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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 2017-05-24, 21:44 based on data in: /tmp/tmpWNBij6/job_working_directory/000/14/working/multiqc_WDir


        General Statistics

        Showing 6/6 rows and 2/2 columns.
        Sample Name% AssignedM Assigned
        70: TopHat on data 1, data 4, and data 3: accepted_hits
        70.8%
        0.3
        75: TopHat on data 1, data 6, and data 5: accepted_hits
        69.6%
        0.4
        80: TopHat on data 1, data 8, and data 7: accepted_hits
        71.8%
        0.4
        85: TopHat on data 1, data 10, and data 9: accepted_hits
        72.0%
        0.4
        90: TopHat on data 1, data 12, and data 11: accepted_hits
        71.3%
        0.4
        95: TopHat on data 1, data 14, and data 13: accepted_hits
        70.7%
        0.5

        featureCounts

        Subread featureCounts is a highly efficient general-purpose read summarization program that counts mapped reads for genomic features such as genes, exons, promoter, gene bodies, genomic bins and chromosomal locations.

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