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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 (11a8f22)

        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 2021-02-26, 09:51 based on data in: /mnt/lustre/agalicina/FUNGI/distiller-nf/stats_collected


        General Statistics

        Showing 6/6 rows and 6/6 columns.
        Sample NameM read pairs% unmapped% single-side mapped% both-side mapped% duplicated% cis
        1441-1.schizo_1441_scaffolds
        69.2
        12.8%
        45.6%
        41.5%
        4.4%
        64.9%
        1441-1.schizo_X44_scaffolds
        71.9
        22.7%
        56.2%
        21.2%
        2.4%
        66.1%
        1441-2.schizo_1441_scaffolds
        80.2
        13.0%
        46.2%
        40.8%
        5.3%
        64.6%
        1441-2.schizo_X44_scaffolds
        83.4
        23.3%
        56.2%
        20.5%
        2.9%
        66.0%
        X44-1.schizo_1441_scaffolds
        56.4
        26.9%
        53.1%
        20.1%
        1.9%
        68.7%
        X44-1.schizo_X44_scaffolds
        52.0
        11.5%
        29.7%
        58.8%
        5.1%
        65.6%

        pairtools

        pairtools pairtools is a command-line framework for processing sequencing data generated with Chromatin Conformation Capture based experiments: pairtools can handle pairs of short-reads aligned to a reference genome, extract 3C-specific information and perform common tasks, such as sorting, filtering and deduplication.

        Pairs alignment status

        Number of pairs classified according to their alignment status, including uniquely mapped (UU), unmapped (NN), duplicated (DD), and others.

        For further details check pairtools documentation.

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        Pre-filtered pairs grouped by genomic separations

        Distribution of pre-filtered pairs (UU, UR and RU) by genomic separations for cis-pairs and trans-pairs as a separate group.

        Pre-filtered read pairs might still include artifacts: Short-range cis-pairs are typically enriched in technical artifacts, such as self-circles, dangling-ends, etc. High fraction of trans interactions typically suggests increased noise levels

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        Frequency of interactions as a function of genomic separation

        Frequency of interactions (pre-filtered pairs) as a function of genomic separation, known as "scaling plots", P(s). Click on an individual curve to reveal P(s) for different read pair orientations.

        Short-range cis-pairs are typically enriched in technical artifacts. Frequency of interactions for read pairs of different orientations ++,+-,-+ and -- (FF, FR, RF, RR) provide insight into these technical artifacts. Different technical artifacts manifest themselves with only single type of read orientation (dangling-ends - FR, self-circles - RF). Thus enrichment of FR/RF pairs at a given genomic separation can hint at the level of contamination.

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        Fraction of read pairs by strand orientation

        Number of interactions (pre-filtered pairs) reported for every type of read pair orientation. Numbers are reported for different ranges of genomic separation and combined.

        Short-range cis-pairs are typically enriched in technical artifacts. Frequency of interactions for read pairs of different orientations ++,+-,-+ and -- (FF, FR, RF, RR) provide insight into these technical artifacts. Different technical artifacts manifest themselves with only single type of read orientation (dangling-ends - FR, self-circles - RF). Thus enrichment of FR/RF pairs at a given genomic separation can hint at the level of contamination.

           
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        Pre-filtered pairs grouped by chromosomes

        Number of pre-filtered interactions (pairs) within a single chromosome or for a pair of chromosomes.

        Numbers of pairs are normalized by the total number of pre-filtered pairs per sample. Number are reported only for chromosomes/pairs that have >1% of pre-filtered pairs. [THERE SEEM TO BE A BUG IN MULTIQC HEATMAP - OBVIOUS WHEN USE HIGHLIGHTING,RENAMING ETC]

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