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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, 12:49 based on data in:

        General Statistics

        Showing 65/65 rows and 5/6 columns.
        Sample NameM Reads Mapped% AssignedM Assigned% AlignedM Aligned
        G175_M10_G175_M10
        83.7%
        13.2
        G175_M10_sorted
        95.9%
        12.7
        G175_M10_statistics_for_all_accepted_reads
        29.4
        G175_M10_statistics_for_primary_reads
        27.5
        G175_M10_statistics_for_primary_unique_reads
        26.4
        G175_M11_G175_M11
        80.6%
        12.3
        G175_M11_sorted
        95.2%
        11.7
        G175_M11_statistics_for_all_accepted_reads
        27.8
        G175_M11_statistics_for_primary_reads
        25.7
        G175_M11_statistics_for_primary_unique_reads
        24.6
        G175_M12_G175_M12
        82.8%
        15.4
        G175_M12_sorted
        95.1%
        14.6
        G175_M12_statistics_for_all_accepted_reads
        34.9
        G175_M12_statistics_for_primary_reads
        32.2
        G175_M12_statistics_for_primary_unique_reads
        30.7
        G175_M13_G175_M13
        80.9%
        10.3
        G175_M13_sorted
        94.9%
        9.8
        G175_M13_statistics_for_all_accepted_reads
        23.4
        G175_M13_statistics_for_primary_reads
        21.6
        G175_M13_statistics_for_primary_unique_reads
        20.6
        G175_M1_G175_M1
        72.4%
        15.1
        G175_M1_sorted
        94.8%
        14.3
        G175_M1_statistics_for_all_accepted_reads
        35.3
        G175_M1_statistics_for_primary_reads
        31.7
        G175_M1_statistics_for_primary_unique_reads
        30.1
        G175_M2_G175_M2
        73.5%
        13.8
        G175_M2_sorted
        95.0%
        13.1
        G175_M2_statistics_for_all_accepted_reads
        32.1
        G175_M2_statistics_for_primary_reads
        29.0
        G175_M2_statistics_for_primary_unique_reads
        27.5
        G175_M3_G175_M3
        77.1%
        19.4
        G175_M3_sorted
        94.0%
        18.2
        G175_M3_statistics_for_all_accepted_reads
        44.3
        G175_M3_statistics_for_primary_reads
        40.6
        G175_M3_statistics_for_primary_unique_reads
        38.8
        G175_M4_G175_M4
        73.0%
        15.5
        G175_M4_sorted
        95.4%
        14.8
        G175_M4_statistics_for_all_accepted_reads
        37.0
        G175_M4_statistics_for_primary_reads
        32.9
        G175_M4_statistics_for_primary_unique_reads
        31.0
        G175_M5_G175_M5
        78.3%
        14.0
        G175_M5_sorted
        94.8%
        13.3
        G175_M5_statistics_for_all_accepted_reads
        32.4
        G175_M5_statistics_for_primary_reads
        29.4
        G175_M5_statistics_for_primary_unique_reads
        28.0
        G175_M6_G175_M6
        77.3%
        14.0
        G175_M6_sorted
        95.3%
        13.3
        G175_M6_statistics_for_all_accepted_reads
        32.4
        G175_M6_statistics_for_primary_reads
        29.4
        G175_M6_statistics_for_primary_unique_reads
        27.9
        G175_M7_G175_M7
        77.8%
        14.8
        G175_M7_sorted
        95.8%
        14.1
        G175_M7_statistics_for_all_accepted_reads
        32.9
        G175_M7_statistics_for_primary_reads
        30.7
        G175_M7_statistics_for_primary_unique_reads
        29.5
        G175_M8_G175_M8
        81.1%
        14.6
        G175_M8_sorted
        95.7%
        14.0
        G175_M8_statistics_for_all_accepted_reads
        32.5
        G175_M8_statistics_for_primary_reads
        30.4
        G175_M8_statistics_for_primary_unique_reads
        29.3
        G175_M9_G175_M9
        74.6%
        14.0
        G175_M9_sorted
        95.4%
        13.4
        G175_M9_statistics_for_all_accepted_reads
        31.7
        G175_M9_statistics_for_primary_reads
        29.2
        G175_M9_statistics_for_primary_unique_reads
        28.0

        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.