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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 2020-05-28, 15:05 based on data in: /beegfs/mk5636/logs/html/000000000-J649D/1


        General Statistics

        Showing 106/106 rows and 3/5 columns.
        Sample Name% Dups% GCM Seqs
        000000000-J649D_l01_n01_CV-54-A
        83.9%
        36%
        0.1
        000000000-J649D_l01_n01_CV-54-B
        88.5%
        39%
        0.2
        000000000-J649D_l01_n01_CV-55-A
        85.0%
        36%
        0.2
        000000000-J649D_l01_n01_CV-55-B
        89.0%
        39%
        0.2
        000000000-J649D_l01_n01_CV-56-A
        64.5%
        38%
        0.0
        000000000-J649D_l01_n01_CV-56-B
        90.1%
        39%
        0.3
        000000000-J649D_l01_n01_CV-57-A
        88.3%
        38%
        0.3
        000000000-J649D_l01_n01_CV-57-B
        89.5%
        39%
        0.2
        000000000-J649D_l01_n01_CV-58-A
        1.9%
        38%
        0.0
        000000000-J649D_l01_n01_CV-58-B
        86.9%
        40%
        0.1
        000000000-J649D_l01_n01_CV-59-A
        77.4%
        38%
        0.1
        000000000-J649D_l01_n01_CV-59-B
        88.9%
        39%
        0.2
        000000000-J649D_l01_n01_CV-60-A
        89.4%
        37%
        0.2
        000000000-J649D_l01_n01_CV-60-B
        88.5%
        40%
        0.2
        000000000-J649D_l01_n01_CV-61-A
        87.3%
        38%
        0.2
        000000000-J649D_l01_n01_CV-61-B
        89.4%
        40%
        0.2
        000000000-J649D_l01_n01_CV-62-A
        89.0%
        47%
        0.2
        000000000-J649D_l01_n01_CV-62-B
        76.4%
        43%
        0.0
        000000000-J649D_l01_n01_CV-63-A
        89.8%
        37%
        0.2
        000000000-J649D_l01_n01_CV-63-B
        89.4%
        40%
        0.2
        000000000-J649D_l01_n01_CV-64-A
        87.8%
        44%
        0.2
        000000000-J649D_l01_n01_CV-64-B
        94.9%
        49%
        0.2
        000000000-J649D_l01_n01_CV-65-A
        87.0%
        41%
        0.2
        000000000-J649D_l01_n01_CV-65-B
        1.3%
        40%
        0.0
        000000000-J649D_l01_n01_CV-66-A
        75.7%
        45%
        0.1
        000000000-J649D_l01_n01_CV-66-B
        62.4%
        45%
        0.1
        000000000-J649D_l01_n01_CV-67-A
        85.9%
        38%
        0.2
        000000000-J649D_l01_n01_CV-67-B
        86.4%
        41%
        0.1
        000000000-J649D_l01_n01_CV-68-A
        87.3%
        37%
        0.2
        000000000-J649D_l01_n01_CV-68-B
        87.4%
        41%
        0.3
        000000000-J649D_l01_n01_CV-69-A
        89.3%
        39%
        0.2
        000000000-J649D_l01_n01_CV-69-B
        87.0%
        39%
        0.1
        000000000-J649D_l01_n01_CV-70-A
        57.1%
        49%
        0.1
        000000000-J649D_l01_n01_CV-70-B
        59.1%
        43%
        0.0
        000000000-J649D_l01_n01_CV-71
        84.0%
        41%
        0.1
        000000000-J649D_l01_n01_CV-72
        88.1%
        37%
        0.3
        000000000-J649D_l01_n01_CV-73
        87.9%
        35%
        0.2
        000000000-J649D_l01_n01_CV-74
        88.4%
        37%
        0.2
        000000000-J649D_l01_n01_CV-75
        91.4%
        37%
        0.4
        000000000-J649D_l01_n01_CV-76
        85.9%
        38%
        0.2
        000000000-J649D_l01_n01_CV-77
        90.8%
        35%
        0.3
        000000000-J649D_l01_n01_CV-78
        86.8%
        37%
        0.2
        000000000-J649D_l01_n01_CV-79
        85.3%
        39%
        0.2
        000000000-J649D_l01_n01_CV-80
        89.5%
        39%
        0.2
        000000000-J649D_l01_n01_CV-81
        75.7%
        38%
        0.1
        000000000-J649D_l01_n01_CV-82
        86.3%
        38%
        0.2
        000000000-J649D_l01_n01_CV-83
        83.6%
        40%
        0.1
        000000000-J649D_l01_n01_CV-84
        88.8%
        38%
        0.3
        000000000-J649D_l01_n01_CV-85
        90.2%
        36%
        0.2
        000000000-J649D_l01_n01_CV-86
        88.2%
        37%
        0.2
        000000000-J649D_l01_n01_CV-87
        79.7%
        39%
        0.1
        000000000-J649D_l01_n01_CV-88
        87.0%
        40%
        0.2
        000000000-J649D_l01_n01_undetermined
        91.0%
        45%
        1.5
        000000000-J649D_l01_n02_CV-54-A
        83.0%
        36%
        0.1
        000000000-J649D_l01_n02_CV-54-B
        88.3%
        39%
        0.2
        000000000-J649D_l01_n02_CV-55-A
        84.2%
        36%
        0.2
        000000000-J649D_l01_n02_CV-55-B
        88.0%
        39%
        0.2
        000000000-J649D_l01_n02_CV-56-A
        63.0%
        38%
        0.0
        000000000-J649D_l01_n02_CV-56-B
        89.5%
        39%
        0.3
        000000000-J649D_l01_n02_CV-57-A
        88.1%
        38%
        0.3
        000000000-J649D_l01_n02_CV-57-B
        88.5%
        39%
        0.2
        000000000-J649D_l01_n02_CV-58-A
        0.0%
        37%
        0.0
        000000000-J649D_l01_n02_CV-58-B
        87.2%
        39%
        0.1
        000000000-J649D_l01_n02_CV-59-A
        78.5%
        38%
        0.1
        000000000-J649D_l01_n02_CV-59-B
        87.7%
        39%
        0.2
        000000000-J649D_l01_n02_CV-60-A
        89.1%
        37%
        0.2
        000000000-J649D_l01_n02_CV-60-B
        87.7%
        40%
        0.2
        000000000-J649D_l01_n02_CV-61-A
        87.0%
        38%
        0.2
        000000000-J649D_l01_n02_CV-61-B
        90.0%
        40%
        0.2
        000000000-J649D_l01_n02_CV-62-A
        88.4%
        47%
        0.2
        000000000-J649D_l01_n02_CV-62-B
        76.1%
        43%
        0.0
        000000000-J649D_l01_n02_CV-63-A
        89.7%
        37%
        0.2
        000000000-J649D_l01_n02_CV-63-B
        88.6%
        40%
        0.2
        000000000-J649D_l01_n02_CV-64-A
        87.9%
        44%
        0.2
        000000000-J649D_l01_n02_CV-64-B
        94.7%
        49%
        0.2
        000000000-J649D_l01_n02_CV-65-A
        87.2%
        41%
        0.2
        000000000-J649D_l01_n02_CV-65-B
        1.7%
        39%
        0.0
        000000000-J649D_l01_n02_CV-66-A
        76.1%
        45%
        0.1
        000000000-J649D_l01_n02_CV-66-B
        62.9%
        45%
        0.1
        000000000-J649D_l01_n02_CV-67-A
        86.9%
        38%
        0.2
        000000000-J649D_l01_n02_CV-67-B
        85.7%
        41%
        0.1
        000000000-J649D_l01_n02_CV-68-A
        87.4%
        37%
        0.2
        000000000-J649D_l01_n02_CV-68-B
        86.7%
        41%
        0.3
        000000000-J649D_l01_n02_CV-69-A
        89.4%
        39%
        0.2
        000000000-J649D_l01_n02_CV-69-B
        85.9%
        39%
        0.1
        000000000-J649D_l01_n02_CV-70-A
        55.2%
        50%
        0.1
        000000000-J649D_l01_n02_CV-70-B
        57.7%
        43%
        0.0
        000000000-J649D_l01_n02_CV-71
        81.7%
        41%
        0.1
        000000000-J649D_l01_n02_CV-72
        87.5%
        37%
        0.3
        000000000-J649D_l01_n02_CV-73
        87.0%
        35%
        0.2
        000000000-J649D_l01_n02_CV-74
        88.0%
        37%
        0.2
        000000000-J649D_l01_n02_CV-75
        91.5%
        37%
        0.4
        000000000-J649D_l01_n02_CV-76
        87.0%
        38%
        0.2
        000000000-J649D_l01_n02_CV-77
        89.8%
        35%
        0.3
        000000000-J649D_l01_n02_CV-78
        86.0%
        37%
        0.2
        000000000-J649D_l01_n02_CV-79
        83.1%
        39%
        0.2
        000000000-J649D_l01_n02_CV-80
        88.7%
        39%
        0.2
        000000000-J649D_l01_n02_CV-81
        73.5%
        38%
        0.1
        000000000-J649D_l01_n02_CV-82
        86.8%
        38%
        0.2
        000000000-J649D_l01_n02_CV-83
        82.8%
        39%
        0.1
        000000000-J649D_l01_n02_CV-84
        87.7%
        38%
        0.3
        000000000-J649D_l01_n02_CV-85
        89.3%
        36%
        0.2
        000000000-J649D_l01_n02_CV-86
        87.9%
        37%
        0.2
        000000000-J649D_l01_n02_CV-87
        78.8%
        39%
        0.1
        000000000-J649D_l01_n02_CV-88
        86.1%
        40%
        0.2
        000000000-J649D_l01_n02_undetermined
        82.8%
        44%
        1.5

        Lane 1 Demultiplexing Report

        Lane 1 Demultiplexing Report
        Total Read Count: Total number of PF (Passing Filter) reads in this library.
        Portion: The proportion of reads that represent the individual library in the entire Library Pool

        Showing 53/53 rows and 2/2 columns.
        Sample NameTotal Read CountPortion (%)
        undetermined_library
        1,504,834
        14.5
        CV-54-A
        132,064
        1.3
        CV-55-A
        156,043
        1.5
        CV-56-A
        21,443
        0.2
        CV-57-A
        278,771
        2.7
        CV-58-A
        105.0
        0.0
        CV-59-A
        66,248
        0.6
        CV-60-A
        239,662
        2.3
        CV-61-A
        176,859
        1.7
        CV-62-A
        192,301
        1.9
        CV-63-A
        243,303
        2.3
        CV-64-A
        152,546
        1.5
        CV-65-A
        210,659
        2.0
        CV-66-A
        134,788
        1.3
        CV-67-A
        218,131
        2.1
        CV-68-A
        235,123
        2.3
        CV-69-A
        178,626
        1.7
        CV-70-A
        64,288
        0.6
        CV-54-B
        208,983
        2.0
        CV-55-B
        197,569
        1.9
        CV-56-B
        259,852
        2.5
        CV-57-B
        215,497
        2.1
        CV-58-B
        143,460
        1.4
        CV-59-B
        188,215
        1.8
        CV-60-B
        189,120
        1.8
        CV-61-B
        238,602
        2.3
        CV-62-B
        44,527
        0.4
        CV-63-B
        195,936
        1.9
        CV-64-B
        189,990
        1.8
        CV-65-B
        236.0
        0.0
        CV-66-B
        73,237
        0.7
        CV-67-B
        102,531
        1.0
        CV-68-B
        303,172
        2.9
        CV-69-B
        119,642
        1.2
        CV-70-B
        42,777
        0.4
        CV-71
        133,524
        1.3
        CV-72
        287,052
        2.8
        CV-73
        205,971
        2.0
        CV-74
        159,892
        1.5
        CV-75
        394,992
        3.8
        CV-76
        161,195
        1.6
        CV-77
        301,113
        2.9
        CV-78
        178,877
        1.7
        CV-79
        153,280
        1.5
        CV-80
        216,151
        2.1
        CV-81
        56,560
        0.5
        CV-82
        194,438
        1.9
        CV-83
        72,713
        0.7
        CV-84
        265,391
        2.6
        CV-85
        235,610
        2.3
        CV-86
        152,487
        1.5
        CV-87
        76,064
        0.7
        CV-88
        222,493
        2.1

        Barcodes of Undetermined Reads

        Barcodes of Undetermined Reads
        We have determined the barcodes of your undetermined reads (reads containing a barcode that you did not encode in your metadata). Here are the top 20 barcodes belonging to the undetermined reads. The full list is available here.

        Showing 20/20 rows and 2/2 columns.
        Sample NameCountFrequency (%)
        CTCTCTACTCTTTCCC
        26511.0
        1.8
        CTCTCTCCTCTTTCCC
        18461.0
        1.2
        CGAGGCTGTCTTTCCC
        11430.0
        0.8
        GCTCATGATCTTTCCC
        11204.0
        0.7
        GTAGAGGATCTTTCCC
        8589.0
        0.6
        TCTCCTTCTCTTTCCC
        7767.0
        0.5
        TAGGCATGTCTTTCCC
        7660.0
        0.5
        AAGAGGCATCTTTCCC
        6473.0
        0.4
        CTCTTCTTTCTTTCCC
        6087.0
        0.4
        ATCTCAGGTCTTTCCC
        5251.0
        0.3
        CCTCTTCCTCTTTCCC
        4802.0
        0.3
        TTCTCTTCTCTTTCCC
        4360.0
        0.3
        TCTTCCTTTCTTTCCC
        3961.0
        0.3
        CTCTCCTTTCTTTCCC
        3891.0
        0.3
        CTCTCTTCTCTTTCCC
        3532.0
        0.2
        TTTTTTTTTCTTTCCC
        2665.0
        0.2
        GCTCATGCTCTTTCCC
        2426.0
        0.2
        TCTCATGATCTTTCCC
        2041.0
        0.1
        TCTCCTGCTCTTTCCC
        1944.0
        0.1
        CTCTCTGCTCTTTCCC
        1840.0
        0.1

        Lane Statistics

        Lane Statistics

        Showing 1/1 rows and 4/4 columns.
        Sample NameTotal # of Single-End ReadsTotal # PF Reads% Undetermined% PhiX Aligned
        1.0
        10,919,814
        10,386,943
        14.5
        11.7

        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.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        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.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        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.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Base N Content

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

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Length Distribution

        All samples have sequences of a single length (151bp).


        Sequence Duplication Levels

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

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Overrepresented sequences

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

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        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.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).