Loading report..

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 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.

         Loading report..

        Report generated on 2017-09-28, 17:09 based on data in: /mnt/gencore/sites/core-fastqc.bio.nyu.edu/html/000000000-BD6BC/1


        General Statistics

        Showing 54/54 rows and 3/5 columns.
        Sample Name% Dups% GCM Seqs
        000000000-BD6BC_l01n01_59n1.3510000009e802
        18.9%
        48%
        0.3
        000000000-BD6BC_l01n01_59n2.3510000009e8cc
        23.8%
        47%
        0.3
        000000000-BD6BC_l01n01_61n1.3510000009e846
        33.0%
        48%
        0.4
        000000000-BD6BC_l01n01_61n2.3510000009e901
        23.2%
        47%
        0.3
        000000000-BD6BC_l01n01_61o2.3510000009e9a2
        58.4%
        49%
        0.6
        000000000-BD6BC_l01n01_62n1.3510000009e82c
        47.3%
        51%
        0.3
        000000000-BD6BC_l01n01_62n2.3510000009e839
        34.9%
        49%
        0.4
        000000000-BD6BC_l01n01_62o1.3510000009e97b
        9.4%
        46%
        0.4
        000000000-BD6BC_l01n01_62o2.3510000009e988
        7.6%
        45%
        0.2
        000000000-BD6BC_l01n01_63n1.3510000009e86f
        67.2%
        51%
        0.3
        000000000-BD6BC_l01n01_63n2.3510000009e87c
        70.7%
        50%
        0.4
        000000000-BD6BC_l01n01_64n1.3510000009e8a3
        72.8%
        51%
        0.4
        000000000-BD6BC_l01n01_64n2.3510000009e8bf
        60.8%
        51%
        0.4
        000000000-BD6BC_l01n01_65n1.3510000009e8e6
        72.6%
        53%
        0.4
        000000000-BD6BC_l01n01_65n2.3510000009e8d9
        49.0%
        50%
        0.4
        000000000-BD6BC_l01n01_65o1.3510000009e995
        28.2%
        49%
        0.4
        000000000-BD6BC_l01n01_66n1.3510000009e92b
        72.0%
        51%
        0.5
        000000000-BD6BC_l01n01_66n2.3510000009e91e
        36.4%
        46%
        0.6
        000000000-BD6BC_l01n01_67n1.3510000009e889
        46.3%
        43%
        0.3
        000000000-BD6BC_l01n01_67n2.3510000009e8f3
        14.0%
        45%
        0.5
        000000000-BD6BC_l01n01_human-a549.3510000009e96e
        78.7%
        58%
        0.4
        000000000-BD6BC_l01n01_mr766a.3510000009e853
        94.0%
        48%
        2.0
        000000000-BD6BC_l01n01_mr766a1-1000.3510000009e952
        89.2%
        49%
        1.1
        000000000-BD6BC_l01n01_negative.3510000009e896
        82.2%
        45%
        0.2
        000000000-BD6BC_l01n01_prvabc59b.3510000009e81f
        93.9%
        50%
        3.0
        000000000-BD6BC_l01n01_prvabc59b1-100.3510000009e945
        70.4%
        46%
        0.1
        000000000-BD6BC_l01n01_prvabc59b1-1000.3510000009e938
        92.5%
        51%
        2.3
        000000000-BD6BC_l01n02_59n1.3520000009e80f
        12.7%
        49%
        0.3
        000000000-BD6BC_l01n02_59n2.3520000009e8c9
        12.1%
        49%
        0.3
        000000000-BD6BC_l01n02_61n1.3520000009e843
        19.7%
        49%
        0.4
        000000000-BD6BC_l01n02_61n2.3520000009e90e
        13.2%
        49%
        0.3
        000000000-BD6BC_l01n02_61o2.3520000009e9af
        56.1%
        49%
        0.6
        000000000-BD6BC_l01n02_62n1.3520000009e829
        44.4%
        51%
        0.3
        000000000-BD6BC_l01n02_62n2.3520000009e836
        28.3%
        49%
        0.4
        000000000-BD6BC_l01n02_62o1.3520000009e978
        7.6%
        45%
        0.4
        000000000-BD6BC_l01n02_62o2.3520000009e985
        4.4%
        46%
        0.2
        000000000-BD6BC_l01n02_63n1.3520000009e86c
        56.4%
        51%
        0.3
        000000000-BD6BC_l01n02_63n2.3520000009e879
        52.1%
        51%
        0.4
        000000000-BD6BC_l01n02_64n1.3520000009e8a0
        60.7%
        52%
        0.4
        000000000-BD6BC_l01n02_64n2.3520000009e8bc
        57.5%
        52%
        0.4
        000000000-BD6BC_l01n02_65n1.3520000009e8e3
        69.4%
        53%
        0.4
        000000000-BD6BC_l01n02_65n2.3520000009e8d6
        35.1%
        51%
        0.4
        000000000-BD6BC_l01n02_65o1.3520000009e992
        22.5%
        49%
        0.4
        000000000-BD6BC_l01n02_66n1.3520000009e928
        56.7%
        52%
        0.5
        000000000-BD6BC_l01n02_66n2.3520000009e91b
        11.5%
        47%
        0.6
        000000000-BD6BC_l01n02_67n1.3520000009e886
        6.5%
        47%
        0.3
        000000000-BD6BC_l01n02_67n2.3520000009e8f0
        6.7%
        46%
        0.5
        000000000-BD6BC_l01n02_human-a549.3520000009e96b
        66.3%
        58%
        0.4
        000000000-BD6BC_l01n02_mr766a.3520000009e850
        65.2%
        49%
        2.0
        000000000-BD6BC_l01n02_mr766a1-1000.3520000009e95f
        70.1%
        50%
        1.1
        000000000-BD6BC_l01n02_negative.3520000009e893
        9.5%
        50%
        0.2
        000000000-BD6BC_l01n02_prvabc59b.3520000009e81c
        79.1%
        51%
        3.0
        000000000-BD6BC_l01n02_prvabc59b1-100.3520000009e942
        13.2%
        48%
        0.1
        000000000-BD6BC_l01n02_prvabc59b1-1000.3520000009e935
        89.9%
        51%
        2.3

        Lane Statistics

        Lane Statistics

        Showing 1/1 rows and 3/3 columns.
        LaneTotal # of Single-End ReadsTotal # PF ReadsUndetermined
        1.0
        19106484
        17044213
        2.52%

        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.
        Perfect: The percentage of reads in this library which have a barcode perfectly matching the barcode specified in TuboWeb. The remainder of reads have mismatches upto the max number of mismatches specified in TuboWeb (Allowed barcode mismatch option in your Library Pool).

        Showing 27/27 rows and 3/3 columns.
        LibraryTotal Read CountPortion (%)Perfect (%)
        62o1
        375611
        2.3
        98.3
        prvabc59b1-100
        63136
        0.4
        95.5
        mr766a
        1997365
        12.0
        97.6
        66n2
        583423
        3.5
        97.1
        63n2
        362781
        2.2
        97.5
        67n1
        331010
        2.0
        96.2
        64n1
        358917
        2.2
        97.7
        61o2
        617708
        3.7
        98.0
        66n1
        463464
        2.8
        97.4
        61n1
        396055
        2.4
        97.2
        mr766a1-1000
        1055356
        6.4
        98.0
        65n1
        382048
        2.3
        96.2
        59n1
        258751
        1.6
        97.3
        62n1
        345755
        2.1
        98.2
        61n2
        280591
        1.7
        97.1
        67n2
        453144
        2.7
        96.1
        59n2
        258319
        1.6
        95.5
        prvabc59b1-1000
        2343374
        14.1
        98.0
        62n2
        384398
        2.3
        97.9
        62o2
        226542
        1.4
        97.2
        negative
        171735
        1.0
        94.5
        human-a549
        384591
        2.3
        98.0
        65o1
        425428
        2.6
        98.0
        prvabc59b
        2981387
        17.9
        98.2
        63n1
        310879
        1.9
        97.8
        64n2
        433518
        2.6
        98.0
        65n2
        369583
        2.2
        95.9

        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

        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.

        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.

        loading..