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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 1.11

        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 2024-12-11, 13:47 based on data in:

        General Statistics

        Showing 83/83 rows and 3/4 columns.
        Sample NameM Reads Mapped% AssignedM Assigned
        G216_M01_sorted
        93.7%
        8.3
        G216_M02_sorted
        95.7%
        7.2
        G216_M03_sorted
        95.1%
        11.6
        G216_M04_sorted
        95.3%
        5.8
        G216_M05_sorted
        95.3%
        7.9
        G216_M06_sorted
        95.9%
        8.9
        G216_M07_sorted
        94.4%
        9.3
        G216_M08_sorted
        95.1%
        9.4
        G216_M09_sorted
        94.5%
        13.9
        G216_M10_sorted
        96.0%
        7.3
        G216_M11_sorted
        96.0%
        7.2
        G216_M12_sorted
        94.8%
        9.6
        G216_M13_sorted
        95.0%
        8.5
        G216_M14_sorted
        94.9%
        8.2
        G216_M15_sorted
        95.1%
        11.6
        G216_M16_sorted
        95.0%
        9.6
        G216_M17_sorted
        95.3%
        8.7
        G216_M18_sorted
        94.6%
        11.1
        G216_M19_sorted
        95.4%
        10.5
        G216_M20_sorted
        95.4%
        8.5
        G216_M21_sorted
        95.5%
        11.1
        G216_M22_sorted
        95.8%
        9.0
        G216_M23_sorted
        94.7%
        7.3
        G216_M24_sorted
        93.7%
        7.3
        G216_M25_sorted
        96.2%
        10.1
        G216_M26_sorted
        94.8%
        7.9
        G216_M27_sorted
        95.2%
        9.2
        G216_M28_sorted
        95.2%
        8.8
        G216_M29_sorted
        95.7%
        7.3
        G216_M30_sorted
        94.6%
        9.3
        G216_M31_sorted
        95.4%
        11.1
        G216_M32_sorted
        94.4%
        20.0
        G216_M33_sorted
        95.1%
        10.2
        G216_M34_sorted
        95.2%
        6.7
        G216_M36_sorted
        95.3%
        7.6
        G216_M37_sorted
        94.4%
        9.6
        G216_M38_sorted
        94.5%
        9.7
        G216_M39_sorted
        94.3%
        7.8
        G216_M40_sorted
        94.7%
        8.6
        G216_M41_sorted
        94.8%
        8.8
        G216_M42_sorted
        96.1%
        7.7
        G216_M43_sorted
        95.1%
        11.2
        G216_M44_sorted
        94.8%
        10.5
        G216_M45_sorted
        94.2%
        8.6
        G216_M46_sorted
        96.1%
        6.1
        G216_M47_sorted
        96.2%
        5.9
        G216_M48_sorted
        94.7%
        7.2
        G216_M49_sorted
        94.8%
        6.9
        G216_M50_sorted
        95.1%
        7.1
        G216_M51_sorted
        94.6%
        9.4
        G216_M52_sorted
        94.3%
        8.1
        G216_M53_sorted
        95.5%
        5.8
        G216_M54_sorted
        95.1%
        7.9
        G216_M55_sorted
        95.3%
        7.9
        G216_M56_sorted
        94.9%
        8.2
        G216_M57_sorted
        94.8%
        10.1
        G216_M58_sorted
        95.2%
        5.7
        G216_M59_sorted
        96.1%
        8.8
        G216_M61_sorted
        94.2%
        7.6
        G216_M62_sorted
        94.4%
        5.8
        G216_M63_sorted
        95.5%
        9.5
        G216_M64_sorted
        95.1%
        6.6
        G216_M65_sorted
        95.0%
        11.1
        G216_M66_sorted
        94.5%
        9.4
        G216_M67_sorted
        94.8%
        8.2
        G216_M68_sorted
        94.4%
        11.4
        G216_M69_sorted
        94.6%
        8.9
        G216_M70_sorted
        95.2%
        8.0
        G216_M71_sorted
        95.6%
        17.9
        G216_M72_sorted
        92.9%
        8.4
        G221_M69_sorted
        93.3%
        5.8
        G221_M70_sorted
        93.9%
        6.7
        G221_M71_sorted
        93.6%
        7.4
        G221_M72_sorted
        94.7%
        5.7
        G221_M73_sorted
        93.8%
        17.4
        G221_M74_sorted
        92.8%
        11.8
        G221_M75_sorted
        93.8%
        17.2
        G221_M76_sorted
        93.5%
        6.7
        G221_M77_sorted
        94.3%
        6.4
        G221_M78_sorted
        94.3%
        7.1
        G221_M79_sorted
        94.4%
        6.7
        G221_M80_sorted
        94.7%
        6.7
        statistics_for_primary_unique_reads
        16.7

        RSeQC

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

        Infer experiment

        Infer experiment counts the percentage of reads and read pairs that match the strandedness of overlapping transcripts. It can be used to infer whether RNA-seq library preps are stranded (sense or antisense).

        loading..

        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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        Samtools

        Samtools is a suite of programs for interacting with high-throughput sequencing data.

        Samtools Flagstat

        This module parses the output from samtools flagstat. All numbers in millions.

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        MultiQC v1.11 - Written by Phil Ewels, available on GitHub.

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