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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 1.9

        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 2021-03-03, 13:42 based on data in: /home/cri.camres.org/sawle01/Documents/training/Bulk_RNAseq_Course_2021/Course_Materials/metrics


        General Statistics

        Showing 13/13 rows and 5/6 columns.
        Sample Name% rRNA% mRNA% AlignedInsert Size% Dups
        SRR7657872
        %
        88.2%
        93%
        253 bp
        22.1%
        SRR7657873
        %
        89.8%
        93%
        259 bp
        24.9%
        SRR7657874
        %
        88.5%
        83%
        264 bp
        21.8%
        SRR7657875
        %
        94.1%
        94%
        259 bp
        24.9%
        SRR7657876
        %
        92.1%
        94%
        258 bp
        25.5%
        SRR7657877
        %
        89.2%
        94%
        256 bp
        24.3%
        SRR7657878
        %
        91.7%
        94%
        263 bp
        25.1%
        SRR7657879
        %
        89.9%
        94%
        251 bp
        24.5%
        SRR7657880
        %
        89.0%
        94%
        261 bp
        22.6%
        SRR7657881
        %
        88.5%
        94%
        262 bp
        24.2%
        SRR7657882
        %
        89.4%
        94%
        261 bp
        29.0%
        SRR7657883
        %
        91.6%
        95%
        259 bp
        24.1%
        SRR7657893
        %
        88.6%
        43%
        195 bp
        23.5%

        Picard

        Picard is a set of Java command line tools for manipulating high-throughput sequencing data.

        Alignment Summary

        Please note that Picard's read counts are divided by two for paired-end data.

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        Insert Size

        Plot shows the number of reads at a given insert size. Reads with different orientations are summed.

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        Mark Duplicates

        Number of reads, categorised by duplication state. Pair counts are doubled - see help text for details.

        The table in the Picard metrics file contains some columns referring read pairs and some referring to single reads.

        To make the numbers in this plot sum correctly, values referring to pairs are doubled according to the scheme below:

        • READS_IN_DUPLICATE_PAIRS = 2 * READ_PAIR_DUPLICATES
        • READS_IN_UNIQUE_PAIRS = 2 * (READ_PAIRS_EXAMINED - READ_PAIR_DUPLICATES)
        • READS_IN_UNIQUE_UNPAIRED = UNPAIRED_READS_EXAMINED - UNPAIRED_READ_DUPLICATES
        • READS_IN_DUPLICATE_PAIRS_OPTICAL = 2 * READ_PAIR_OPTICAL_DUPLICATES
        • READS_IN_DUPLICATE_PAIRS_NONOPTICAL = READS_IN_DUPLICATE_PAIRS - READS_IN_DUPLICATE_PAIRS_OPTICAL
        • READS_IN_DUPLICATE_UNPAIRED = UNPAIRED_READ_DUPLICATES
        • READS_UNMAPPED = UNMAPPED_READS
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        RnaSeqMetrics Assignment

        Number of bases in primary alignments that align to regions in the reference genome.

        Picard was run without an rRNA annotation file 12 samples, therefore the ribosomal assignment is not available. To correct, rerun with the RIBOSOMAL_INTERVALS parameter, as documented here.

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        Gene Coverage

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