usage: NanoPlot [-h] [-v] [-t THREADS] [--verbose] [--store] [--raw] [--huge] [-o OUTDIR] [--no_static] [-p PREFIX] [--tsv_stats] [--info_in_report] [--maxlength N]
                [--minlength N] [--drop_outliers] [--downsample N] [--loglength] [--percentqual] [--alength] [--minqual N] [--runtime_until N] [--readtype {1D,2D,1D2}]
                [--barcoded] [--no_supplementary] [-c COLOR] [-cm COLORMAP] [-f [{png,jpg,jpeg,webp,svg,pdf,eps,json} ...]] [--plots [{kde,hex,dot} ...]]
                [--legacy [{kde,dot,hex} ...]] [--listcolors] [--listcolormaps] [--no-N50] [--N50] [--title TITLE] [--font_scale FONT_SCALE] [--dpi DPI] [--hide_stats]
                (--fastq file [file ...] | --fasta file [file ...] | --fastq_rich file [file ...] | --fastq_minimal file [file ...] | --summary file [file ...] | --bam file [file ...] | --ubam file [file ...] | --cram file [file ...] | --pickle pickle | --feather file [file ...])

CREATES VARIOUS PLOTS FOR LONG READ SEQUENCING DATA.

General options:
  -h, --help            show the help and exit
  -v, --version         Print version and exit.
  -t, --threads THREADS
                        Set the allowed number of threads to be used by the script
  --verbose             Write log messages also to terminal.
  --store               Store the extracted data in a pickle file for future plotting.
  --raw                 Store the extracted data in tab separated file.
  --huge                Input data is one very large file.
  -o, --outdir OUTDIR   Specify directory in which output has to be created.
  --no_static           Do not make static (png) plots.
  -p, --prefix PREFIX   Specify an optional prefix to be used for the output files.
  --tsv_stats           Output the stats file as a properly formatted TSV.
  --info_in_report      Add NanoPlot run info in the report.

Options for filtering or transforming input prior to plotting:
  --maxlength N         Hide reads longer than length specified.
  --minlength N         Hide reads shorter than length specified.
  --drop_outliers       Drop outlier reads with extreme long length.
  --downsample N        Reduce dataset to N reads by random sampling.
  --loglength           Additionally show logarithmic scaling of lengths in plots.
  --percentqual         Use qualities as theoretical percent identities.
  --alength             Use aligned read lengths rather than sequenced length (bam mode)
  --minqual N           Drop reads with an average quality lower than specified.
  --runtime_until N     Only take the N first hours of a run
  --readtype {1D,2D,1D2}
                        Which read type to extract information about from summary. Options are 1D, 2D,
                        1D2
  --barcoded            Use if you want to split the summary file by barcode
  --no_supplementary    Use if you want to remove supplementary alignments

Options for customizing the plots created:
  -c, --color COLOR     Specify a valid matplotlib color for the plots
  -cm, --colormap COLORMAP
                        Specify a valid matplotlib colormap for the heatmap
  -f, --format [{png,jpg,jpeg,webp,svg,pdf,eps,json} ...]
                        Specify the output format of the plots, which are in addition to the html files
  --plots [{kde,hex,dot} ...]
                        Specify which bivariate plots have to be made.
  --legacy [{kde,dot,hex} ...]
                        Specify which bivariate plots have to be made (legacy mode).
  --listcolors          List the colors which are available for plotting and exit.
  --listcolormaps       List the colors which are available for plotting and exit.
  --no-N50              Hide the N50 mark in the read length histogram
  --N50                 Show the N50 mark in the read length histogram
  --title TITLE         Add a title to all plots, requires quoting if using spaces
  --font_scale FONT_SCALE
                        Scale the font of the plots by a factor
  --dpi DPI             Set the dpi for saving images
  --hide_stats          Not adding Pearson R stats in some bivariate plots

Input data sources, one of these is required.:
  --fastq file [file ...]
                        Data is in one or more default fastq file(s).
  --fasta file [file ...]
                        Data is in one or more fasta file(s).
  --fastq_rich file [file ...]
                        Data is in one or more fastq file(s) generated by albacore, MinKNOW or guppy
                        with additional information concerning channel and time.
  --fastq_minimal file [file ...]
                        Data is in one or more fastq file(s) generated by albacore, MinKNOW or guppy
                        with additional information concerning channel and time. Is extracted swiftly
                        without elaborate checks.
  --summary file [file ...]
                        Data is in one or more summary file(s) generated by albacore or guppy.
  --bam file [file ...]
                        Data is in one or more sorted bam file(s).
  --ubam file [file ...]
                        Data is in one or more unmapped bam file(s).
  --cram file [file ...]
                        Data is in one or more sorted cram file(s).
  --pickle pickle       Data is a pickle file stored earlier.
  --feather file [file ...]
                        Data is in one or more feather file(s).

EXAMPLES:
    NanoPlot --summary sequencing_summary.txt --loglength -o summary-plots-log-transformed
    NanoPlot -t 2 --fastq reads1.fastq.gz reads2.fastq.gz --maxlength 40000 --plots hex dot
    NanoPlot --color yellow --bam alignment1.bam alignment2.bam alignment3.bam --downsample 10000