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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411
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        About MultiQC

        This report was generated using MultiQC, version 1.32

        Video: Using MultiQC Reports MultiQC homepage MultiQC documentation Source code Issue tracker

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        MultiQC is developed by Seqera.

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        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2025-11-01, 06:26 PDT based on data in: /home/shared/16TB_HDD_01/sr320/github/project-lake-trout/analyses/08-nanoplot

        General Statistics

        Showing 8/8 rows and 1/7 columns.
        Sample NameMedian lengthMean lengthRead N50Median QualMean Qual# Reads (K)Total Bases (Mb)
        bc2041
        6516bp
        7634bp
        8296bp
        38.8
        29.0
        3259.0K
        24879.4Mb
        bc2068
        3778bp
        4224bp
        4541bp
        39.8
        30.2
        3287.6K
        13887.0Mb
        bc2069
        6046bp
        6836bp
        7356bp
        38.9
        29.0
        1348.6K
        9219.5Mb
        bc2070
        5499bp
        6181bp
        6549bp
        39.2
        29.4
        3019.6K
        18663.5Mb
        bc2071
        5349bp
        6036bp
        6439bp
        39.3
        29.4
        3406.0K
        20559.9Mb
        bc2072
        5599bp
        6333bp
        6759bp
        39.2
        29.3
        2312.3K
        14643.5Mb
        bc2073
        5693bp
        6488bp
        6960bp
        39.1
        29.2
        3641.3K
        23624.5Mb
        bc2096
        5216bp
        6336bp
        7191bp
        38.8
        29.1
        5899.5K
        37377.0Mb

        NanoStat

        Reports various statistics for long read dataset in FASTQ, BAM, or albacore sequencing summary format (supports NanoPack; NanoPlot, NanoComp).https://github.com/wdecoster/nanostat; https://github.com/wdecoster/nanoplotDOI: 10.1093/bioinformatics/bty149

        Programs are part of the NanoPack family for summarising results of sequencing on Oxford Nanopore methods (MinION, PromethION etc.)

        Summary Statistics (FASTQ)

        Showing 8/8 rows and 5/7 columns.
        Sample NameMedian lengthMean lengthRead N50Median QualMean Qual# Reads (K)Total Bases (Mb)
        bc2041
        6516bp
        7634bp
        8296bp
        38.8
        29.0
        3259.0K
        24879.4Mb
        bc2068
        3778bp
        4224bp
        4541bp
        39.8
        30.2
        3287.6K
        13887.0Mb
        bc2069
        6046bp
        6836bp
        7356bp
        38.9
        29.0
        1348.6K
        9219.5Mb
        bc2070
        5499bp
        6181bp
        6549bp
        39.2
        29.4
        3019.6K
        18663.5Mb
        bc2071
        5349bp
        6036bp
        6439bp
        39.3
        29.4
        3406.0K
        20559.9Mb
        bc2072
        5599bp
        6333bp
        6759bp
        39.2
        29.3
        2312.3K
        14643.5Mb
        bc2073
        5693bp
        6488bp
        6960bp
        39.1
        29.2
        3641.3K
        23624.5Mb
        bc2096
        5216bp
        6336bp
        7191bp
        38.8
        29.1
        5899.5K
        37377.0Mb

        Reads by quality

        Read counts categorised by read quality (Phred score).

        Sequencing machines assign each generated read a quality score using the Phred scale. The phred score represents the liklelyhood that a given read contains errors. High quality reads have a high score.

        Created with MultiQC

        MultiQC v1.32 - Written by Phil Ewels, available on GitHub.

        This report uses Plotly, jQuery, jQuery UI, Bootstrap and FileSaver.js.