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        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 2025-10-27, 07:11 PDT based on data in: /home/shared/16TB_HDD_01/sr320/github/project-lake-trout/analyses/08-nanoplot

        General Statistics

        Showing 1/1 rows and 1/7 columns.
        Sample NameMedian lengthMean lengthRead N50Median QualMean Qual# Reads (K)Total Bases (Mb)
        bc2068
        3778bp
        4224bp
        4541bp
        39.8
        30.2
        3287.6K
        13887.0Mb

        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 1/1 rows and 5/7 columns.
        Sample NameMedian lengthMean lengthRead N50Median QualMean Qual# Reads (K)Total Bases (Mb)
        bc2068
        3778bp
        4224bp
        4541bp
        39.8
        30.2
        3287.6K
        13887.0Mb

        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.