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        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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        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 2023-11-02, 17:12 based on data in: /scratch/gencore/logs/html/HMLTGDMXY/merged


        General Statistics

        Showing 298/298 rows and 3/5 columns.
        Sample Name% Dups% GCM Seqs
        HMLTGDMXY_n01_KHC-001
        70.0%
        42%
        69.3
        HMLTGDMXY_n01_KHC-002
        43.5%
        51%
        37.3
        HMLTGDMXY_n01_KHC-003
        61.7%
        41%
        2.5
        HMLTGDMXY_n01_KHC-004
        57.5%
        42%
        3.0
        HMLTGDMXY_n01_KHC-005
        64.3%
        42%
        2.3
        HMLTGDMXY_n01_KHC-006
        21.2%
        48%
        2.4
        HMLTGDMXY_n01_KHC-007
        52.1%
        52%
        27.2
        HMLTGDMXY_n01_KHC-008
        82.8%
        40%
        5.0
        HMLTGDMXY_n01_KHC-009
        69.5%
        40%
        2.6
        HMLTGDMXY_n01_KHC-010
        54.7%
        55%
        33.4
        HMLTGDMXY_n01_KHC-011
        49.0%
        49%
        62.5
        HMLTGDMXY_n01_KHC-012
        64.0%
        64%
        33.9
        HMLTGDMXY_n01_KHC-013
        18.6%
        41%
        2.5
        HMLTGDMXY_n01_KHC-014
        59.1%
        53%
        29.6
        HMLTGDMXY_n01_KHC-015
        69.4%
        40%
        2.2
        HMLTGDMXY_n01_KHC-016
        34.2%
        47%
        8.6
        HMLTGDMXY_n01_MHC-001
        61.4%
        42%
        2.4
        HMLTGDMXY_n01_MHC-002
        16.4%
        40%
        2.0
        HMLTGDMXY_n01_MHC-003
        60.7%
        44%
        44.1
        HMLTGDMXY_n01_MHC-004
        81.0%
        45%
        55.9
        HMLTGDMXY_n01_MHC-005
        39.9%
        46%
        40.0
        HMLTGDMXY_n01_MHC-006
        61.6%
        52%
        44.6
        HMLTGDMXY_n01_MHC-007
        39.7%
        50%
        32.3
        HMLTGDMXY_n01_MHC-008
        59.0%
        52%
        59.1
        HMLTGDMXY_n01_MHC-009
        64.3%
        41%
        2.5
        HMLTGDMXY_n01_MHC-010
        27.3%
        47%
        1.8
        HMLTGDMXY_n01_MHC-011
        74.9%
        39%
        2.1
        HMLTGDMXY_n01_MHC-012
        58.2%
        41%
        2.9
        HMLTGDMXY_n01_MHC-013
        48.3%
        46%
        53.0
        HMLTGDMXY_n01_MHC-014
        48.6%
        44%
        2.1
        HMLTGDMXY_n01_MHC-015
        21.5%
        41%
        1.9
        HMLTGDMXY_n01_MHC-016
        64.1%
        41%
        3.7
        HMLTGDMXY_n01_MHC-017
        17.8%
        41%
        1.1
        HMLTGDMXY_n01_MHC-018
        23.3%
        40%
        1.4
        HMLTGDMXY_n01_MHC-019
        40.6%
        45%
        1.6
        HMLTGDMXY_n01_MHC-020
        83.4%
        40%
        68.8
        HMLTGDMXY_n01_MHC-021
        67.0%
        41%
        3.0
        HMLTGDMXY_n01_MHC-022
        43.1%
        40%
        1.9
        HMLTGDMXY_n01_MHC-023
        87.7%
        41%
        64.7
        HMLTGDMXY_n01_MHC-024
        68.5%
        40%
        3.7
        HMLTGDMXY_n01_MHC-025
        41.0%
        50%
        29.9
        HMLTGDMXY_n01_MHC-026
        51.1%
        48%
        47.8
        HMLTGDMXY_n01_MHC-027
        64.6%
        51%
        89.5
        HMLTGDMXY_n01_MHC-028
        68.4%
        41%
        2.2
        HMLTGDMXY_n01_MHC-029
        49.1%
        50%
        44.0
        HMLTGDMXY_n01_MHC-030
        58.8%
        50%
        55.5
        HMLTGDMXY_n01_MHC-031
        76.0%
        41%
        40.0
        HMLTGDMXY_n01_MHC-032
        70.9%
        54%
        76.2
        HMLTGDMXY_n01_MHC-033
        54.3%
        50%
        43.9
        HMLTGDMXY_n01_MHC-034
        53.0%
        43%
        2.5
        HMLTGDMXY_n01_MHC-035
        56.0%
        49%
        83.3
        HMLTGDMXY_n01_MHC-036
        43.1%
        51%
        22.6
        HMLTGDMXY_n01_MHC-037
        26.1%
        47%
        1.6
        HMLTGDMXY_n01_MHC-038
        60.3%
        54%
        37.3
        HMLTGDMXY_n01_MHC-039
        60.5%
        53%
        44.9
        HMLTGDMXY_n01_MHC-040
        50.4%
        48%
        38.9
        HMLTGDMXY_n01_MHC-041
        45.4%
        47%
        34.9
        HMLTGDMXY_n01_MHC-042
        49.7%
        43%
        2.0
        HMLTGDMXY_n01_MHC-043
        21.1%
        47%
        4.0
        HMLTGDMXY_n01_MHC-044
        35.3%
        47%
        3.1
        HMLTGDMXY_n01_MHC-045
        83.6%
        41%
        46.7
        HMLTGDMXY_n01_MHC-046
        76.4%
        39%
        39.9
        HMLTGDMXY_n01_MHC-047
        62.7%
        48%
        74.3
        HMLTGDMXY_n01_MHC-048
        90.1%
        40%
        48.8
        HMLTGDMXY_n01_MHC-049
        50.2%
        50%
        34.5
        HMLTGDMXY_n01_MHC-050
        37.1%
        46%
        45.0
        HMLTGDMXY_n01_MHC-051
        34.9%
        48%
        21.4
        HMLTGDMXY_n01_MHC-052
        52.4%
        49%
        43.9
        HMLTGDMXY_n01_MHC-053
        43.9%
        48%
        34.7
        HMLTGDMXY_n01_MHC-054
        53.7%
        45%
        45.3
        HMLTGDMXY_n01_MHC-055
        91.1%
        52%
        62.3
        HMLTGDMXY_n01_MHC-056
        74.3%
        40%
        2.5
        HMLTGDMXY_n01_MHC-057
        64.9%
        41%
        1.3
        HMLTGDMXY_n01_MHC-058
        66.4%
        45%
        53.3
        HMLTGDMXY_n01_MHC-059
        46.6%
        49%
        23.4
        HMLTGDMXY_n01_MHC-060
        44.0%
        49%
        27.4
        HMLTGDMXY_n01_MHC-061
        54.2%
        47%
        2.8
        HMLTGDMXY_n01_MHC-062
        58.7%
        43%
        2.3
        HMLTGDMXY_n01_MHC-063
        47.6%
        48%
        39.4
        HMLTGDMXY_n01_MHC-064
        49.9%
        47%
        45.1
        HMLTGDMXY_n01_MHC-065
        39.8%
        45%
        38.8
        HMLTGDMXY_n01_MHC-066
        37.7%
        46%
        26.6
        HMLTGDMXY_n01_MHC-067
        43.5%
        45%
        1.8
        HMLTGDMXY_n01_MHC-068
        58.1%
        43%
        2.7
        HMLTGDMXY_n01_MHC-069
        67.2%
        45%
        58.0
        HMLTGDMXY_n01_MHC-070
        64.3%
        41%
        2.1
        HMLTGDMXY_n01_MHC-071
        82.9%
        42%
        46.6
        HMLTGDMXY_n01_MHC-072
        45.1%
        50%
        31.7
        HMLTGDMXY_n01_MHC-073
        58.3%
        43%
        3.0
        HMLTGDMXY_n01_MHC-074
        50.9%
        47%
        53.5
        HMLTGDMXY_n01_MHC-075
        39.5%
        46%
        36.4
        HMLTGDMXY_n01_MHC-076
        67.9%
        41%
        1.6
        HMLTGDMXY_n01_MHC-077
        35.3%
        45%
        24.3
        HMLTGDMXY_n01_MHC-078
        59.3%
        43%
        4.3
        HMLTGDMXY_n01_MHC-079
        27.1%
        50%
        2.3
        HMLTGDMXY_n01_MHC-080
        52.0%
        44%
        33.8
        HMLTGDMXY_n01_MHC-081
        70.0%
        52%
        60.8
        HMLTGDMXY_n01_MHC-082
        85.1%
        40%
        50.2
        HMLTGDMXY_n01_MHC-083
        91.4%
        56%
        69.3
        HMLTGDMXY_n01_MHC-084
        28.0%
        49%
        1.7
        HMLTGDMXY_n01_MHC-085
        67.9%
        41%
        3.5
        HMLTGDMXY_n01_MHC-086
        87.8%
        44%
        42.0
        HMLTGDMXY_n01_MHC-087
        69.6%
        41%
        3.8
        HMLTGDMXY_n01_MHC-088
        59.2%
        47%
        2.7
        HMLTGDMXY_n01_MHC-089
        22.0%
        42%
        2.2
        HMLTGDMXY_n01_MHC-090
        68.7%
        39%
        26.5
        HMLTGDMXY_n01_MHC-091
        45.2%
        44%
        41.0
        HMLTGDMXY_n01_MHC-092
        61.1%
        39%
        2.1
        HMLTGDMXY_n01_MTH-001
        44.8%
        47%
        36.1
        HMLTGDMXY_n01_MTH-002
        55.6%
        51%
        40.8
        HMLTGDMXY_n01_MTH-003
        47.0%
        43%
        2.4
        HMLTGDMXY_n01_MTH-004
        51.4%
        49%
        29.2
        HMLTGDMXY_n01_MTH-005
        82.8%
        38%
        2.9
        HMLTGDMXY_n01_MTH-006
        80.1%
        40%
        30.4
        HMLTGDMXY_n01_MTH-007
        52.9%
        48%
        47.7
        HMLTGDMXY_n01_MTH-008
        48.5%
        47%
        52.8
        HMLTGDMXY_n01_MTH-009
        49.6%
        43%
        3.2
        HMLTGDMXY_n01_MTH-010
        46.4%
        48%
        36.4
        HMLTGDMXY_n01_MTH-011
        43.4%
        40%
        1.7
        HMLTGDMXY_n01_MTH-012
        35.0%
        50%
        4.9
        HMLTGDMXY_n01_MTH-013
        49.7%
        47%
        58.5
        HMLTGDMXY_n01_MTH-014
        72.9%
        42%
        46.5
        HMLTGDMXY_n01_MTH-015
        44.3%
        47%
        54.1
        HMLTGDMXY_n01_MTH-016
        37.0%
        41%
        2.8
        HMLTGDMXY_n01_MTH-017
        44.0%
        48%
        29.8
        HMLTGDMXY_n01_MTH-018
        43.2%
        46%
        42.1
        HMLTGDMXY_n01_MTH-019
        72.3%
        45%
        39.2
        HMLTGDMXY_n01_MTH-020
        23.6%
        42%
        2.1
        HMLTGDMXY_n01_MTH-021
        86.8%
        40%
        69.9
        HMLTGDMXY_n01_MTH-022
        76.1%
        38%
        4.1
        HMLTGDMXY_n01_MTH-023
        50.7%
        47%
        76.8
        HMLTGDMXY_n01_MTH-024
        48.5%
        47%
        60.6
        HMLTGDMXY_n01_MTH-025
        54.0%
        40%
        2.3
        HMLTGDMXY_n01_MTH-026
        51.9%
        47%
        34.6
        HMLTGDMXY_n01_MTH-027
        40.5%
        44%
        36.8
        HMLTGDMXY_n01_MTH-028
        67.8%
        39%
        2.2
        HMLTGDMXY_n01_MTH-029
        84.3%
        58%
        72.9
        HMLTGDMXY_n01_MTH-030
        46.0%
        48%
        43.7
        HMLTGDMXY_n01_MTH-031
        83.0%
        39%
        41.6
        HMLTGDMXY_n01_MTH-032
        42.9%
        46%
        49.0
        HMLTGDMXY_n01_MTH-033
        86.3%
        39%
        9.3
        HMLTGDMXY_n01_MTH-034
        65.8%
        39%
        2.0
        HMLTGDMXY_n01_MTH-035
        46.1%
        47%
        40.8
        HMLTGDMXY_n01_MTH-036
        50.0%
        47%
        61.6
        HMLTGDMXY_n01_MTH-037
        77.3%
        39%
        8.5
        HMLTGDMXY_n01_MTH-038
        54.8%
        40%
        0.7
        HMLTGDMXY_n01_MTH-039
        57.9%
        40%
        1.1
        HMLTGDMXY_n01_MTH-040
        60.2%
        42%
        1.1
        HMLTGDMXY_n01_undetermined
        72.1%
        43%
        277.1
        HMLTGDMXY_n02_KHC-001
        65.5%
        42%
        69.3
        HMLTGDMXY_n02_KHC-002
        39.1%
        51%
        37.3
        HMLTGDMXY_n02_KHC-003
        59.2%
        41%
        2.5
        HMLTGDMXY_n02_KHC-004
        55.0%
        42%
        3.0
        HMLTGDMXY_n02_KHC-005
        61.3%
        42%
        2.3
        HMLTGDMXY_n02_KHC-006
        18.0%
        48%
        2.4
        HMLTGDMXY_n02_KHC-007
        46.2%
        51%
        27.2
        HMLTGDMXY_n02_KHC-008
        79.4%
        39%
        5.0
        HMLTGDMXY_n02_KHC-009
        66.4%
        40%
        2.6
        HMLTGDMXY_n02_KHC-010
        50.0%
        54%
        33.4
        HMLTGDMXY_n02_KHC-011
        46.1%
        49%
        62.5
        HMLTGDMXY_n02_KHC-012
        61.5%
        64%
        33.9
        HMLTGDMXY_n02_KHC-013
        15.1%
        41%
        2.5
        HMLTGDMXY_n02_KHC-014
        52.8%
        52%
        29.6
        HMLTGDMXY_n02_KHC-015
        66.9%
        40%
        2.2
        HMLTGDMXY_n02_KHC-016
        32.1%
        48%
        8.6
        HMLTGDMXY_n02_MHC-001
        58.3%
        42%
        2.4
        HMLTGDMXY_n02_MHC-002
        13.1%
        40%
        2.0
        HMLTGDMXY_n02_MHC-003
        57.1%
        44%
        44.1
        HMLTGDMXY_n02_MHC-004
        78.2%
        44%
        55.9
        HMLTGDMXY_n02_MHC-005
        35.7%
        46%
        40.0
        HMLTGDMXY_n02_MHC-006
        58.0%
        52%
        44.6
        HMLTGDMXY_n02_MHC-007
        37.6%
        50%
        32.3
        HMLTGDMXY_n02_MHC-008
        53.2%
        52%
        59.1
        HMLTGDMXY_n02_MHC-009
        61.3%
        41%
        2.5
        HMLTGDMXY_n02_MHC-010
        24.9%
        47%
        1.8
        HMLTGDMXY_n02_MHC-011
        71.4%
        39%
        2.1
        HMLTGDMXY_n02_MHC-012
        55.4%
        41%
        2.9
        HMLTGDMXY_n02_MHC-013
        44.2%
        46%
        53.0
        HMLTGDMXY_n02_MHC-014
        47.8%
        45%
        2.1
        HMLTGDMXY_n02_MHC-015
        17.9%
        40%
        1.9
        HMLTGDMXY_n02_MHC-016
        61.7%
        42%
        3.7
        HMLTGDMXY_n02_MHC-017
        14.8%
        40%
        1.1
        HMLTGDMXY_n02_MHC-018
        20.4%
        40%
        1.4
        HMLTGDMXY_n02_MHC-019
        38.0%
        46%
        1.6
        HMLTGDMXY_n02_MHC-020
        80.9%
        40%
        68.8
        HMLTGDMXY_n02_MHC-021
        64.4%
        41%
        3.0
        HMLTGDMXY_n02_MHC-022
        41.0%
        39%
        1.9
        HMLTGDMXY_n02_MHC-023
        85.3%
        40%
        64.7
        HMLTGDMXY_n02_MHC-024
        65.9%
        41%
        3.7
        HMLTGDMXY_n02_MHC-025
        37.1%
        50%
        29.9
        HMLTGDMXY_n02_MHC-026
        44.8%
        48%
        47.8
        HMLTGDMXY_n02_MHC-027
        60.0%
        51%
        89.5
        HMLTGDMXY_n02_MHC-028
        66.6%
        41%
        2.2
        HMLTGDMXY_n02_MHC-029
        45.8%
        50%
        44.0
        HMLTGDMXY_n02_MHC-030
        51.8%
        50%
        55.5
        HMLTGDMXY_n02_MHC-031
        72.4%
        41%
        40.0
        HMLTGDMXY_n02_MHC-032
        65.7%
        54%
        76.2
        HMLTGDMXY_n02_MHC-033
        48.6%
        50%
        43.9
        HMLTGDMXY_n02_MHC-034
        50.8%
        43%
        2.5
        HMLTGDMXY_n02_MHC-035
        48.9%
        48%
        83.3
        HMLTGDMXY_n02_MHC-036
        38.3%
        51%
        22.6
        HMLTGDMXY_n02_MHC-037
        23.9%
        47%
        1.6
        HMLTGDMXY_n02_MHC-038
        55.6%
        53%
        37.3
        HMLTGDMXY_n02_MHC-039
        57.6%
        53%
        44.9
        HMLTGDMXY_n02_MHC-040
        42.0%
        48%
        38.9
        HMLTGDMXY_n02_MHC-041
        39.3%
        47%
        34.9
        HMLTGDMXY_n02_MHC-042
        48.3%
        44%
        2.0
        HMLTGDMXY_n02_MHC-043
        18.5%
        47%
        4.0
        HMLTGDMXY_n02_MHC-044
        33.1%
        47%
        3.1
        HMLTGDMXY_n02_MHC-045
        80.7%
        40%
        46.7
        HMLTGDMXY_n02_MHC-046
        75.5%
        39%
        39.9
        HMLTGDMXY_n02_MHC-047
        59.3%
        48%
        74.3
        HMLTGDMXY_n02_MHC-048
        87.6%
        39%
        48.8
        HMLTGDMXY_n02_MHC-049
        42.5%
        50%
        34.5
        HMLTGDMXY_n02_MHC-050
        34.3%
        46%
        45.0
        HMLTGDMXY_n02_MHC-051
        28.4%
        49%
        21.4
        HMLTGDMXY_n02_MHC-052
        46.4%
        50%
        43.9
        HMLTGDMXY_n02_MHC-053
        37.2%
        49%
        34.7
        HMLTGDMXY_n02_MHC-054
        50.6%
        45%
        45.3
        HMLTGDMXY_n02_MHC-055
        89.6%
        52%
        62.3
        HMLTGDMXY_n02_MHC-056
        71.5%
        40%
        2.5
        HMLTGDMXY_n02_MHC-057
        62.4%
        41%
        1.3
        HMLTGDMXY_n02_MHC-058
        63.6%
        44%
        53.3
        HMLTGDMXY_n02_MHC-059
        40.2%
        50%
        23.4
        HMLTGDMXY_n02_MHC-060
        37.5%
        49%
        27.4
        HMLTGDMXY_n02_MHC-061
        52.5%
        47%
        2.8
        HMLTGDMXY_n02_MHC-062
        56.6%
        43%
        2.3
        HMLTGDMXY_n02_MHC-063
        41.4%
        49%
        39.4
        HMLTGDMXY_n02_MHC-064
        42.5%
        48%
        45.1
        HMLTGDMXY_n02_MHC-065
        36.3%
        45%
        38.8
        HMLTGDMXY_n02_MHC-066
        31.8%
        47%
        26.6
        HMLTGDMXY_n02_MHC-067
        42.2%
        46%
        1.8
        HMLTGDMXY_n02_MHC-068
        57.6%
        44%
        2.7
        HMLTGDMXY_n02_MHC-069
        64.5%
        45%
        58.0
        HMLTGDMXY_n02_MHC-070
        62.5%
        42%
        2.1
        HMLTGDMXY_n02_MHC-071
        80.2%
        42%
        46.6
        HMLTGDMXY_n02_MHC-072
        41.1%
        50%
        31.7
        HMLTGDMXY_n02_MHC-073
        55.5%
        43%
        3.0
        HMLTGDMXY_n02_MHC-074
        44.8%
        48%
        53.5
        HMLTGDMXY_n02_MHC-075
        31.6%
        47%
        36.4
        HMLTGDMXY_n02_MHC-076
        65.3%
        41%
        1.6
        HMLTGDMXY_n02_MHC-077
        32.7%
        45%
        24.3
        HMLTGDMXY_n02_MHC-078
        56.8%
        43%
        4.3
        HMLTGDMXY_n02_MHC-079
        25.6%
        50%
        2.3
        HMLTGDMXY_n02_MHC-080
        49.4%
        43%
        33.8
        HMLTGDMXY_n02_MHC-081
        65.8%
        51%
        60.8
        HMLTGDMXY_n02_MHC-082
        81.5%
        39%
        50.2
        HMLTGDMXY_n02_MHC-083
        90.2%
        56%
        69.3
        HMLTGDMXY_n02_MHC-084
        26.9%
        50%
        1.7
        HMLTGDMXY_n02_MHC-085
        65.1%
        42%
        3.5
        HMLTGDMXY_n02_MHC-086
        85.4%
        43%
        42.0
        HMLTGDMXY_n02_MHC-087
        66.1%
        41%
        3.8
        HMLTGDMXY_n02_MHC-088
        57.1%
        46%
        2.7
        HMLTGDMXY_n02_MHC-089
        20.1%
        42%
        2.2
        HMLTGDMXY_n02_MHC-090
        64.7%
        39%
        26.5
        HMLTGDMXY_n02_MHC-091
        41.9%
        44%
        41.0
        HMLTGDMXY_n02_MHC-092
        59.0%
        39%
        2.1
        HMLTGDMXY_n02_MTH-001
        38.4%
        48%
        36.1
        HMLTGDMXY_n02_MTH-002
        47.7%
        51%
        40.8
        HMLTGDMXY_n02_MTH-003
        43.4%
        42%
        2.4
        HMLTGDMXY_n02_MTH-004
        47.8%
        49%
        29.2
        HMLTGDMXY_n02_MTH-005
        80.7%
        37%
        2.9
        HMLTGDMXY_n02_MTH-006
        77.1%
        40%
        30.4
        HMLTGDMXY_n02_MTH-007
        44.2%
        48%
        47.7
        HMLTGDMXY_n02_MTH-008
        43.4%
        47%
        52.8
        HMLTGDMXY_n02_MTH-009
        46.3%
        43%
        3.2
        HMLTGDMXY_n02_MTH-010
        41.9%
        48%
        36.4
        HMLTGDMXY_n02_MTH-011
        41.8%
        40%
        1.7
        HMLTGDMXY_n02_MTH-012
        31.1%
        50%
        4.9
        HMLTGDMXY_n02_MTH-013
        46.6%
        47%
        58.5
        HMLTGDMXY_n02_MTH-014
        69.3%
        42%
        46.5
        HMLTGDMXY_n02_MTH-015
        40.2%
        48%
        54.1
        HMLTGDMXY_n02_MTH-016
        34.2%
        40%
        2.8
        HMLTGDMXY_n02_MTH-017
        39.1%
        48%
        29.8
        HMLTGDMXY_n02_MTH-018
        40.0%
        46%
        42.1
        HMLTGDMXY_n02_MTH-019
        70.0%
        45%
        39.2
        HMLTGDMXY_n02_MTH-020
        19.4%
        42%
        2.1
        HMLTGDMXY_n02_MTH-021
        83.9%
        40%
        69.9
        HMLTGDMXY_n02_MTH-022
        73.4%
        37%
        4.1
        HMLTGDMXY_n02_MTH-023
        45.5%
        47%
        76.8
        HMLTGDMXY_n02_MTH-024
        44.8%
        47%
        60.6
        HMLTGDMXY_n02_MTH-025
        51.4%
        39%
        2.3
        HMLTGDMXY_n02_MTH-026
        45.9%
        48%
        34.6
        HMLTGDMXY_n02_MTH-027
        36.1%
        44%
        36.8
        HMLTGDMXY_n02_MTH-028
        65.8%
        38%
        2.2
        HMLTGDMXY_n02_MTH-029
        81.7%
        58%
        72.9
        HMLTGDMXY_n02_MTH-030
        42.5%
        48%
        43.7
        HMLTGDMXY_n02_MTH-031
        81.6%
        38%
        41.6
        HMLTGDMXY_n02_MTH-032
        36.9%
        46%
        49.0
        HMLTGDMXY_n02_MTH-033
        83.4%
        38%
        9.3
        HMLTGDMXY_n02_MTH-034
        63.3%
        38%
        2.0
        HMLTGDMXY_n02_MTH-035
        42.3%
        47%
        40.8
        HMLTGDMXY_n02_MTH-036
        45.0%
        47%
        61.6
        HMLTGDMXY_n02_MTH-037
        74.3%
        38%
        8.5
        HMLTGDMXY_n02_MTH-038
        52.9%
        39%
        0.7
        HMLTGDMXY_n02_MTH-039
        56.0%
        39%
        1.1
        HMLTGDMXY_n02_MTH-040
        57.2%
        40%
        1.1
        HMLTGDMXY_n02_undetermined
        68.5%
        43%
        277.1

        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 149/149 rows and 2/2 columns.
        LibraryTotal Read CountPortion (%)
        undetermined_library
        277075160
        6.4
        KHC-003
        2475101
        0.1
        KHC-004
        2992634
        0.1
        KHC-005
        2265592
        0.1
        KHC-006
        2439739
        0.1
        KHC-008
        5005252
        0.1
        KHC-009
        2575233
        0.1
        KHC-015
        2242168
        0.1
        MHC-001
        2395442
        0.1
        MHC-009
        2508506
        0.1
        MHC-010
        1769756
        0.0
        MHC-011
        2131664
        0.0
        MHC-012
        2920828
        0.1
        MHC-014
        2090794
        0.0
        MHC-016
        3661555
        0.1
        MHC-019
        1612892
        0.0
        MHC-021
        3039378
        0.1
        MHC-024
        3690403
        0.1
        MHC-028
        2154872
        0.1
        MHC-034
        2544595
        0.1
        MHC-037
        1609721
        0.0
        MHC-042
        1987408
        0.0
        MHC-044
        3135807
        0.1
        MHC-056
        2542598
        0.1
        MHC-057
        1260159
        0.0
        MHC-061
        2776495
        0.1
        MHC-062
        2299280
        0.1
        MHC-067
        1827389
        0.0
        MHC-068
        2703435
        0.1
        MHC-070
        2139246
        0.0
        MHC-073
        2955046
        0.1
        MHC-076
        1623916
        0.0
        MHC-078
        4312291
        0.1
        MHC-079
        2290946
        0.1
        MHC-084
        1732589
        0.0
        MHC-085
        3496743
        0.1
        MHC-087
        3751371
        0.1
        MHC-089
        2157501
        0.1
        MHC-090
        26473661
        0.6
        MHC-092
        2050144
        0.0
        MTH-003
        2358537
        0.1
        MTH-005
        2909122
        0.1
        MTH-011
        1684103
        0.0
        MTH-016
        2758328
        0.1
        MTH-020
        2131606
        0.0
        MTH-022
        4081125
        0.1
        MTH-025
        2291050
        0.1
        MTH-028
        2189072
        0.1
        MTH-033
        9252900
        0.2
        MTH-034
        2024457
        0.0
        MTH-037
        8507576
        0.2
        MTH-038
        733304
        0.0
        MTH-039
        1087103
        0.0
        MTH-040
        1078933
        0.0
        KHC-013
        2511340
        0.1
        MHC-002
        1965790
        0.0
        MHC-015
        1870185
        0.0
        MHC-017
        1114225
        0.0
        MHC-018
        1429760
        0.0
        MHC-022
        1875975
        0.0
        MHC-043
        3963338
        0.1
        MTH-006
        30373866
        0.7
        MTH-012
        4858676
        0.1
        MHC-031
        40001275
        0.9
        KHC-001
        69342850
        1.6
        MHC-023
        64671087
        1.5
        MHC-045
        46734595
        1.1
        MHC-048
        48811975
        1.1
        MHC-071
        46599293
        1.1
        MHC-082
        50225159
        1.2
        MHC-086
        41951060
        1.0
        MHC-088
        2652026
        0.1
        MTH-009
        3194474
        0.1
        MTH-014
        46482368
        1.1
        MTH-021
        69887470
        1.6
        MTH-031
        41644851
        1.0
        KHC-011
        62529432
        1.4
        MHC-039
        44898057
        1.0
        MHC-046
        39874068
        0.9
        MHC-050
        44952760
        1.0
        MHC-054
        45257752
        1.0
        MHC-065
        38761582
        0.9
        MHC-077
        24319467
        0.6
        MHC-080
        33818000
        0.8
        MHC-091
        40956875
        0.9
        MTH-004
        29154525
        0.7
        MTH-018
        42122107
        1.0
        MTH-019
        39244068
        0.9
        MTH-024
        60596679
        1.4
        MTH-027
        36807165
        0.8
        MTH-029
        72942524
        1.7
        MHC-047
        74325985
        1.7
        MHC-055
        62320134
        1.4
        MHC-058
        53253742
        1.2
        MHC-069
        58044788
        1.3
        MHC-081
        60794569
        1.4
        MHC-083
        69297265
        1.6
        MHC-003
        44092252
        1.0
        MHC-004
        55910850
        1.3
        MHC-006
        44592270
        1.0
        MHC-007
        32340812
        0.7
        MHC-020
        68778029
        1.6
        MHC-029
        44016343
        1.0
        MHC-036
        22624095
        0.5
        MHC-072
        31697244
        0.7
        KHC-002
        37309741
        0.9
        KHC-007
        27170850
        0.6
        KHC-010
        33381209
        0.8
        KHC-012
        33903223
        0.8
        KHC-014
        29596582
        0.7
        KHC-016
        8601649
        0.2
        MHC-008
        59138211
        1.4
        MHC-025
        29886650
        0.7
        MHC-026
        47755466
        1.1
        MHC-027
        89530953
        2.1
        MHC-030
        55492701
        1.3
        MHC-032
        76153719
        1.8
        MHC-033
        43857195
        1.0
        MHC-035
        83344051
        1.9
        MHC-038
        37321906
        0.9
        MHC-040
        38903222
        0.9
        MHC-049
        34453321
        0.8
        MHC-051
        21403056
        0.5
        MHC-052
        43936984
        1.0
        MHC-053
        34655146
        0.8
        MHC-059
        23402734
        0.5
        MHC-060
        27422194
        0.6
        MHC-063
        39395974
        0.9
        MHC-064
        45145844
        1.0
        MHC-066
        26560832
        0.6
        MHC-074
        53502032
        1.2
        MHC-075
        36432523
        0.8
        MTH-001
        36122599
        0.8
        MTH-002
        40823922
        0.9
        MTH-007
        47712668
        1.1
        MTH-008
        52772562
        1.2
        MTH-010
        36411510
        0.8
        MTH-013
        58493849
        1.3
        MTH-015
        54102356
        1.2
        MTH-017
        29803001
        0.7
        MTH-026
        34575641
        0.8
        MTH-030
        43723026
        1.0
        MTH-032
        49045650
        1.1
        MTH-035
        40775790
        0.9
        MTH-036
        61611548
        1.4
        MHC-005
        39988310
        0.9
        MHC-013
        53012548
        1.2
        MHC-041
        34878132
        0.8
        MTH-023
        76767228
        1.8

        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. If your libraries are dual indexed, the two indicies are concatenated.

        Showing 20/20 rows and 2/2 columns.
        Barcode Sequence(s)CountFrequency (%)
        GGGGGGGGAGATCTCG
        138065672.0
        49.8
        GGGGGGGGCGATCTCG
        395248.0
        0.1
        GGGGGGGGAGTTCTCG
        316613.0
        0.1
        AAAAAAAAAAAAAAAA
        257589.0
        0.1
        CACGCAATTACGCACG
        162866.0
        0.1
        GGGGGGGGCGTTGAGT
        155047.0
        0.1
        GGGGGGGGAGTGCTTG
        151375.0
        0.1
        GGGGGGGGTGGCTAGT
        134271.0
        0.1
        GGGGGGGGAGTCTGTG
        132441.0
        0.1
        GGGGGGGGGGTGACAA
        126189.0
        0.1
        GGGGGGGGATATCTCG
        122980.0
        0.0
        CACGCATATAACGCAC
        117795.0
        0.0
        GGGGGGGGTCGACATG
        116842.0
        0.0
        GGGGGGGGAGATATCG
        109970.0
        0.0
        ACAGTGGAGGTGACAA
        109387.0
        0.0
        GGGGGGGGCACTGTTG
        107692.0
        0.0
        GGGGGGGGNGATCTCG
        106285.0
        0.0
        GGGGGGGGGATTCGTG
        101246.0
        0.0
        GGGGGGGGCGCTCTAT
        100870.0
        0.0
        GGGGGGGGCTAGACGA
        100861.0
        0.0

        Run Statistics

        Showing 1/1 rows and 4/4 columns.
        Number of LanesTotal # of Single-End ReadsTotal # PF Reads% Undetermined% PhiX Aligned
        2.0
        5761400832
        4352567911
        6.4
        3.2

        FastQC

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

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

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


        Sequence Quality Histograms

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

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

        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.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

        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.

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample 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.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

        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.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

        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 (101bp).

        Sequence Duplication Levels

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (eg PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

        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.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as over represented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all of the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        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.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

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


        Status Checks

        Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

        Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

        In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

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