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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 1.0

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/ewels/MultiQC

        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

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

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        Report generated on 2017-10-17, 08:57 based on data in: /projects/rcorbettprj2/TechD/costReductionLowInput


        General Statistics

        Showing 3/3 rows and 5/11 columns.
        Sample NameAvg. GCInsert Size≥ 30XCoverage% Aligned
        A36971_2_lanes_dupsFlagged
        41%
        432bp
        91.1%
        73.0X
        99.6%
        A79947
        98.9%
        A79947_stats
        41%
        363bp
        59.2%
        33.0X

        QualiMap

        QualiMap is a platform-independent application to facilitate the quality control of alignment sequencing data and its derivatives like feature counts.

        Coverage histogram

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        Cumulative coverage genome fraction

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        Insert size histogram

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        GC content distribution

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        Picard

        Picard is a set of Java command line tools for manipulating high-throughput sequencing data.

        GC Coverage Bias

        This plot shows bias in coverage across regions of the genome with varying GC content. A perfect library would be a flat line at y = 1.

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