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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 1.8

        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 2021-06-29, 11:15 based on data in: /gscratch/scrubbed/samwhite/outputs/20210629_cvir_fastqc_yaamini_rnaseq-wgbs


        General Statistics

        Showing 104/104 rows and 4/5 columns.
        Sample Name% Dups% GCLengthM Seqs
        12M_R1_val_1
        26.8%
        20%
        124 bp
        192.8
        12M_R2_val_2
        25.2%
        20%
        124 bp
        192.8
        13M_R1_val_1
        28.1%
        20%
        122 bp
        217.3
        13M_R2_val_2
        26.6%
        20%
        122 bp
        217.3
        16F_R1_val_1
        25.0%
        21%
        119 bp
        184.2
        16F_R2_val_2
        23.5%
        22%
        119 bp
        184.2
        19F_R1_val_1
        26.5%
        21%
        119 bp
        199.7
        19F_R2_val_2
        24.9%
        21%
        119 bp
        199.7
        22F_R1_val_1
        21.7%
        19%
        127 bp
        125.9
        22F_R2_val_2
        19.7%
        19%
        127 bp
        125.9
        23M_R1_val_1
        28.6%
        20%
        123 bp
        211.6
        23M_R2_val_2
        26.7%
        20%
        123 bp
        211.6
        29F_R1_val_1
        22.0%
        19%
        126 bp
        137.6
        29F_R2_val_2
        21.3%
        20%
        126 bp
        137.6
        31M_R1_val_1
        22.6%
        20%
        121 bp
        141.8
        31M_R2_val_2
        22.2%
        21%
        121 bp
        141.8
        35F_R1_val_1
        22.1%
        20%
        124 bp
        159.2
        35F_R2_val_2
        23.3%
        20%
        124 bp
        159.2
        36F_R1_val_1
        24.2%
        19%
        125 bp
        163.4
        36F_R2_val_2
        23.3%
        19%
        125 bp
        163.4
        39F_R1_val_1
        23.7%
        20%
        123 bp
        156.6
        39F_R2_val_2
        22.5%
        20%
        123 bp
        156.6
        3F_R1_val_1
        27.1%
        21%
        121 bp
        175.3
        3F_R2_val_2
        26.0%
        21%
        121 bp
        175.3
        41F_R1_val_1
        19.2%
        19%
        120 bp
        113.0
        41F_R2_val_2
        18.2%
        20%
        120 bp
        113.0
        44F_R1_val_1
        30.8%
        19%
        126 bp
        308.9
        44F_R2_val_2
        29.2%
        19%
        126 bp
        308.9
        48M_R1_val_1
        27.6%
        21%
        117 bp
        202.1
        48M_R2_val_2
        27.5%
        21%
        117 bp
        202.1
        50F_R1_val_1
        21.6%
        18%
        128 bp
        147.2
        50F_R2_val_2
        20.2%
        19%
        128 bp
        147.2
        52F_R1_val_1
        24.2%
        18%
        128 bp
        174.2
        52F_R2_val_2
        21.0%
        19%
        128 bp
        174.2
        53F_R1_val_1
        23.9%
        19%
        126 bp
        171.1
        53F_R2_val_2
        23.0%
        19%
        126 bp
        171.1
        54F_R1_val_1
        30.2%
        19%
        126 bp
        198.5
        54F_R2_val_2
        28.4%
        20%
        126 bp
        198.5
        59M_R1_val_1
        22.8%
        21%
        113 bp
        140.0
        59M_R2_val_2
        21.6%
        21%
        113 bp
        140.0
        64M_R1_val_1
        25.6%
        19%
        124 bp
        168.6
        64M_R2_val_2
        24.3%
        19%
        124 bp
        168.6
        6M_R1_val_1
        22.5%
        22%
        118 bp
        156.8
        6M_R2_val_2
        24.0%
        22%
        118 bp
        156.8
        76F_R1_val_1
        24.4%
        19%
        125 bp
        155.3
        76F_R2_val_2
        23.5%
        19%
        125 bp
        155.3
        77F_R1_val_1
        26.4%
        19%
        123 bp
        183.3
        77F_R2_val_2
        25.6%
        20%
        123 bp
        183.3
        7M_R1_val_1
        24.1%
        19%
        126 bp
        144.2
        7M_R2_val_2
        22.3%
        20%
        126 bp
        144.2
        9M_R1_val_1
        22.8%
        20%
        126 bp
        135.5
        9M_R2_val_2
        22.0%
        20%
        126 bp
        135.5
        S12M_R1
        18.6%
        44%
        151 bp
        34.3
        S12M_R2
        11.8%
        44%
        151 bp
        34.3
        S13M_R1
        29.5%
        51%
        151 bp
        29.5
        S13M_R2
        24.8%
        50%
        151 bp
        29.5
        S16F_R1
        52.7%
        43%
        151 bp
        24.2
        S16F_R2
        22.3%
        44%
        151 bp
        24.2
        S19F_R1
        53.9%
        43%
        151 bp
        24.3
        S19F_R2
        23.5%
        43%
        151 bp
        24.3
        S22F_R1
        55.0%
        43%
        151 bp
        28.5
        S22F_R2
        22.7%
        43%
        151 bp
        28.5
        S23M_R1
        20.5%
        45%
        151 bp
        40.5
        S23M_R2
        13.3%
        45%
        151 bp
        40.5
        S29F_R1
        40.0%
        42%
        151 bp
        22.6
        S29F_R2
        16.0%
        42%
        151 bp
        22.6
        S31M_R1
        10.5%
        39%
        151 bp
        20.4
        S31M_R2
        4.8%
        40%
        151 bp
        20.4
        S35F_R1
        51.2%
        43%
        151 bp
        20.3
        S35F_R2
        21.7%
        43%
        151 bp
        20.3
        S36F_R1
        50.0%
        42%
        151 bp
        21.7
        S36F_R2
        20.2%
        42%
        151 bp
        21.7
        S39F_R1
        55.4%
        43%
        151 bp
        24.5
        S39F_R2
        22.6%
        43%
        151 bp
        24.5
        S3F_R1
        51.7%
        43%
        151 bp
        22.1
        S3F_R2
        22.9%
        42%
        151 bp
        22.1
        S41F_R1
        45.4%
        43%
        151 bp
        22.6
        S41F_R2
        20.0%
        43%
        151 bp
        22.6
        S44F_R1
        49.2%
        44%
        151 bp
        25.0
        S44F_R2
        23.2%
        44%
        151 bp
        25.0
        S48M_R1
        30.1%
        49%
        151 bp
        67.4
        S48M_R2
        22.8%
        48%
        151 bp
        67.4
        S50F_R1
        50.9%
        43%
        151 bp
        20.3
        S50F_R2
        24.2%
        43%
        151 bp
        20.3
        S52F_R1
        38.3%
        42%
        151 bp
        23.7
        S52F_R2
        15.3%
        42%
        151 bp
        23.7
        S53F_R1
        51.1%
        43%
        151 bp
        23.2
        S53F_R2
        23.6%
        43%
        151 bp
        23.2
        S54F_R1
        45.0%
        43%
        151 bp
        23.2
        S54F_R2
        19.8%
        43%
        151 bp
        23.2
        S59M_R1
        31.6%
        41%
        151 bp
        21.9
        S59M_R2
        12.9%
        41%
        151 bp
        21.9
        S64M_R1
        39.4%
        42%
        151 bp
        23.9
        S64M_R2
        23.7%
        43%
        151 bp
        23.9
        S6M_R1
        25.4%
        48%
        151 bp
        43.8
        S6M_R2
        20.5%
        48%
        151 bp
        43.8
        S76F_R1
        54.7%
        44%
        151 bp
        26.1
        S76F_R2
        27.6%
        44%
        151 bp
        26.1
        S77F_R1
        57.9%
        44%
        151 bp
        27.9
        S77F_R2
        27.4%
        44%
        151 bp
        27.9
        S7M_R1
        18.9%
        45%
        151 bp
        29.4
        S7M_R2
        12.2%
        45%
        151 bp
        29.4
        S9M_R1
        22.1%
        47%
        151 bp
        37.6
        S9M_R2
        15.2%
        46%
        151 bp
        37.6

        FastQC

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

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Quality Histograms

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

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Base Sequence Content

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

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample 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.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Base N Content

        The percentage of base calls at each position for which an N was called.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Length Distribution

        The distribution of fragment sizes (read lengths) found. See the FastQC help

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Duplication Levels

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (eg PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Overrepresented sequences

        The total amount of overrepresented sequences found in each library.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as over represented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all of the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

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        Status Checks

        Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

        Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

        In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

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