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

        Note that additional data was saved in multiqc_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 1.7

        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 2019-02-18, 17:50 based on data in: /home/tavinbio/transcriptome_virus_renato/d1_rRNA_logs


        General Statistics

        Showing 36/36 rows and 1/1 columns.
        Sample Name% Aligned
        logrrna_Mock1_L001
        46.8%
        logrrna_Mock1_L002
        46.8%
        logrrna_Mock1_L003
        46.9%
        logrrna_Mock1_L004
        46.8%
        logrrna_Mock2_L001
        22.7%
        logrrna_Mock2_L002
        22.7%
        logrrna_Mock2_L003
        22.8%
        logrrna_Mock2_L004
        22.7%
        logrrna_Mock3_L001
        37.8%
        logrrna_Mock3_L002
        37.8%
        logrrna_Mock3_L003
        37.9%
        logrrna_Mock3_L004
        37.8%
        logrrna_OROV1_L001
        68.8%
        logrrna_OROV1_L002
        68.7%
        logrrna_OROV1_L003
        68.8%
        logrrna_OROV1_L004
        68.8%
        logrrna_OROV2_L001
        75.9%
        logrrna_OROV2_L002
        75.8%
        logrrna_OROV2_L003
        76.0%
        logrrna_OROV2_L004
        75.9%
        logrrna_OROV3_L001
        73.5%
        logrrna_OROV3_L002
        73.5%
        logrrna_OROV3_L003
        73.6%
        logrrna_OROV3_L004
        73.6%
        logrrna_ZIKAV1_L001
        74.7%
        logrrna_ZIKAV1_L002
        74.5%
        logrrna_ZIKAV1_L003
        74.8%
        logrrna_ZIKAV1_L004
        74.6%
        logrrna_ZIKAV2_L001
        71.4%
        logrrna_ZIKAV2_L002
        71.3%
        logrrna_ZIKAV2_L003
        71.4%
        logrrna_ZIKAV2_L004
        71.3%
        logrrna_ZIKAV3_L001
        63.8%
        logrrna_ZIKAV3_L002
        63.7%
        logrrna_ZIKAV3_L003
        64.0%
        logrrna_ZIKAV3_L004
        63.8%

        Bowtie 2

        Bowtie 2 is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences.

        This plot shows the number of reads aligning to the reference in different ways.
        Please note that single mate alignment counts are halved to tally with pair counts properly.

        There are 6 possible types of alignment: PE mapped uniquely: Pair has only one occurence in the reference genome. PE mapped discordantly uniquely: Pair has only one occurence but not in proper pair. PE one mate mapped uniquely: One read of a pair has one occurence. PE multimapped: Pair has multiple occurence. PE one mate multimapped: One read of a pair has multiple occurence. PE neither mate aligned: Pair has no occurence.

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