0012                  filtered_out                          -1.0                                    -1.0                                    0.0

Output

The script will produce plots for the following and save as png files in a directory with --output name:

1. Total yield as a function of sequencing time
2. Maximum read length as a function of cumulative sequencing time
3. Average read length as a function of cumulative sequencing time
4. Maximum read length per hour
5. Average read length per hour

It will also produce a PDF with all these plots.

Example usage

For single-run plots:

python plot_nanopore_run.py -s /path/to/batch0/sequencing_summary.txt /path/to/batch1/sequencing_summary.txt -r "MinION run 2018-01-22" -o mion_run

For multi-run plots:

python plot_nanopore_run.py \
    -s /path/to/MINIONRUN/batch0/sequencing_summary.txt /path/to/MINIONRUN/batch1/sequencing_summary.txt \
    -r "MinION run 2018-01-22" \
    -s /path/to/PROMETHIONRUN/sequencing_summary.txt \
    -r "PromethION run 2018-02-01" \
    -o nanopore_multi_run

Example output (single run)