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        Note that additional data was saved in multiqc_data when this report was generated.


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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.dev0

        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 2018-03-14, 08:03 based on data in: /Volumes/Serine/wd/18-03-14


        General Statistics

        Showing 39/39 rows and 3/5 columns.
        Sample Name% Dups% GCM Seqs
        10_32_S32_L001_R1_001
        2.4%
        25%
        0.6
        10_32_S32_L001_R2_001
        1.6%
        24%
        0.6
        11_37_S37_L001_R1_001
        0.9%
        24%
        0.7
        11_37_S37_L001_R2_001
        0.7%
        24%
        0.7
        12_38_S38_L001_R1_001
        1.0%
        25%
        0.9
        12_38_S38_L001_R2_001
        0.9%
        24%
        0.9
        13_33_S33_L001_R1_001
        2.4%
        25%
        0.6
        13_33_S33_L001_R2_001
        2.2%
        24%
        0.6
        14_34_S34_L001_R1_001
        1.7%
        25%
        0.7
        14_34_S34_L001_R2_001
        1.5%
        24%
        0.7
        15_39_S39_L001_R1_001
        1.0%
        25%
        0.7
        15_39_S39_L001_R2_001
        0.9%
        25%
        0.7
        16_40_S40_L001_R1_001
        2.0%
        25%
        0.8
        16_40_S40_L001_R2_001
        1.2%
        24%
        0.8
        17_9_S9_L001_R1_001
        4.1%
        33%
        0.4
        17_9_S9_L001_R2_001
        3.7%
        33%
        0.4
        18_10_S10_L001_R1_001
        0.9%
        22%
        0.5
        18_10_S10_L001_R2_001
        0.7%
        22%
        0.5
        19_7_S7_L001_R1_001
        0.6%
        21%
        0.4
        19_7_S7_L001_R2_001
        0.6%
        21%
        0.4
        1_25_S25_L001_R1_001
        12.7%
        32%
        0.5
        1_25_S25_L001_R2_001
        12.8%
        32%
        0.5
        20_8_S8_L001_R1_001
        0.8%
        25%
        0.3
        20_8_S8_L001_R2_001
        0.6%
        24%
        0.3
        2_26_S26_L001_R1_001
        10.5%
        34%
        0.2
        2_26_S26_L001_R2_001
        9.8%
        34%
        0.2
        3_27_S27_L001_R1_001
        10.9%
        39%
        0.2
        3_27_S27_L001_R2_001
        10.2%
        40%
        0.2
        4_28_S28_L001_R1_001
        6.4%
        29%
        0.3
        4_28_S28_L001_R2_001
        3.8%
        30%
        0.3
        5_35_S35_L001_R1_001
        1.5%
        22%
        0.0
        5_35_S35_L001_R2_001
        1.2%
        22%
        0.0
        6_36_S36_L001_R1_001
        5.5%
        23%
        0.0
        6_36_S36_L001_R2_001
        2.0%
        23%
        0.0
        7_29_S29_L001_R1_001
        13.2%
        24%
        0.6
        7_29_S29_L001_R2_001
        17.2%
        23%
        0.6
        8_30_S30_L001_R2_001
        15.0%
        24%
        0.7
        9_31_S31_L001_R1_001
        1.3%
        25%
        0.6
        9_31_S31_L001_R2_001
        1.2%
        24%
        0.6

        FastQC

        FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

        Sequence Quality Histograms

        The mean quality value across each base position in the read. See the FastQC help.

        loading..

        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality. See the FastQC help.

        loading..

        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called. See the FastQC help.

        Click a heatmap row to see a line plot for that dataset.

        rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content. See the FastQC help.

        loading..

        Per Base N Content

        The percentage of base calls at each position for which an N was called. See the FastQC help.

        loading..

        Sequence Length Distribution

        The distribution of fragment sizes (read lengths) found. See the FastQC help.

        loading..

        Sequence Duplication Levels

        The relative level of duplication found for every sequence. See the FastQC help.

        loading..

        Overrepresented sequences

        The total amount of overrepresented sequences found in each library. See the FastQC help for further information.

        loading..

        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. See the FastQC help. Only samples with ≥ 0.1% adapter contamination are shown.

        No samples found with any adapter contamination > 0.1%