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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_GRCg6a_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 1.11

        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 v0.6.1, 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.

        Workflow
        atac-seq
        Date
        January 11, 2022
        Project
        atac
        Contact E-mail
        tessa.dewijs2@ru.nl

        Report generated on 2022-01-13, 13:54 based on data in:

        Change sample names:

        General Statistics

        Showing 34/34 rows and 16/33 columns.
        Sample Name% DuplicationGC content% PF% AdapterInsert Size% Dups% MappedM Total seqs% Proper PairsM Total seqs% AssignedGenome coverageM Genome readsM MT genome readsNumber of PeaksTreatment Redundancy
        DRR138947
        37.2%
        47.3%
        100.0%
        9.1%
        98 bp
        58.4%
        99.3%
        152.0
        99.7%
        38.5
        13.2%
        4.5 X
        95.7
        55.2
        52629
        0.05
        DRR138948
        35.0%
        47.2%
        100.0%
        9.3%
        85 bp
        59.0%
        99.3%
        162.2
        99.8%
        44.5
        12.6%
        4.6 X
        97.8
        63.3
        55659
        0.05
        DRR138949
        37.4%
        47.3%
        100.0%
        10.5%
        82 bp
        63.7%
        99.3%
        146.0
        99.8%
        34.6
        12.2%
        3.7 X
        79.7
        65.3
        41320
        0.04
        DRR138950
        7.1%
        47.2%
        100.0%
        10.6%
        72 bp
        65.1%
        99.7%
        134.6
        99.9%
        33.7
        22.8%
        2.2 X
        46.7
        87.4
        76162
        0.07
        DRR138951
        8.6%
        47.4%
        100.0%
        9.9%
        75 bp
        48.5%
        99.5%
        130.7
        99.9%
        49.0
        21.7%
        3.3 X
        70.6
        59.6
        91863
        0.09
        DRR138952
        9.8%
        47.1%
        100.0%
        11.0%
        72 bp
        47.9%
        99.5%
        137.3
        99.9%
        53.7
        17.0%
        3.6 X
        75.9
        60.6
        71214
        0.07
        DRR138953
        6.6%
        47.8%
        100.0%
        17.1%
        62 bp
        72.9%
        99.5%
        138.8
        99.9%
        29.6
        37.6%
        1.7 X
        37.0
        101.1
        113956
        0.12
        DRR138954
        8.8%
        47.8%
        100.0%
        17.1%
        64 bp
        71.9%
        99.4%
        140.5
        99.9%
        29.9
        36.8%
        1.8 X
        39.7
        99.9
        113482
        0.11
        DRR138955
        8.5%
        47.8%
        100.0%
        18.8%
        61 bp
        72.2%
        99.5%
        131.0
        99.9%
        28.1
        37.1%
        1.6 X
        36.3
        94.0
        107591
        0.11
        DRR138956
        9.1%
        48.0%
        100.0%
        18.0%
        64 bp
        71.8%
        99.4%
        134.2
        99.9%
        29.3
        41.2%
        1.7 X
        38.2
        95.2
        108341
        0.12
        DRR138957
        7.0%
        48.0%
        100.0%
        21.2%
        62 bp
        62.1%
        99.6%
        154.3
        99.9%
        47.4
        40.3%
        2.7 X
        60.2
        93.5
        134190
        0.16
        DRR138958
        8.0%
        47.9%
        100.0%
        19.3%
        64 bp
        68.7%
        99.7%
        160.7
        99.9%
        39.4
        40.2%
        2.3 X
        51.6
        108.7
        119190
        0.14
        DRR138959
        6.8%
        47.5%
        100.0%
        19.2%
        58 bp
        63.3%
        99.5%
        141.5
        99.9%
        40.1
        32.3%
        2.4 X
        52.6
        88.2
        96653
        0.10
        DRR138960
        7.6%
        47.7%
        100.0%
        21.2%
        57 bp
        59.1%
        99.6%
        138.9
        99.9%
        45.0
        33.3%
        2.7 X
        58.7
        79.6
        107837
        0.11
        DRR138961
        8.9%
        48.1%
        100.0%
        20.3%
        61 bp
        55.6%
        99.5%
        154.7
        99.9%
        55.8
        38.4%
        3.3 X
        72.9
        81.0
        124872
        0.15
        DRR138962
        9.7%
        47.5%
        100.0%
        18.4%
        63 bp
        48.8%
        99.6%
        125.7
        99.9%
        49.7
        27.1%
        3.1 X
        68.4
        56.8
        103636
        0.11
        DRR138963
        10.8%
        47.4%
        100.0%
        20.6%
        59 bp
        54.1%
        99.6%
        118.1
        99.9%
        41.8
        28.2%
        2.6 X
        57.8
        59.9
        98999
        0.10
        DRR138964
        11.1%
        47.4%
        100.0%
        20.9%
        58 bp
        51.7%
        99.6%
        124.4
        99.9%
        47.8
        26.3%
        2.9 X
        64.7
        59.2
        100080
        0.10
        DRR138965
        8.7%
        47.5%
        100.0%
        19.1%
        62 bp
        40.6%
        99.4%
        144.9
        99.9%
        70.9
        27.8%
        4.2 X
        92.8
        51.2
        125755
        0.13
        DRR138966
        7.6%
        47.3%
        100.0%
        19.1%
        63 bp
        38.3%
        99.4%
        147.5
        99.9%
        74.0
        26.7%
        4.4 X
        96.9
        49.7
        120331
        0.12
        DRR138967
        9.6%
        47.3%
        100.0%
        19.5%
        63 bp
        43.0%
        99.5%
        160.5
        99.9%
        74.8
        27.0%
        4.5 X
        99.6
        60.1
        119026
        0.12
        DRR138968
        7.9%
        47.0%
        100.0%
        16.0%
        73 bp
        51.2%
        99.4%
        158.1
        99.9%
        62.3
        15.7%
        3.7 X
        80.8
        76.4
        67952
        0.08
        DRR138969
        8.3%
        47.0%
        100.0%
        18.2%
        70 bp
        46.9%
        99.3%
        145.0
        99.9%
        61.7
        17.5%
        3.7 X
        81.3
        62.7
        77567
        0.09
        DRR138970
        7.1%
        46.9%
        100.0%
        20.6%
        67 bp
        46.7%
        99.4%
        150.7
        99.9%
        65.6
        16.7%
        3.8 X
        84.1
        65.7
        74931
        0.08
        GSM4120721
        2.9%
        52.6%
        97.3%
        5.7%
        108 bp
        39.5%
        80.4%
        20.5
        99.6%
        4.8
        31.2%
        0.4 X
        9.5
        7.0
        46978
        0.06
        GSM4120722
        5.4%
        50.7%
        97.7%
        3.3%
        129 bp
        26.2%
        94.1%
        42.7
        99.7%
        14.4
        17.6%
        1.2 X
        30.2
        10.0
        49522
        0.05
        GSM4120723
        3.1%
        50.6%
        97.3%
        4.1%
        139 bp
        28.6%
        95.0%
        29.2
        99.7%
        9.1
        11.6%
        0.7 X
        19.0
        8.7
        40829
        0.04
        GSM4120724
        5.4%
        47.2%
        97.7%
        3.0%
        150 bp
        60.9%
        91.7%
        48.3
        99.4%
        6.8
        6.4%
        0.6 X
        15.5
        28.8
        16385
        0.02
        GSM5017897
        32.4%
        48.3%
        97.7%
        4.6%
        121 bp
        43.0%
        95.1%
        381.1
        99.6%
        103.8
        10.9%
        12.0 X
        313.2
        49.2
        48265
        0.09
        GSM5017898
        31.6%
        48.4%
        96.9%
        5.0%
        115 bp
        42.2%
        95.4%
        477.2
        99.7%
        140.6
        9.4%
        15.8 X
        411.8
        43.5
        46838
        0.11
        GSM5017899
        20.8%
        45.8%
        93.6%
        0.9%
        105 bp
        44.8%
        97.6%
        580.7
        99.6%
        178.4
        20.1%
        18.0 X
        474.2
        92.7
        112605
        0.16
        GSM5017900
        16.4%
        45.2%
        93.3%
        0.8%
        115 bp
        37.3%
        97.5%
        382.0
        99.5%
        128.8
        15.7%
        11.9 X
        312.7
        59.8
        74822
        0.10
        GSM5017901
        32.5%
        46.6%
        97.0%
        4.6%
        158 bp
        45.4%
        98.4%
        521.4
        99.6%
        126.3
        25.0%
        17.1 X
        445.4
        67.4
        103327
        0.14
        GSM5017902
        42.4%
        46.1%
        96.6%
        3.8%
        167 bp
        53.3%
        98.6%
        577.6
        99.5%
        111.4
        22.3%
        19.4 X
        504.9
        64.6
        90810
        0.12

        Workflow explanation

        Oh no! Something went wrong... Please let us know: https://github.com/vanheeringen-lab/seq2science/issues

        Assembly stats

        Genome assembly GRCg6a contains of 464 contigs, with a GC-content of 42.23%, and 0.92% consists of the letter N. The N50-L50 stats are 91315245-4 and the N75-L75 stats are 24153086-10. The genome annotation contains 13384 genes.

        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.

        loading..

        Insert Sizes

        Insert size estimation of sampled reads.

        loading..

        Sequence Quality

        Average sequencing quality over each base of all reads.

        loading..

        GC Content

        Average GC content over each base of all reads.

        loading..

        N content

        Average N content over each base of all reads.

        loading..

        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, read length filtering, 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.

        loading..

        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.

        loading..

        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

        loading..

        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..

        deepTools - Spearman correlation heatmap of reads in bins across the genome

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

        deepTools - Pearson correlation heatmap of reads in bins across the genome

        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 distributions (macs2)

        The distribution of read pileup around 20000 random peaks for each sample. This visualization is a quick and dirty way to check if your peaks look like what you would expect, and what the underlying distribution of different types of peaks is.

        Peak feature distribution (macs2)

        Figure generated by chipseeker

        Distribution of peak locations relative to TSS (macs2)

        Figure generated by chipseeker

        DESeq2 - Sample distance cluster heatmap of counts

        Euclidean distance between samples, based on variance stabilizing transformed counts (RNA: expressed genes, ChIP: bound regions, ATAC: accessible regions). Gives us an overview of similarities and dissimilarities between samples.

        DESeq2 - Spearman correlation cluster heatmap of counts

        Correlation cluster heatmap based on variance stabilizing transformed counts. Spearman correlation is a non-parametric (distribution-free) method, and assesses the monotonicity of the relationship.

        DESeq2 - Pearson correlation cluster heatmap of counts

        Correlation cluster heatmap based on variance stabilizing transformed counts. Pearson correlation is a parametric (lots of assumptions, e.g. normality and homoscedasticity) method, and assesses the linearity of the relationship.

        Samples & Config

        The samples file used for this run:

        sample assembly biological_replicates descriptive_name
        DRR138947 GRCg6a HH6 24hpf_GA1
        DRR138948 GRCg6a HH6 24hpf_GA2
        DRR138949 GRCg6a HH6 24hpf_GA3
        DRR138950 GRCg6a HH11 43hpf_GA4
        DRR138951 GRCg6a HH11 43hpf_GA5
        DRR138952 GRCg6a HH11 43hpf_GA6
        DRR138953 GRCg6a HH16 54hpf_GA7
        DRR138954 GRCg6a HH16 54hpf_GA8
        DRR138955 GRCg6a HH16 54hpf_GA9
        DRR138956 GRCg6a HH19 78hpf_GA10
        DRR138957 GRCg6a HH19 78hpf_GA11
        DRR138958 GRCg6a HH19 78hpf_GA12
        DRR138959 GRCg6a HH24 108hpf_GA13
        DRR138960 GRCg6a HH24 108hpf_GA14
        DRR138961 GRCg6a HH24 108hpf_GA15
        DRR138962 GRCg6a HH28 138hpf_GA16
        DRR138963 GRCg6a HH28 138hpf_GA17
        DRR138964 GRCg6a HH28 138hpf_GA18
        DRR138965 GRCg6a HH32 180hpf_GA19
        DRR138966 GRCg6a HH32 180hpf_GA20
        DRR138967 GRCg6a HH32 180hpf_GA21
        DRR138968 GRCg6a HH38 288hpf_GA22
        DRR138969 GRCg6a HH38 288hpf_GA23
        DRR138970 GRCg6a HH38 288hpf_GA24
        GSM5017897 GRCg6a HH20 80hpf_GB1_wb
        GSM5017898 GRCg6a HH20 80hpf_GB2_wb
        GSM5017899 GRCg6a HH22 94hpf_GB3_wb
        GSM5017900 GRCg6a HH22 94hpf_GB4_wb
        GSM5017901 GRCg6a HH24 108hpf_GB5_wb
        GSM5017902 GRCg6a HH24 108hpf_GB6_wb
        GSM4120721 GRCg6a HH6 24hpf_GC1
        GSM4120722 GRCg6a HH6 24hpf_GC2
        GSM4120723 GRCg6a HH9 30hpf_GC3
        GSM4120724 GRCg6a HH9 30hpf_GC4

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

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


# contact info for multiqc report and trackhub
email: tessa.dewijs2@ru.nl

# produce a UCSC trackhub?
create_trackhub: true

# how to handle replicates
biological_replicates: fisher  # 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
max_template_length: 150
remove_dups: true

# peak callers (supported peak callers are macs2, and genrich)
peak_caller:
  macs2:
      --shift -100 --extsize 200 --nomodel --buffer-size 10000
#  genrich:
#      -j -y -D -d 200 -q 0.05

# how much peak summits will be extended by (on each side) for the final count table
# (e.g. 100 means a 200 bp wide peak)
slop: 100

## differential accessibility analysis
#contrasts:
#  - 'biological_replicates_adult_embryo'

        MultiQC v1.11 - Written by Phil Ewels, available on GitHub.

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