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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 1.15.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 2023-03-06, 10:57 CET based on data in: /media/djn/6TB/SRA/bam/GEO/fastqc


        General Statistics

        Showing 221/221 rows and 3/6 columns.
        Sample Name% Dups% GCM Seqs
        SRR7819727
        16.8%
        49%
        85.2
        SRR7819728
        15.4%
        49%
        75.7
        SRR7819729
        15.5%
        51%
        74.2
        SRR7819730
        17.9%
        51%
        77.4
        SRR7819731
        17.6%
        52%
        75.2
        SRR7819732
        18.4%
        51%
        83.5
        SRR7819733
        25.9%
        51%
        84.3
        SRR7819734
        20.5%
        51%
        80.3
        SRR7819735
        21.1%
        50%
        91.2
        SRR7819736
        17.4%
        50%
        81.4
        SRR7819737
        24.0%
        51%
        78.4
        SRR7819738
        16.5%
        50%
        79.4
        SRR7819739
        16.8%
        49%
        80.5
        SRR7819740
        16.2%
        50%
        87.9
        SRR7819741
        18.5%
        49%
        79.0
        SRR7819742
        18.8%
        50%
        74.1
        SRR7819743
        18.0%
        50%
        75.0
        SRR7819744
        22.3%
        50%
        78.5
        SRR7819745
        14.9%
        50%
        95.6
        SRR7819746
        18.5%
        52%
        92.1
        SRR7819747
        15.6%
        50%
        80.0
        SRR7819748
        18.3%
        51%
        82.2
        SRR7819749
        19.2%
        51%
        79.7
        SRR7819750
        18.3%
        49%
        80.8
        SRR7819751
        19.6%
        52%
        79.3
        SRR7819752
        19.3%
        50%
        73.1
        SRR7819753
        17.2%
        49%
        81.9
        SRR7819754
        17.2%
        48%
        93.3
        SRR7819755
        17.4%
        50%
        99.4
        SRR7819756
        15.7%
        50%
        79.6
        SRR7819757
        15.8%
        49%
        84.4
        SRR7819758
        15.7%
        50%
        75.0
        SRR7819759
        15.4%
        51%
        77.8
        SRR7819760
        15.3%
        49%
        78.3
        SRR7819761
        28.6%
        53%
        93.1
        SRR7819762
        28.8%
        51%
        84.1
        SRR7819763
        24.1%
        49%
        87.4
        SRR7819764
        14.8%
        52%
        87.3
        SRR7819765
        15.1%
        49%
        79.5
        SRR7819766
        15.3%
        49%
        75.5
        SRR7819767
        18.0%
        50%
        83.7
        SRR7819768
        18.2%
        49%
        81.2
        SRR7819769
        15.9%
        49%
        88.4
        SRR7819770
        16.1%
        51%
        87.7
        SRR7819771
        18.2%
        51%
        84.1
        SRR7819772
        16.4%
        49%
        85.3
        SRR7819773
        14.0%
        49%
        85.5
        SRR7819774
        23.2%
        50%
        74.1
        SRR7819775
        16.7%
        49%
        79.6
        SRR7819776
        16.6%
        50%
        74.5
        SRR7819777
        19.5%
        50%
        81.0
        SRR7819778
        17.0%
        49%
        81.5
        SRR7819779
        17.4%
        52%
        85.8
        SRR7819780
        20.2%
        48%
        77.4
        SRR7819781
        15.5%
        50%
        91.3
        SRR7819782
        30.1%
        53%
        97.5
        SRR7819783
        16.3%
        49%
        75.2
        SRR7819784
        19.0%
        50%
        86.2
        SRR7819785
        16.9%
        50%
        82.1
        SRR7819786
        17.9%
        51%
        87.8
        SRR7819787
        16.5%
        49%
        80.6
        SRR7819788
        15.0%
        51%
        79.1
        SRR7819789
        15.7%
        50%
        83.2
        SRR7819790
        16.4%
        49%
        78.4
        SRR7819791
        16.3%
        51%
        85.9
        SRR7819792
        14.4%
        50%
        81.4
        SRR7819793
        16.1%
        50%
        71.2
        SRR7819794
        17.3%
        50%
        76.7
        SRR7819795
        16.5%
        50%
        72.9
        SRR7819796
        25.2%
        52%
        79.4
        SRR7819797
        17.4%
        50%
        82.9
        SRR7819798
        17.4%
        50%
        78.6
        SRR7819799
        15.9%
        50%
        73.8
        SRR7819800
        23.3%
        53%
        85.1
        SRR7819801
        16.8%
        49%
        79.8
        SRR7819802
        17.6%
        50%
        79.0
        SRR7819803
        16.6%
        49%
        79.7
        SRR7819804
        16.6%
        50%
        79.3
        SRR7819805
        16.9%
        51%
        78.4
        SRR7819806
        16.1%
        50%
        73.2
        SRR7819807
        16.4%
        50%
        71.6
        SRR7819808
        14.2%
        50%
        93.5
        SRR7819809
        20.9%
        52%
        82.2
        SRR7819810
        15.3%
        50%
        81.4
        SRR7819811
        22.2%
        53%
        92.4
        SRR7819812
        15.2%
        50%
        72.8
        SRR7819813
        15.1%
        49%
        73.3
        SRR7819814
        23.2%
        52%
        96.4
        SRR7819815
        15.3%
        51%
        72.9
        SRR7819816
        14.3%
        50%
        91.9
        SRR7819817
        15.9%
        51%
        81.5
        SRR7819818
        15.8%
        50%
        81.3
        SRR7819819
        19.5%
        51%
        81.1
        SRR7819820
        17.7%
        50%
        85.1
        SRR7819821
        17.3%
        51%
        79.2
        SRR7819822
        16.8%
        50%
        92.1
        SRR7819823
        16.0%
        50%
        79.0
        SRR7819824
        30.6%
        51%
        101.5
        SRR7819825
        40.9%
        50%
        72.7
        SRR7819826
        35.5%
        50%
        71.3
        SRR7819827
        42.3%
        51%
        81.4
        SRR7819828
        58.1%
        52%
        160.8
        SRR7819829
        39.4%
        51%
        64.7
        SRR7819830
        44.4%
        50%
        120.3
        SRR7819831
        35.8%
        51%
        85.2
        SRR7819832
        40.3%
        50%
        76.9
        SRR7819833
        26.7%
        50%
        106.5
        SRR7819834
        26.0%
        51%
        73.2
        SRR7819835
        43.1%
        53%
        105.4
        SRR7819836
        39.4%
        49%
        73.6
        SRR7819837
        34.1%
        51%
        92.7
        SRR7819838
        27.0%
        53%
        67.9
        SRR7819839
        36.9%
        50%
        69.8
        SRR7819840
        39.4%
        49%
        86.9
        SRR7819841
        40.1%
        51%
        78.5
        SRR7819842
        38.5%
        50%
        76.3
        SRR7819843
        40.8%
        49%
        89.8
        SRR7819844
        37.9%
        49%
        90.3
        SRR7819845
        36.5%
        51%
        73.5
        SRR7819846
        38.9%
        49%
        79.8
        SRR7819847
        25.0%
        51%
        92.7
        SRR7819848
        43.1%
        48%
        65.1
        SRR7819849
        44.9%
        50%
        99.9
        SRR7819851
        25.1%
        52%
        14.5
        SRR7819852
        40.0%
        50%
        89.7
        SRR7819853
        35.7%
        50%
        107.1
        SRR7819854
        24.3%
        51%
        73.6
        SRR7819855
        37.7%
        50%
        90.2
        SRR7819856
        38.5%
        50%
        87.0
        SRR7819857
        34.6%
        52%
        85.2
        SRR7819858
        33.9%
        50%
        78.5
        SRR7819859
        37.1%
        50%
        83.5
        SRR7819860
        29.6%
        50%
        86.8
        SRR7819861
        37.8%
        50%
        70.5
        SRR7819862
        35.2%
        49%
        131.3
        SRR7819863
        30.1%
        51%
        97.4
        SRR7819864
        37.9%
        51%
        71.1
        SRR7819865
        38.8%
        50%
        103.7
        SRR7819866
        25.0%
        51%
        79.4
        SRR7819867
        28.2%
        50%
        84.0
        SRR7819868
        39.6%
        51%
        72.1
        SRR7819869
        39.1%
        49%
        90.8
        SRR7819870
        37.2%
        50%
        77.2
        SRR7819871
        27.4%
        50%
        89.5
        SRR7819872
        38.0%
        50%
        76.3
        SRR7819873
        40.0%
        49%
        88.5
        SRR7819874
        28.3%
        49%
        112.9
        SRR7819875
        38.1%
        49%
        73.3
        SRR7819876
        28.4%
        50%
        68.0
        SRR7819877
        22.2%
        49%
        77.2
        SRR7819878
        42.1%
        50%
        83.1
        SRR7819879
        37.7%
        49%
        88.1
        SRR7819880
        38.4%
        51%
        81.5
        SRR7819881
        42.3%
        52%
        83.0
        SRR7819882
        38.1%
        50%
        76.0
        SRR7819883
        38.3%
        50%
        84.3
        SRR7819884
        27.8%
        50%
        87.8
        SRR7819885
        26.3%
        50%
        90.0
        SRR7819886
        26.6%
        50%
        109.8
        SRR7819887
        31.8%
        52%
        96.8
        SRR7819888
        27.2%
        50%
        74.5
        SRR7819889
        26.7%
        50%
        119.8
        SRR7819890
        36.9%
        52%
        89.8
        SRR7819891
        27.1%
        51%
        73.8
        SRR7819892
        31.7%
        51%
        79.9
        SRR7819893
        26.3%
        51%
        106.2
        SRR7819894
        36.3%
        48%
        91.3
        SRR7819895
        42.8%
        49%
        95.2
        SRR7819896
        34.8%
        50%
        73.8
        SRR7819897
        25.1%
        50%
        92.5
        SRR7819898
        26.7%
        51%
        118.5
        SRR7819899
        28.1%
        49%
        65.6
        SRR7819900
        28.4%
        51%
        91.5
        SRR7819901
        36.1%
        51%
        142.3
        SRR7819902
        25.3%
        49%
        108.2
        SRR7819903
        30.1%
        49%
        76.8
        SRR7819904
        26.6%
        51%
        112.5
        SRR7819905
        21.7%
        50%
        84.0
        SRR7819906
        25.0%
        51%
        94.7
        SRR7819907
        30.5%
        51%
        72.6
        SRR7819908
        32.4%
        50%
        77.9
        SRR7819909
        28.5%
        50%
        111.8
        SRR7819910
        47.7%
        51%
        179.9
        SRR7819911
        31.0%
        52%
        91.0
        SRR7819912
        25.9%
        51%
        66.5
        SRR7819913
        30.2%
        48%
        125.6
        SRR7819914
        29.9%
        49%
        123.4
        SRR7819915
        23.4%
        52%
        79.0
        SRR7819916
        30.8%
        49%
        80.9
        SRR7819917
        40.5%
        52%
        84.7
        SRR7819918
        31.1%
        49%
        85.2
        SRR7819919
        27.9%
        49%
        67.5
        SRR7819920
        30.6%
        51%
        80.5
        SRR7819921
        35.8%
        55%
        90.6
        SRR7819922
        27.5%
        49%
        105.1
        SRR7819923
        31.1%
        51%
        97.1
        SRR7819924
        28.8%
        50%
        72.2
        SRR7819925
        30.1%
        51%
        84.6
        SRR7819926
        30.5%
        50%
        87.9
        SRR7819927
        43.1%
        54%
        124.5
        SRR7819928
        37.7%
        51%
        104.1
        SRR7819929
        28.8%
        49%
        72.2
        SRR7819930
        23.5%
        49%
        64.8
        SRR7819931
        41.0%
        51%
        114.8
        SRR7819932
        24.6%
        51%
        80.5
        SRR7819933
        26.8%
        50%
        94.3
        SRR7819934
        25.7%
        50%
        149.5
        SRR7819935
        37.2%
        52%
        93.8
        SRR7819936
        26.2%
        51%
        81.4
        SRR7819937
        27.2%
        50%
        92.7
        SRR7819938
        26.3%
        51%
        94.0
        SRR7819939
        23.3%
        52%
        100.6
        SRR7819940
        20.7%
        51%
        87.9
        SRR7819941
        34.1%
        51%
        92.6
        SRR7819942
        32.6%
        52%
        84.4
        SRR7819943
        42.6%
        52%
        182.6
        SRR7819944
        69.8%
        50%
        178.6
        SRR7819945
        31.6%
        52%
        72.1
        SRR7819946
        26.2%
        50%
        71.8
        SRR7819947
        31.6%
        51%
        71.3
        SRR7819948
        20.7%
        49%
        71.7

        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.

        loading..

        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.

        loading..

        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.

        loading..

        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.

        loading..

        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.

        loading..

        Sequence Length Distribution

        All samples have sequences of a single length (101bp).

        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.

        loading..

        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.

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        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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