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        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 1.0.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

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

        Report generated on 2017-11-18, 23:11 based on data in: /woldlab/castor/home/dangeles/projects/med_cafe


        General Statistics

        Showing 66/66 rows and 5/7 columns.
        Sample Name% AlignedM Aligned% Dups% GCM Seqs
        18841_AGTCAA_L001_R1_001
        55.3%
        47%
        10.5
        18841_AGTCAA_L002_R1_001
        55.9%
        47%
        10.8
        18842_AGTTCC_L001_R1_001
        56.4%
        47%
        10.9
        18842_AGTTCC_L002_R1_001
        56.7%
        47%
        11.1
        18843_ATGTCA_L001_R1_001
        55.8%
        47%
        10.2
        18843_ATGTCA_L002_R1_001
        56.4%
        47%
        10.5
        18844_CCGTCC_L001_R1_001
        51.7%
        46%
        10.8
        18844_CCGTCC_L002_R1_001
        52.5%
        46%
        11.1
        18845_GTCCGC_L001_R1_001
        50.8%
        47%
        9.4
        18845_GTCCGC_L002_R1_001
        51.3%
        47%
        9.6
        18846_GTGAAA_L001_R1_001
        51.1%
        46%
        9.6
        18846_GTGAAA_L002_R1_001
        51.4%
        46%
        9.8
        18847_GTGGCC_L001_R1_001
        54.4%
        47%
        10.3
        18847_GTGGCC_L002_R1_001
        55.0%
        47%
        10.5
        18848_GTTTCG_L001_R1_001
        55.6%
        47%
        10.5
        18848_GTTTCG_L002_R1_001
        56.3%
        47%
        10.7
        18849_CGTACG_L001_R1_001
        54.3%
        46%
        9.9
        18849_CGTACG_L002_R1_001
        55.0%
        46%
        10.2
        18850_GAGTGG_L001_R1_001
        57.4%
        47%
        12.8
        18850_GAGTGG_L002_R1_001
        57.7%
        47%
        13.1
        18851_ACTGAT_L001_R1_001
        55.8%
        47%
        12.0
        18851_ACTGAT_L002_R1_001
        56.3%
        47%
        12.3
        18852_ATTCCT_L001_R1_001
        58.3%
        47%
        13.6
        18852_ATTCCT_L002_R1_001
        58.7%
        46%
        14.0
        18853_ATCACG_L001_R1_001
        55.6%
        47%
        12.5
        18853_ATCACG_L002_R1_001
        55.8%
        47%
        12.8
        18854_CGATGT_L001_R1_001
        53.1%
        46%
        12.4
        18854_CGATGT_L002_R1_001
        53.7%
        46%
        12.7
        18855_TTAGGC_L001_R1_001
        56.3%
        47%
        12.9
        18855_TTAGGC_L002_R1_001
        57.2%
        47%
        13.2
        18889_AGTCAA_L001_R1_001
        54.0%
        47%
        10.3
        18889_AGTCAA_L002_R1_001
        53.4%
        47%
        10.2
        18890_AGTTCC_L001_R1_001
        53.8%
        47%
        10.0
        18890_AGTTCC_L002_R1_001
        53.7%
        47%
        9.9
        18891_ATGTCA_L001_R1_001
        56.7%
        47%
        10.9
        18891_ATGTCA_L002_R1_001
        56.6%
        47%
        10.8
        18892_CCGTCC_L001_R1_001
        56.3%
        47%
        11.4
        18892_CCGTCC_L002_R1_001
        55.8%
        47%
        11.3
        18893_GTCCGC_L001_R1_001
        56.3%
        47%
        11.0
        18893_GTCCGC_L002_R1_001
        56.4%
        47%
        11.0
        18894_GTGAAA_L001_R1_001
        55.7%
        47%
        11.0
        18894_GTGAAA_L002_R1_001
        55.6%
        47%
        10.9
        18895_GTGGCC_L001_R1_001
        57.9%
        47%
        13.0
        18895_GTGGCC_L002_R1_001
        57.9%
        47%
        12.9
        Project_18841_index13
        94.9%
        21.6
        Project_18842_index14
        94.4%
        22.3
        Project_18843_index15
        94.2%
        21.0
        Project_18844_index16
        94.1%
        22.1
        Project_18845_index18
        93.5%
        19.0
        Project_18846_index19
        94.3%
        19.6
        Project_18847_index20
        94.0%
        21.0
        Project_18848_index21
        92.5%
        21.0
        Project_18849_index22
        94.5%
        20.4
        Project_18850_index23
        94.9%
        26.2
        Project_18851_index25
        94.6%
        24.6
        Project_18852_index27
        94.4%
        27.9
        Project_18853_index1
        94.5%
        25.7
        Project_18854_index2
        91.3%
        24.5
        Project_18855_index3
        94.1%
        26.5
        Project_18889_index13
        93.1%
        20.6
        Project_18890_index14
        93.4%
        19.9
        Project_18891_index15
        94.0%
        22.0
        Project_18892_index16
        93.6%
        22.9
        Project_18893_index18
        94.5%
        22.4
        Project_18894_index19
        94.5%
        22.3
        Project_18895_index20
        94.0%
        26.2

        RSeQC

        RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput RNA-seq data.

        Read Distribution

        Read Distribution calculates how mapped reads are distributed over genome features.

        loading..

        Gene Body Coverage

        Gene Body Coverage calculates read coverage over gene bodies. This is used to check if reads coverage is uniform and if there is any 5' or 3' bias.

        loading..

        Salmon

        Salmon is a tool for quantifying the expression of transcripts using RNA-seq data.

        loading..

        FastQC

        FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

        Sequence Quality Histograms

        The mean quality value across each base position in the read. See the FastQC help.

        loading..

        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality. See the FastQC help.

        loading..

        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called. See the FastQC help.

        Click a heatmap row to see a line plot for that dataset.

        rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content. See the FastQC help.

        loading..

        Per Base N Content

        The percentage of base calls at each position for which an N was called. See the FastQC help.

        loading..

        Sequence Length Distribution

        All samples have sequences of a single length (50bp).


        Sequence Duplication Levels

        The relative level of duplication found for every sequence. See the FastQC help.

        loading..

        Overrepresented sequences

        The total amount of overrepresented sequences found in each library. See the FastQC help for further information.

        44 samples had less than 1% of reads made up of overrepresented sequences

        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. See the FastQC help. Only samples with ≥ 0.1% adapter contamination are shown.

        No samples found with any adapter contamination > 0.1%