ChIPseq-mapping-report

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        Download the raw data used to create the plots in this report below:

        Note that additional data was saved in ChIPseq-mapping-report_multiqc_report_data when this report was generated.


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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 1.10.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

        ChIPseq-mapping-report

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

        Report generated on 2020-12-01, 02:52 based on data in: /share/workshop/epigenetics_workshop/msettles/chipseq_example/02-BWA


        General Statistics

        Showing 8/8 rows and 7/9 columns.
        Sample NameM Reads MappedError rateM Non-PrimaryM Reads Mapped% Mapped% Proper PairsM Total seqs
        JLDY037D_bwa
        4.3
        1.24%
        0.0
        4.2
        93.2%
        82.3%
        4.5
        JLDY037E_bwa
        40.6
        0.64%
        0.0
        38.6
        99.4%
        79.3%
        38.8
        JLDY037F_bwa
        51.3
        0.59%
        0.0
        49.4
        99.4%
        85.4%
        49.7
        JLDY037G_bwa
        33.7
        0.57%
        0.0
        32.3
        99.0%
        85.3%
        32.7
        JLDY037I_bwa
        50.2
        0.68%
        0.0
        48.4
        99.3%
        85.7%
        48.7
        JLDY037J_bwa
        47.1
        0.69%
        0.0
        42.5
        99.6%
        63.8%
        42.7
        JLDY037K_bwa
        47.9
        0.68%
        0.0
        43.8
        99.3%
        68.0%
        44.1
        JLDY037L_bwa
        0.1
        1.92%
        0.0
        0.1
        28.2%
        18.2%
        0.2

        Samtools

        Samtools is a suite of programs for interacting with high-throughput sequencing data.

        Percent Mapped

        Alignment metrics from samtools stats; mapped vs. unmapped reads.

        For a set of samples that have come from the same multiplexed library, similar numbers of reads for each sample are expected. Large differences in numbers might indicate issues during the library preparation process. Whilst large differences in read numbers may be controlled for in downstream processings (e.g. read count normalisation), you may wish to consider whether the read depths achieved have fallen below recommended levels depending on the applications.

        Low alignment rates could indicate contamination of samples (e.g. adapter sequences), low sequencing quality or other artefacts. These can be further investigated in the sequence level QC (e.g. from FastQC).

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        Alignment metrics

        This module parses the output from samtools stats. All numbers in millions.

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        Samtools Flagstat

        This module parses the output from samtools flagstat. All numbers in millions.

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        XY counts

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        Mapped reads per contig

        The samtools idxstats tool counts the number of mapped reads per chromosome / contig. Chromosomes with < 0.1% of the total aligned reads are omitted from this plot.

           
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