Slamdunk timeseries example QA

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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 0.9.dev0 (3f5c6b4)

        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

        Slamdunk timeseries example QA

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2016-12-29, 18:12 based on data in: /clustertmp/slamdunk/timeseries_example_v0.2.2-dev

        General Statistics

        Showing 6/6 rows and 4/4 columns.
        Sample NameCountedRetainedMappedSequenced
        day1_timepoint_rep1
        17.69 M
        12.28 M
        18.53 M
        20.70 M
        day1_timepoint_rep2
        19.68 M
        11.44 M
        17.75 M
        20.36 M
        day1_timepoint_rep3
        25.15 M
        14.41 M
        21.12 M
        23.77 M
        zero_timepoint_rep1
        24.41 M
        13.00 M
        18.69 M
        21.00 M
        zero_timepoint_rep2
        20.60 M
        11.66 M
        17.54 M
        19.61 M
        zero_timepoint_rep3
        26.93 M
        14.46 M
        21.77 M
        27.57 M

        Slamdunk

        Slamdunk is a tool to analyze SLAMSeq data.

        Filter statistics

        This table shows the number of reads filtered with each filter criterion during filtering phase of slamdunk.

        Showing 6/6 rows and 5/5 columns.
        Sample NameMappedMultimap-FilteredNM-FilteredIdentity-FilteredMQ-Filtered
        day1_timepoint_rep1
        18.53 M
        2.20 M
        0.00 M
        4.05 M
        0.00 M
        day1_timepoint_rep2
        17.75 M
        2.58 M
        0.00 M
        3.73 M
        0.00 M
        day1_timepoint_rep3
        21.12 M
        3.08 M
        0.00 M
        3.63 M
        0.00 M
        zero_timepoint_rep1
        18.69 M
        2.96 M
        0.00 M
        2.73 M
        0.00 M
        zero_timepoint_rep2
        17.54 M
        2.95 M
        0.00 M
        2.93 M
        0.00 M
        zero_timepoint_rep3
        21.77 M
        3.70 M
        0.00 M
        3.62 M
        0.00 M

        PCA (T>C based)

        This plot shows the principal components of samples based on the distribution of reads with T>C conversions within UTRs (see the slamdunk docs).

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        Conversion rates per UTR

        This plot shows the individual conversion rates for all UTRs (see the slamdunk docs).

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        Conversion rates per read

        This plot shows the individual conversion rates over all reads. It shows these conversion rates strand-specific: This means for a properly labelled sample you would see a T>C excess on the plus-strand and an A>G excess on the minus strand (see the slamdunk docs).

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        Non T>C mutations over read positions

        This plot shows the distribution of non T>C mutations across read positions (see the slamdunk docs).

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        T>C conversions over read positions

        This plot shows the distribution of T>C conversions across read positions (see the slamdunk docs).

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        Non T>C mutations over UTR positions

        This plot shows the distribution of non T>C mutations across UTR positions for the last 200 bp from the 3' UTR end (see the slamdunk docs).

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        T>C conversions over UTR positions

        This plot shows the distribution of T>C conversions across UTR positions for the last 200 bp from the 3' UTR end (see the slamdunk docs).

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        MultiQC v0.9.dev0 (3f5c6b4) - Written by Phil Ewels, available on GitHub.

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