Highlight Samples

Regex mode off

    Rename Samples

    Click here for bulk input.

    Paste two columns of a tab-delimited table here (eg. from Excel).

    First column should be the old name, second column the new name.

    Regex mode off

      Show / Hide Samples

      Regex mode off

        Export Plots

        px
        px
        X

        Download the raw data used to create the plots in this report below:

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

        Choose Plots

        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

        Save Settings

        You can save the toolbox settings for this report to the browser.

        Load Settings

        Choose a saved report profile from the dropdown box below:

        About MultiQC

        This report was generated using MultiQC, version 0.9

        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 2019-08-09, 11:08 based on data in: /home/srlab/GitHub/Shelly_Pgenerosa/multiqc/FASTQC

        General Statistics

        Showing 88/88 rows and 4/5 columns.
        Sample Name% Dups% GCLengthM Seqs
        16C_26psu_1_S13_L001_R1_001_val_1
        17.3%
        27%
        112
        22.1
        16C_26psu_1_S13_L001_R2_001_val_2
        17.2%
        27%
        112
        22.1
        16C_26psu_1_S13_L002_R1_001_val_1
        16.8%
        27%
        112
        22.0
        16C_26psu_1_S13_L002_R2_001_val_2
        16.6%
        27%
        112
        22.0
        16C_26psu_2_S14_L001_R1_001_val_1
        20.0%
        27%
        114
        17.2
        16C_26psu_2_S14_L001_R2_001_val_2
        19.5%
        27%
        114
        17.2
        16C_26psu_2_S14_L002_R1_001_val_1
        19.5%
        27%
        113
        17.1
        16C_26psu_2_S14_L002_R2_001_val_2
        19.0%
        27%
        114
        17.1
        16C_26psu_3_S15_L001_R1_001_val_1
        25.5%
        28%
        115
        14.6
        16C_26psu_3_S15_L001_R2_001_val_2
        24.2%
        28%
        115
        14.6
        16C_26psu_3_S15_L002_R1_001_val_1
        25.0%
        28%
        115
        14.6
        16C_26psu_3_S15_L002_R2_001_val_2
        23.7%
        28%
        115
        14.6
        16C_26psu_4_S16_L001_R1_001_val_1
        16.9%
        27%
        110
        17.2
        16C_26psu_4_S16_L001_R2_001_val_2
        16.7%
        27%
        110
        17.2
        16C_26psu_4_S16_L002_R1_001_val_1
        16.5%
        27%
        110
        17.2
        16C_26psu_4_S16_L002_R2_001_val_2
        16.3%
        28%
        110
        17.2
        16C_32psu_1_S1_L001_R1_001_val_1
        18.2%
        28%
        104
        19.6
        16C_32psu_1_S1_L001_R2_001_val_2
        18.0%
        28%
        104
        19.6
        16C_32psu_1_S1_L002_R1_001_val_1
        17.8%
        28%
        104
        19.5
        16C_32psu_1_S1_L002_R2_001_val_2
        17.6%
        28%
        104
        19.5
        16C_32psu_2_S2_L001_R1_001_val_1
        19.4%
        28%
        105
        17.7
        16C_32psu_2_S2_L001_R2_001_val_2
        19.2%
        28%
        106
        17.7
        16C_32psu_2_S2_L002_R1_001_val_1
        18.5%
        28%
        105
        17.7
        16C_32psu_2_S2_L002_R2_001_val_2
        18.5%
        28%
        106
        17.7
        16C_32psu_3_S3_L001_R1_001_val_1
        15.1%
        28%
        102
        13.7
        16C_32psu_3_S3_L001_R2_001_val_2
        14.7%
        28%
        102
        13.7
        16C_32psu_3_S3_L002_R1_001_val_1
        14.7%
        28%
        102
        13.6
        16C_32psu_3_S3_L002_R2_001_val_2
        14.3%
        28%
        102
        13.6
        16C_32psu_4_S4_L001_R1_001_val_1
        18.6%
        26%
        120
        15.7
        16C_32psu_4_S4_L001_R2_001_val_2
        17.6%
        26%
        120
        15.7
        16C_32psu_4_S4_L002_R1_001_val_1
        18.0%
        26%
        120
        15.6
        16C_32psu_4_S4_L002_R2_001_val_2
        17.1%
        26%
        120
        15.6
        8C_26psu_1_S9_L001_R1_001_val_1
        16.7%
        27%
        113
        18.1
        8C_26psu_1_S9_L001_R2_001_val_2
        16.3%
        27%
        114
        18.1
        8C_26psu_1_S9_L002_R1_001_val_1
        16.0%
        27%
        113
        18.0
        8C_26psu_1_S9_L002_R2_001_val_2
        15.6%
        27%
        113
        18.0
        8C_26psu_2_S10_L001_R1_001_val_1
        19.0%
        27%
        109
        18.4
        8C_26psu_2_S10_L001_R2_001_val_2
        18.7%
        27%
        109
        18.4
        8C_26psu_2_S10_L002_R1_001_val_1
        18.4%
        27%
        109
        18.3
        8C_26psu_2_S10_L002_R2_001_val_2
        18.1%
        27%
        109
        18.3
        8C_26psu_3_S11_L001_R1_001_val_1
        18.7%
        28%
        101
        17.2
        8C_26psu_3_S11_L001_R2_001_val_2
        18.2%
        29%
        101
        17.2
        8C_26psu_3_S11_L002_R1_001_val_1
        18.4%
        28%
        101
        17.1
        8C_26psu_3_S11_L002_R2_001_val_2
        17.9%
        29%
        101
        17.1
        8C_26psu_4_S12_L001_R1_001_val_1
        32.3%
        25%
        120
        12.6
        8C_26psu_4_S12_L001_R2_001_val_2
        30.7%
        26%
        120
        12.6
        8C_26psu_4_S12_L002_R1_001_val_1
        31.4%
        26%
        119
        12.4
        8C_26psu_4_S12_L002_R2_001_val_2
        29.8%
        26%
        120
        12.4
        8C_32psu_1_S5_L001_R1_001_val_1
        15.9%
        29%
        94
        14.0
        8C_32psu_1_S5_L001_R2_001_val_2
        16.0%
        29%
        94
        14.0
        8C_32psu_1_S5_L002_R1_001_val_1
        15.5%
        29%
        94
        13.9
        8C_32psu_1_S5_L002_R2_001_val_2
        15.3%
        29%
        94
        13.9
        8C_32psu_2_S6_L001_R1_001_val_1
        14.9%
        27%
        110
        12.9
        8C_32psu_2_S6_L001_R2_001_val_2
        14.9%
        27%
        110
        12.9
        8C_32psu_2_S6_L002_R1_001_val_1
        14.3%
        27%
        110
        12.8
        8C_32psu_2_S6_L002_R2_001_val_2
        14.2%
        27%
        110
        12.8
        8C_32psu_3_S7_L001_R1_001_val_1
        16.2%
        28%
        105
        14.1
        8C_32psu_3_S7_L001_R2_001_val_2
        16.2%
        28%
        105
        14.1
        8C_32psu_3_S7_L002_R1_001_val_1
        15.9%
        28%
        105
        14.1
        8C_32psu_3_S7_L002_R2_001_val_2
        15.8%
        28%
        105
        14.1
        8C_32psu_4_S8_L001_R1_001_val_1
        18.6%
        26%
        116
        14.7
        8C_32psu_4_S8_L001_R2_001_val_2
        17.7%
        26%
        116
        14.7
        8C_32psu_4_S8_L002_R1_001_val_1
        18.0%
        26%
        116
        14.6
        8C_32psu_4_S8_L002_R2_001_val_2
        17.2%
        26%
        116
        14.6
        CTRL_16C_26psu_1_S19_L001_R1_001_val_1
        19.5%
        27%
        112
        18.5
        CTRL_16C_26psu_1_S19_L001_R2_001_val_2
        18.9%
        27%
        113
        18.5
        CTRL_16C_26psu_1_S19_L002_R1_001_val_1
        18.9%
        27%
        112
        18.5
        CTRL_16C_26psu_1_S19_L002_R2_001_val_2
        18.4%
        27%
        112
        18.5
        CTRL_16C_26psu_2_S21_L001_R1_001_val_1
        15.7%
        29%
        101
        13.4
        CTRL_16C_26psu_2_S21_L001_R2_001_val_2
        15.3%
        29%
        102
        13.4
        CTRL_16C_26psu_2_S21_L002_R1_001_val_1
        15.3%
        29%
        101
        13.4
        CTRL_16C_26psu_2_S21_L002_R2_001_val_2
        14.9%
        29%
        102
        13.4
        CTRL_8C_26psu_1_S17_L001_R1_001_val_1
        20.8%
        25%
        114
        13.7
        CTRL_8C_26psu_1_S17_L001_R2_001_val_2
        20.5%
        25%
        115
        13.7
        CTRL_8C_26psu_1_S17_L002_R1_001_val_1
        20.1%
        25%
        114
        13.6
        CTRL_8C_26psu_1_S17_L002_R2_001_val_2
        19.7%
        25%
        115
        13.6
        CTRL_8C_26psu_2_S18_L001_R1_001_val_1
        19.8%
        29%
        93
        16.9
        CTRL_8C_26psu_2_S18_L001_R2_001_val_2
        19.7%
        30%
        94
        16.9
        CTRL_8C_26psu_2_S18_L002_R1_001_val_1
        19.2%
        29%
        93
        16.9
        CTRL_8C_26psu_2_S18_L002_R2_001_val_2
        19.0%
        30%
        94
        16.9
        Sealice_F1_S20_L001_R1_001_val_1
        37.1%
        21%
        122
        113.3
        Sealice_F1_S20_L001_R2_001_val_2
        36.5%
        21%
        122
        113.3
        Sealice_F1_S20_L002_R1_001_val_1
        36.4%
        21%
        122
        112.5
        Sealice_F1_S20_L002_R2_001_val_2
        35.3%
        21%
        122
        112.5
        Sealice_F2_S22_L001_R1_001_val_1
        30.5%
        22%
        121
        82.1
        Sealice_F2_S22_L001_R2_001_val_2
        28.9%
        22%
        121
        82.1
        Sealice_F2_S22_L002_R1_001_val_1
        30.0%
        22%
        120
        81.6
        Sealice_F2_S22_L002_R2_001_val_2
        28.2%
        22%
        121
        81.6

        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.

        88 samples had less than 1% of reads made up of overrepresented sequences

        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%

        MultiQC v0.9 - Written by Phil Ewels, available on GitHub.

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