NanoPlot 0.27.0

Plotting suite for Oxford Nanopore sequencing data and alignments

Plotting tool for Oxford Nanopore sequencing data and alignments.

Example plot

The example plot above shows a bivariate plot comparing log transformed read length with average basecall Phred quality score. More examples can be found in the gallery on my blog ‘Gigabase Or Gigabyte’.

In addition to various plots also a NanoStats file is created summarizing key features of the dataset.

This script performs data extraction from Oxford Nanopore sequencing data in the following formats:

- fastq files

(can be bgzip, bzip2 or gzip compressed)

- fastq files generated by albacore or MinKNOW containing additional information

(can be bgzip, bzip2 or gzip compressed)

- sorted bam files

- sequencing_summary.txt output table generated by albacore

INSTALLATION

pip install NanoPlot

Upgrade to a newer version using:

pip install NanoPlot --upgrade

or

conda install -c bioconda nanoplot

STATUS

The script is written for python3.

USAGE

``` NanoPlot [-h] [-v] [-t THREADS] [–verbose] [-o OUTDIR] [-p PREFIX] [–maxlength N] [–drop_outliers] [–downsample N][–loglength] [–alength] [–minqual N] [–readtype {1D,2D,1D2}] [–barcoded] [-c COLOR][-f {eps,jpeg,jpg,pdf,pgf,png,ps,raw,rgba,svg,svgz,tif,tiff}] [–plots [{kde,hex,dot,pauvre} [{kde,hex,dot,pauvre} …]]][–listcolors] (–fastq file [file …] | –fastq_rich file [file …] | –fastq_minimal file [file …] | –summary file [file …] | –bam file [file …])

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 using the –pickle input option –report Create a html report containing all plots and stats. -o, –outdir OUTDIR Specify directory in which output has to be created. -p, –prefix PREFIX Specify an optional prefix to be used for the output files.

Input data sources, one of these is required.: –fastq file [file …] Data is in one or more default fastq file(s). –fastq_rich file [file …] Data is in one or more fastq file(s) generated by albacore or MinKNOW with additional information concerning channel and time. –fastq_minimal file [file …] Data is in one or more fastq file(s) generated by albacore or MinKNOW with additional information concerning channel and time. Minimal data is extracted swiftly without elaborate checks. –summary file [file …] Data is in one or more summary file(s) generated by albacore. –bam file [file …] Data is in one or more sorted bam file(s). –pickle pickle Data is a pickle file stored earlier using the –store option

Each of these options can take one or multiple files e.g. –summary summary1.txt summary2.txt summary3.txt –bam bam1.txt bam2.txt

Options for filtering or transforming input prior to plotting: –maxlength N Drop reads longer than length specified. –drop_outliers Drop outlier reads with extreme long length. –downsample N Reduce dataset to N reads by random sampling. –loglength Logarithmic scaling of lengths in plots. –alength Use aligned read lengths rather than sequenced length (bam mode) –minqual N Drop reads with an average quality lower than specified. –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

Options for customizing the plots created: -c, –color COLOR Specify a color for the plots, must be a valid matplotlib color -f, –format {eps,jpeg,jpg,pdf,pgf,png,ps,raw,rgba,svg,svgz,tif,tiff} Specify the output format of the plots. –plots [{kde,hex,dot,pauvre} [{kde,hex,dot,pauvre} …]] Specify which bivariate plots have to be made. –listcolors List the colors which are available for plotting and exit.```

EXAMPLES

bash 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 -t 12 --color yellow --bam alignment1.bam alignment2.bam alignment3.bam --downsample 10000 -o bamplots_downsampled

This script now also provides read length vs mean quality plots in the ‘pauvre’-style from [@conchoecia](https://github.com/conchoecia).

ACKNOWLEDGMENTS

I welcome all suggestions, bug reports, feature requests and contributions. Please leave an issue or open a pull request. I will usually respond within a day, or rarely within a few days.

COMPANION SCRIPTS

• NanoComp: comparing multiple runs

• NanoStat: statistic summary report of reads or alignments

• NanoFilt: filtering and trimming of reads

• NanoLyse: removing contaminant reads (e.g. lambda control DNA) from fastq