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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 1.8

        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 2023-12-06, 16:05 based on data in: /gscratch/srlab/graceac9/analyses/pycno/20231206_PSC2022_trimming


        General Statistics

        Showing 32/32 rows and 4/6 columns.
        Sample Name% DuplicationGC content% PF% Adapter
        PSC-0085_R1_001
        28.4%
        42.3%
        98.1%
        11.2%
        PSC-0087_R1_001
        21.1%
        42.2%
        97.8%
        11.0%
        PSC-0090_R1_001
        33.0%
        41.9%
        97.4%
        11.7%
        PSC-0093_R1_001
        19.8%
        41.8%
        98.1%
        11.1%
        PSC-0095_R1_001
        20.8%
        41.8%
        98.1%
        7.0%
        PSC-0096_R1_001
        20.4%
        41.3%
        98.0%
        6.1%
        PSC-0099_R1_001
        26.5%
        41.6%
        98.0%
        9.7%
        PSC-0105_R1_001
        22.2%
        41.1%
        98.2%
        6.8%
        PSC-0118_R1_001
        30.1%
        42.2%
        98.3%
        8.8%
        PSC-0119_R1_001
        20.1%
        41.7%
        97.9%
        8.6%
        PSC-0132_R1_001
        24.7%
        41.8%
        98.1%
        7.4%
        PSC-0141_R1_001
        20.6%
        42.0%
        98.4%
        8.3%
        PSC-0149_R1_001
        23.0%
        44.4%
        98.2%
        11.3%
        PSC-0150_R1_001
        24.9%
        36.8%
        96.8%
        22.9%
        PSC-0156_R1_001
        29.3%
        40.4%
        97.7%
        11.9%
        PSC-0174_R1_001
        23.1%
        41.0%
        98.1%
        10.9%
        PSC-0177_R1_001
        22.6%
        41.7%
        98.0%
        6.1%
        PSC-0186_R1_001
        22.9%
        41.0%
        97.8%
        9.6%
        PSC-0187_R1_001
        21.9%
        41.6%
        98.1%
        9.2%
        PSC-0188_R1_001
        23.5%
        42.6%
        98.3%
        9.8%
        PSC-0190_R1_001
        20.3%
        41.7%
        98.4%
        10.5%
        PSC-0198_R1_001
        23.0%
        40.7%
        97.9%
        9.0%
        PSC-0202_R1_001
        24.4%
        40.9%
        98.3%
        10.2%
        PSC-0203_R1_001
        29.7%
        41.1%
        97.9%
        10.7%
        PSC-0206_R1_001
        24.9%
        41.2%
        98.5%
        9.6%
        PSC-0209_R1_001
        65.7%
        40.8%
        98.0%
        32.2%
        PSC-0217_R1_001
        35.4%
        40.2%
        98.2%
        8.9%
        PSC-0219_R1_001
        21.6%
        41.3%
        98.3%
        8.2%
        PSC-0228_R1_001
        20.9%
        41.3%
        98.2%
        8.8%
        PSC-0230_R1_001
        21.1%
        41.7%
        97.9%
        8.2%
        PSC-0231_R1_001
        25.0%
        44.5%
        98.0%
        8.7%
        PSC-0235_R1_001
        32.8%
        41.1%
        97.9%
        5.1%

        fastp

        fastp An ultra-fast all-in-one FASTQ preprocessor (QC, adapters, trimming, filtering, splitting...)

        Filtered Reads

        Filtering statistics of sampled reads.

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        Duplication Rates

        Duplication rates of sampled reads.

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        Insert Sizes

        Insert size estimation of sampled reads.

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        Sequence Quality

        Average sequencing quality over each base of all reads.

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        GC Content

        Average GC content over each base of all reads.

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        N content

        Average N content over each base of all reads.

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