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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 2024-07-23, 12:55 based on data in:

        General Statistics

        Showing 65/65 rows and 5/6 columns.
        Sample NameM Reads Mapped% AssignedM Assigned% AlignedM Aligned
        G176_M10_G176_M10
        77.6%
        12.7
        G176_M10_sorted
        94.6%
        12.1
        G176_M10_statistics_for_all_accepted_reads
        29.1
        G176_M10_statistics_for_primary_reads
        26.8
        G176_M10_statistics_for_primary_unique_reads
        25.5
        G176_M11_G176_M11
        79.1%
        15.2
        G176_M11_sorted
        94.1%
        14.3
        G176_M11_statistics_for_all_accepted_reads
        34.7
        G176_M11_statistics_for_primary_reads
        32.1
        G176_M11_statistics_for_primary_unique_reads
        30.4
        G176_M12_G176_M12
        80.3%
        14.9
        G176_M12_sorted
        95.7%
        14.3
        G176_M12_statistics_for_all_accepted_reads
        33.6
        G176_M12_statistics_for_primary_reads
        31.2
        G176_M12_statistics_for_primary_unique_reads
        29.8
        G176_M13_G176_M13
        80.3%
        13.7
        G176_M13_sorted
        95.2%
        13.0
        G176_M13_statistics_for_all_accepted_reads
        30.7
        G176_M13_statistics_for_primary_reads
        28.5
        G176_M13_statistics_for_primary_unique_reads
        27.3
        G176_M1_G176_M1
        71.5%
        14.1
        G176_M1_sorted
        95.3%
        13.5
        G176_M1_statistics_for_all_accepted_reads
        33.2
        G176_M1_statistics_for_primary_reads
        29.8
        G176_M1_statistics_for_primary_unique_reads
        28.2
        G176_M2_G176_M2
        74.2%
        15.3
        G176_M2_sorted
        95.6%
        14.6
        G176_M2_statistics_for_all_accepted_reads
        35.8
        G176_M2_statistics_for_primary_reads
        32.3
        G176_M2_statistics_for_primary_unique_reads
        30.6
        G176_M3_G176_M3
        76.2%
        11.7
        G176_M3_sorted
        95.6%
        11.2
        G176_M3_statistics_for_all_accepted_reads
        26.7
        G176_M3_statistics_for_primary_reads
        24.6
        G176_M3_statistics_for_primary_unique_reads
        23.4
        G176_M4_G176_M4
        75.1%
        15.1
        G176_M4_sorted
        96.2%
        14.5
        G176_M4_statistics_for_all_accepted_reads
        35.6
        G176_M4_statistics_for_primary_reads
        31.9
        G176_M4_statistics_for_primary_unique_reads
        30.2
        G176_M5_G176_M5
        78.2%
        21.1
        G176_M5_sorted
        96.1%
        20.3
        G176_M5_statistics_for_all_accepted_reads
        49.2
        G176_M5_statistics_for_primary_reads
        44.6
        G176_M5_statistics_for_primary_unique_reads
        42.3
        G176_M6_G176_M6
        77.6%
        11.7
        G176_M6_sorted
        95.8%
        11.2
        G176_M6_statistics_for_all_accepted_reads
        27.1
        G176_M6_statistics_for_primary_reads
        24.7
        G176_M6_statistics_for_primary_unique_reads
        23.5
        G176_M7_G176_M7
        78.8%
        21.8
        G176_M7_sorted
        95.6%
        20.8
        G176_M7_statistics_for_all_accepted_reads
        47.6
        G176_M7_statistics_for_primary_reads
        45.0
        G176_M7_statistics_for_primary_unique_reads
        43.5
        G176_M8_G176_M8
        82.0%
        16.9
        G176_M8_sorted
        95.7%
        16.2
        G176_M8_statistics_for_all_accepted_reads
        37.6
        G176_M8_statistics_for_primary_reads
        35.3
        G176_M8_statistics_for_primary_unique_reads
        33.9
        G176_M9_G176_M9
        76.4%
        9.5
        G176_M9_sorted
        95.8%
        9.1
        G176_M9_statistics_for_all_accepted_reads
        21.6
        G176_M9_statistics_for_primary_reads
        19.8
        G176_M9_statistics_for_primary_unique_reads
        18.9

        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).

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        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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        STAR

        STAR is an ultrafast universal RNA-seq aligner.

        Alignment Scores

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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.