mca-cleaning

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        Note that additional data was saved in mca-cleaning_multiqc_report_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 1.10.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

        mca-cleaning

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

        Report generated on 2021-05-17, 06:35 based on data in: /share/workshop/mca_workshop/msettles/01-HTS_Preproc


        HTStream

        HTStream quality control and processing pipeline for High Throughput Sequencing data.

        Processing Overview

        General statistics from the HTStream pipeline.


        Preprocessing Statistics

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        Fragment Reduction

        Provides scaled statistics collected throughout the preprocessing pipeline, highlighting variable statistics across experiment.

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        Basepair Reduction

        Provides scaled statistics collected throughout the preprocessing pipeline, highlighting variable statistics across experiment.

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        hts_Stats

        Generates a JSON formatted file containing a set of statistical measures about the input read data.

        Showing 8/8 rows and 6/6 columns.
        Sample Name% PE% R1 Q30% R2 Q30GC ContentN ContentNotes
        Bs1_2C_A0
        100.00%
        87.69%
        64.28%
        54.76%
        0.0000%
        Initial Stats
        Bs1_2C_A5
        100.00%
        87.96%
        64.30%
        54.87%
        0.0000%
        Initial Stats
        Bs1_2C_B0
        100.00%
        87.86%
        64.19%
        54.78%
        0.0000%
        Initial Stats
        Bs1_2C_B5
        100.00%
        87.73%
        60.73%
        54.77%
        0.0000%
        Initial Stats
        Bs1_2C_C0
        100.00%
        88.03%
        64.96%
        54.70%
        0.0000%
        Initial Stats
        Bs1_2C_C5
        100.00%
        87.94%
        64.88%
        54.62%
        0.0000%
        Initial Stats
        Bs1_2C_D0
        100.00%
        87.99%
        63.37%
        54.84%
        0.0000%
        Initial Stats
        Bs1_2C_D5
        100.00%
        87.97%
        65.61%
        54.65%
        0.0000%
        Initial Stats

        Read Lengths: Paired End

        Distribution of read lengths for each sample.

        Notice: Each sample has a uniform read length distribution.
        Showing 8/8 rows and 2/2 columns.
        Sample NameR1 Read LengthsR2 Read Lengths
        Bs1_2C_A0
        301
        301
        Bs1_2C_A5
        301
        301
        Bs1_2C_B0
        301
        301
        Bs1_2C_B5
        301
        301
        Bs1_2C_C0
        301
        301
        Bs1_2C_C5
        301
        301
        Bs1_2C_D0
        301
        301
        Bs1_2C_D5
        301
        301

        Base by Cycle: Paired End

        Provides a measure of the uniformity of a distribution. The higher the average is at a certain position, the more unequal the base pair composition. N's are excluded from this calculation.

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        Quality by Cycle: Paired End

        Mean quality score for each position along the read. Sample is colored red if less than 60% of bps have mean score of at least Q30, orange if between 60% and 80%, and green otherwise.

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        hts_Overlapper

        Attempts to overlap paired end reads to produce the original fragment, trims adapters, and can correct sequencing errors.

        Showing 8/8 rows and 2/2 columns.
        Sample Name% OverlappedNotes
        Bs1_2C_A0
        98.28%
        Overlap reads
        Bs1_2C_A5
        98.20%
        Overlap reads
        Bs1_2C_B0
        98.39%
        Overlap reads
        Bs1_2C_B5
        97.76%
        Overlap reads
        Bs1_2C_C0
        98.56%
        Overlap reads
        Bs1_2C_C5
        98.34%
        Overlap reads
        Bs1_2C_D0
        98.16%
        Overlap reads
        Bs1_2C_D5
        98.52%
        Overlap reads

        Overlapper: Overlap Composition

        Plots the quantities of insert types for each sample.

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        Overlapper: Overlapped Lengths

        Plots the lengths of paired end read overlaps.

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        hts_Primers

        Identifies primer sequences located on the 5' ends of R1 and R2, or 5' and 3' end of SE reads.

        Showing 8/8 rows and 3/3 columns.
        Sample Name% Bp LostReads FlippedNotes
        Bs1_2C_A0
        16.7242%
        49729
        Single set V3V4 primers
        Bs1_2C_A5
        16.9455%
        47539
        Single set V3V4 primers
        Bs1_2C_B0
        16.7234%
        44384
        Single set V3V4 primers
        Bs1_2C_B5
        17.3585%
        34183
        Single set V3V4 primers
        Bs1_2C_C0
        16.6489%
        31868
        Single set V3V4 primers
        Bs1_2C_C5
        16.8561%
        27089
        Single set V3V4 primers
        Bs1_2C_D0
        16.9417%
        40076
        Single set V3V4 primers
        Bs1_2C_D5
        16.6015%
        29558
        Single set V3V4 primers

        Primers: Primer Counts

        Heatmap indicating abundance of primer combinations.

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        hts_NTrimmer

        Trims reads to the longest subsequence that contains no N's.

        Notice: No basepairs were trimmed from any sample.

        hts_LengthFilter

        Discards reads below a minimum length threshold.

        Showing 8/8 rows and 2/2 columns.
        Sample Name% SE LostNotes
        Bs1_2C_A0
        0.10%
        Filter sequences 100 - 400
        Bs1_2C_A5
        0.04%
        Filter sequences 100 - 400
        Bs1_2C_B0
        0.05%
        Filter sequences 100 - 400
        Bs1_2C_B5
        0.05%
        Filter sequences 100 - 400
        Bs1_2C_C0
        0.08%
        Filter sequences 100 - 400
        Bs1_2C_C5
        0.03%
        Filter sequences 100 - 400
        Bs1_2C_D0
        0.05%
        Filter sequences 100 - 400
        Bs1_2C_D5
        0.05%
        Filter sequences 100 - 400

        hts_Stats 2

        Generates a JSON formatted file containing a set of statistical measures about the input read data.

        Showing 8/8 rows and 8/8 columns.
        Sample Name% PE% SE% R1 Q30% R2 Q30% SE Q30GC ContentN ContentNotes
        Bs1_2C_A0
        0.88%
        99.12%
        36.71%
        42.82%
        97.92%
        54.60%
        0.0000%
        Bs1_2C_A5
        0.87%
        99.13%
        34.85%
        42.70%
        97.97%
        54.75%
        0.0000%
        Bs1_2C_B0
        0.80%
        99.20%
        35.27%
        42.14%
        97.93%
        54.64%
        0.0000%
        Bs1_2C_B5
        1.05%
        98.95%
        37.90%
        40.36%
        97.50%
        54.58%
        0.0000%
        Bs1_2C_C0
        0.76%
        99.24%
        38.88%
        41.89%
        98.04%
        54.54%
        0.0000%
        Bs1_2C_C5
        0.76%
        99.24%
        34.91%
        43.30%
        98.02%
        54.46%
        0.0000%
        Bs1_2C_D0
        0.92%
        99.08%
        35.28%
        42.57%
        97.83%
        54.69%
        0.0000%
        Bs1_2C_D5
        0.73%
        99.27%
        34.70%
        43.26%
        98.09%
        54.51%
        0.0000%

        Read Lengths: Paired End

        Distribution of read lengths for each sample.

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        Base by Cycle: Paired End

        Provides a measure of the uniformity of a distribution. The higher the average is at a certain position, the more unequal the base pair composition. N's are excluded from this calculation.

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        Quality by Cycle: Paired End

        Mean quality score for each position along the read. Sample is colored red if less than 60% of bps have mean score of at least Q30, orange if between 60% and 80%, and green otherwise.

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        Read Lengths: Single End

        Distribution of read lengths for each sample.

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        Base by Cycle: Single End

        Provides a measure of the uniformity of a distribution. The higher the average is at a certain position, the more unequal the base pair composition. N's are excluded from this calculation.

        loading..

        Quality by Cycle: Single End

        Mean quality score for each position along the read. Sample is colored red if less than 60% of bps have mean score of at least Q30, orange if between 60% and 80%, and green otherwise.

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