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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_hg38_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 1.9

        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

        These samples were run by seq2science v0.4.3, a tool for easy preprocessing of NGS data.

        Take a look at our docs for info about how to use this report to the fullest.

        Contact E-mail
        Jsmits@science.ru.nl
        Workflow
        ATAC
        Date
        February 18, 2021

        Report generated on 2021-02-19, 06:40 based on data in:

        Change sample names:

        General Statistics

        Showing 14/14 rows and 15/32 columns.
        Sample Name% DuplicationGC content% PF% AdapterInsert Size% Dups% MappedM Total seqs% Proper PairsM Total seqs% AssignedGenome coverageM Genome readsM MT genome readsTreatment Redundancy
        Dombi-23_ATAC_1
        19.9%
        47.5%
        96.4%
        2.8%
        152 bp
        21.6%
        98.7%
        15.7
        99.6%
        8.0
        7.2%
        0.2 X
        11.9
        3.7
        0.01
        Dombi-23_ATAC_2
        0.3%
        46.7%
        85.2%
        5.3%
        75 bp
        0.5%
        97.6%
        1.5
        98.8%
        1.0
        15.4%
        0.0 X
        1.1
        0.4
        0.01
        GSM2400260
        11.1%
        47.7%
        88.3%
        1.9%
        94 bp
        19.3%
        94.1%
        318.4
        99.1%
        207.5
        25.4%
        3.4 X
        291.7
        7.8
        0.09
        GSM2400261
        23.0%
        46.9%
        94.4%
        11.0%
        41 bp
        28.5%
        78.8%
        305.9
        96.4%
        128.2
        23.1%
        2.5 X
        214.6
        26.6
        0.06
        GSM4728093
        19.2%
        46.2%
        97.8%
        64.1%
        112 bp
        21.2%
        98.6%
        173.4
        99.7%
        72.4
        48.7%
        3.9 X
        112.6
        58.5
        0.15
        GSM4728094
        19.1%
        46.2%
        98.4%
        61.4%
        132 bp
        21.8%
        98.0%
        198.3
        99.8%
        77.3
        56.5%
        4.3 X
        123.3
        71.4
        0.19
        GSM736582
        9.4%
        50.8%
        94.7%
        3.3%
        6.7%
        95.9%
        31.7
        0.0%
        17.1
        22.0%
        0.3 X
        25.9
        4.4
        0.00
        PKC19_ATAC_1
        33.2%
        48.1%
        99.1%
        0.3%
        165 bp
        34.7%
        99.6%
        46.7
        97.5%
        25.6
        21.5%
        0.5 X
        43.5
        3.0
        0.03
        PKC19_ATAC_2
        64.8%
        49.4%
        99.1%
        0.4%
        167 bp
        68.6%
        99.8%
        57.6
        99.7%
        15.9
        30.8%
        0.7 X
        54.9
        2.5
        0.04
        PKC19_ATAC_3
        56.9%
        49.0%
        99.0%
        0.3%
        165 bp
        59.9%
        99.8%
        30.0
        99.4%
        10.6
        25.7%
        0.4 X
        28.7
        1.2
        0.03
        PRIM_LSC_ATAC_1
        64.9%
        48.8%
        99.1%
        0.3%
        171 bp
        68.6%
        99.8%
        23.7
        99.7%
        6.7
        17.5%
        0.3 X
        23.2
        0.4
        0.02
        PRIM_LSC_ATAC_2
        58.2%
        48.5%
        99.1%
        0.2%
        170 bp
        61.3%
        99.7%
        29.0
        99.8%
        10.1
        20.5%
        0.3 X
        28.2
        0.6
        0.02
        PRIM_LSC_ATAC_3
        44.9%
        48.6%
        98.0%
        0.3%
        164 bp
        63.5%
        99.0%
        166.9
        96.4%
        53.5
        42.4%
        1.9 X
        158.5
        6.8
        0.11
        PRIM_LSC_ATAC_4
        5.4%
        49.3%
        98.3%
        0.9%
        94 bp
        6.1%
        99.7%
        16.6
        99.9%
        12.9
        28.6%
        0.2 X
        15.2
        1.4
        0.02

        fastp

        fastp An ultra-fast all-in-one FASTQ preprocessor (QC, adapters, trimming, filtering, splitting...)

        Filtered Reads

        Filtering statistics of sampled reads.

        loading..

        Duplication Rates

        Duplication rates of sampled reads.

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        Insert Sizes

        Insert size estimation of sampled reads.

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        Sequence Quality

        Average sequencing quality over each base of all reads.

        loading..

        GC Content

        Average GC content over each base of all reads.

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        N content

        Average N content over each base of all reads.

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        Picard

        Picard is a set of Java command line tools for manipulating high-throughput sequencing data.

        Insert Size

        Plot shows the number of reads at a given insert size. Reads with different orientations are summed.

        loading..

        Mark Duplicates

        Number of reads, categorised by duplication state. Pair counts are doubled - see help text for details.

        The table in the Picard metrics file contains some columns referring read pairs and some referring to single reads.

        To make the numbers in this plot sum correctly, values referring to pairs are doubled according to the scheme below:

        • READS_IN_DUPLICATE_PAIRS = 2 * READ_PAIR_DUPLICATES
        • READS_IN_UNIQUE_PAIRS = 2 * (READ_PAIRS_EXAMINED - READ_PAIR_DUPLICATES)
        • READS_IN_UNIQUE_UNPAIRED = UNPAIRED_READS_EXAMINED - UNPAIRED_READ_DUPLICATES
        • READS_IN_DUPLICATE_PAIRS_OPTICAL = 2 * READ_PAIR_OPTICAL_DUPLICATES
        • READS_IN_DUPLICATE_PAIRS_NONOPTICAL = READS_IN_DUPLICATE_PAIRS - READS_IN_DUPLICATE_PAIRS_OPTICAL
        • READS_IN_DUPLICATE_UNPAIRED = UNPAIRED_READ_DUPLICATES
        • READS_UNMAPPED = UNMAPPED_READS
        loading..

        SamTools pre-sieve

        Samtools is a suite of programs for interacting with high-throughput sequencing data.

        The pre-sieve statistics are quality metrics measured before applying (optional) minimum mapping quality, blacklist removal, mitochondrial read removal, and tn5 shift.

        Percent Mapped

        Alignment metrics from samtools stats; mapped vs. unmapped reads.

        For a set of samples that have come from the same multiplexed library, similar numbers of reads for each sample are expected. Large differences in numbers might indicate issues during the library preparation process. Whilst large differences in read numbers may be controlled for in downstream processings (e.g. read count normalisation), you may wish to consider whether the read depths achieved have fallen below recommended levels depending on the applications.

        Low alignment rates could indicate contamination of samples (e.g. adapter sequences), low sequencing quality or other artefacts. These can be further investigated in the sequence level QC (e.g. from FastQC).

        loading..

        Alignment metrics

        This module parses the output from samtools stats. All numbers in millions.

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        SamTools post-sieve

        Samtools is a suite of programs for interacting with high-throughput sequencing data.

        The post-sieve statistics are quality metrics measured after applying (optional) minimum mapping quality, blacklist removal, mitochondrial read removal, and tn5 shift.

        Percent Mapped

        Alignment metrics from samtools stats; mapped vs. unmapped reads.

        For a set of samples that have come from the same multiplexed library, similar numbers of reads for each sample are expected. Large differences in numbers might indicate issues during the library preparation process. Whilst large differences in read numbers may be controlled for in downstream processings (e.g. read count normalisation), you may wish to consider whether the read depths achieved have fallen below recommended levels depending on the applications.

        Low alignment rates could indicate contamination of samples (e.g. adapter sequences), low sequencing quality or other artefacts. These can be further investigated in the sequence level QC (e.g. from FastQC).

        loading..

        Alignment metrics

        This module parses the output from samtools stats. All numbers in millions.

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        deepTools

        deepTools is a suite of tools to process and analyze deep sequencing data.

        PCA plot

        PCA plot with the top two principal components calculated based on genome-wide distribution of sequence reads

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        Fingerprint plot

        Signal fingerprint according to plotFingerprint

        loading..

        Read Distribution Profile after Annotation

        Accumulated view of the distribution of sequence reads related to the closest annotated gene. All annotated genes have been normalized to the same size.

        • Green: -2.0Kb upstream of gene to TSS
        • Yellow: TSS to TES
        • Pink: TES to 0.5Kb downstream of gene
        loading..

        macs2_frips

        Subread featureCounts is a highly efficient general-purpose read summarization program that counts mapped reads for genomic features such as genes, exons, promoter, gene bodies, genomic bins and chromosomal locations.

        loading..

        Pileup (BAM) Spearman correlation

        Spearman correlation plot generated by deeptools. Spearman correlation is a non-parametric (distribution-free) method, and assesses the monotonicity of the relationship.

        Pileup (BAM) Pearson correlation

        Pearson correlation plot generated by deeptools. Pearson correlation is a parametric (lots of assumptions, e.g. normality and homoscedasticity) method, and assesses the linearity of the relationship.

        Peak feature distribution (macs2)

        Figure generated by chipseeker

        Distribution of peak locations relative to TSS (macs2)

        Figure generated by chipseeker

        Samples & Config

        The samples file used for this run:

        sample assembly descriptive_name cell_type
        Dombi-23_ATAC_1 hg38 KC1 KC
        Dombi-23_ATAC_2 hg38 KC2 KC
        PKC19_ATAC_1 hg38 KC3 KC
        PKC19_ATAC_2 hg38 KC4 KC
        PKC19_ATAC_3 hg38 KC5 KC
        PRIM_LSC_ATAC_1 hg38 LSC1 LSC
        PRIM_LSC_ATAC_2 hg38 LSC2 LSC
        PRIM_LSC_ATAC_3 hg38 LSC3 LSC
        PRIM_LSC_ATAC_4 hg38 LSC4 LSC
        GSM4728093 hg38 LSC5 LSC
        GSM4728094 hg38 LSC6 LSC
        GSM736582 hg38 H1_ESC1 ESC
        GSM2400260 hg38 H9_ESC1 ESC
        GSM2400261 hg38 H9_ESC2 ESC

        The config file used for this run: 
        # tab-separated file of the samples
samples: samples.tsv

# pipeline file locations
result_dir: ./results  # where to store results
genome_dir: ../genomes  # where to look for or download the genomes
fastq_dir: ../fastq_dir  # where to look for or download the fastqs

# contact info for multiqc report and trackhub
email: Jsmits@science.ru.nl

# produce a UCSC trackhub?
create_trackhub: True

# how to handle replicates
biolocal_replicates: keep  # change to "keep" to not combine them
technical_replicates: merge    # change to "keep" to not combine them

# which trimmer to use
trimmer: fastp

# which aligner to use
aligner: bwa-mem2

# filtering after alignment
remove_blacklist: True
remove_mito: True
tn5_shift: True
min_mapping_quality: 30
only_primary_align: True

# peak callers (supported peak callers are macs2, and genrich)
peak_caller:
  macs2:
      --shift -100 --extsize 200 --nomodel --keep-dup 1 --buffer-size 10000
#  genrich:
#      -y -j -r

        MultiQC v1.9 - Written by Phil Ewels, available on GitHub.

        This report uses HighCharts, jQuery, jQuery UI, Bootstrap, FileSaver.js and clipboard.js.