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+test_R1_val_1.fq.gz FastQC Report
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diff --git a/software/fastqc/test/output/test_R2_fastqc.html b/software/fastqc/test/output/test_R2_fastqc.html
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+test_R2.fastq.gz FastQC Report
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+test_R2_val_2.fq.gz FastQC Report
+ 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.
+
+
+
+
+
+
+
+
+
+
Loading report..
+
+
+
Report generated on 2020-03-18, 10:46 based on data in:
+ /bi/home/fkrueger/VersionControl/nf-core-modules/tools/multiqc/test/work/52/07836c4fe43e822e375798bf42c0e4
+
+
Uncheck the tick box to hide columns. Click and drag the handle on the left to change order.
+
+
+
+
+
+
+
+
Sort
+
Visible
+
Group
+
Column
+
Description
+
ID
+
Scale
+
+
+
+
+
+
||
+
+
+
+
Bowtie 2
+
% Aligned
+
overall alignment rate
+
overall_alignment_rate
+
None
+
+
+
||
+
+
+
+
Cutadapt
+
% Trimmed
+
% Total Base Pairs trimmed
+
percent_trimmed
+
None
+
+
+
||
+
+
+
+
FastQC
+
% Dups
+
% Duplicate Reads
+
percent_duplicates
+
None
+
+
+
||
+
+
+
+
FastQC
+
% GC
+
Average % GC Content
+
percent_gc
+
None
+
+
+
||
+
+
+
+
FastQC
+
Length
+
Average Sequence Length (bp)
+
avg_sequence_length
+
None
+
+
+
||
+
+
+
+
FastQC
+
% Failed
+
Percentage of modules failed in FastQC report (includes those not plotted here)
+
percent_fails
+
None
+
+
+
||
+
+
+
+
FastQC
+
M Seqs
+
Total Sequences (millions)
+
total_sequences
+
read_count
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
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.
+
+
+
+
+
+
+
loading..
+
+
+
+
+
+
+
+
+
+
+
+
+
Cutadapt
+
Cutadapt is a tool to find and remove adapter sequences, primers, poly-Atails and other types of unwanted sequence from your high-throughput sequencing reads.
+
+
+
+
+
+
+
This plot shows the number of reads with certain lengths of adapter trimmed.
+ Obs/Exp shows the raw counts divided by the number expected due to sequencing errors. A defined peak
+ may be related to adapter length. See the
+ cutadapt documentation
+ for more information on how these numbers are generated.
+
+
+
+
+
+
+
+
loading..
+
+
+
+
+
+
+
+
+
+
+
+
+
FastQ Screen
+
FastQ Screen allows you to screen a library of sequences in FastQ format against a set of sequence databases so you can see if the composition of the library matches with what you expect.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
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).
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.
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.
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.
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.
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
+
+
+
+
The distribution of fragment sizes (read lengths) found.
+ See the FastQC help
+
+
+
loading..
+
+
+
+
+
+
+
+
+
+
+
+ Sequence Duplication Levels
+
+
+
+
+
+
The relative level of duplication found for every sequence.
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.
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.
+
+
+
4 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.
+
+
+
+
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.
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.
+
+
+
loading..
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
Plot Table Data
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
Regex Help
+
+
+
Toolbox search strings can behave as regular expressions (regexes). Click a button below to see an example of it in action. Try modifying them yourself in the text box.
FastQC Report![[OK]](data:image/png;base64,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)
Basic Statistics
![[FAIL]](data:image/png;base64,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)
Per base sequence content
![[WARN]](data:image/png;base64,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)
Overrepresented sequences
+ 
+