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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 1.7 (7d61ef5)

        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.

        Report generated on 2019-02-18, 17:43 based on data in: /pbtech_mounts/homes022/frd2007/ANGSD_2019/alignment_qc/multiqc

        General Statistics

        Showing 10/10 rows and 2/2 columns.
        Sample Name% AlignedM Aligned
        SNF2_1 | SNF2_1
        89.5%
        10.9
        SNF2_2 | SNF2_2
        88.3%
        9.0
        SNF2_3 | SNF2_3
        89.0%
        9.1
        SNF2_4 | SNF2_4
        88.8%
        11.3
        SNF2_5 | SNF2_5
        81.8%
        7.3
        WT_1 | WT_1
        85.7%
        6.0
        WT_2 | WT_2
        87.1%
        8.2
        WT_3 | WT_3
        85.3%
        6.7
        WT_4 | WT_4
        86.3%
        10.7
        WT_5 | WT_5
        85.3%
        8.3

        RSeQC

        RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput RNA-seq data.

        Read Distribution

        Read Distribution calculates how mapped reads are distributed over genome features.

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        Gene Body Coverage

        Gene Body Coverage calculates read coverage over gene bodies. This is used to check if reads coverage is uniform and if there is any 5' or 3' bias.

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        STAR

        STAR is an ultrafast universal RNA-seq aligner.

        Alignment Scores

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        MultiQC v1.7 (7d61ef5) - Written by Phil Ewels, available on GitHub.

        This report uses HighCharts, jQuery, jQuery UI, Bootstrap, FileSaver.js and clipboard.js.