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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 1.33.dev0

        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

        MultiQC is developed by Seqera.

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

        Report generated on 2025-11-11, 16:31 GMT based on data in: /Users/jonathan.manning/projects/MultiQC/ribotish_plugin/Chen_2020

        General Statistics

        Showing 8/8 rows and 6/7 columns.
        Sample NameWeighted F0 %% in 28-30ntBest F0 %Best F0 Length (nt)Peak Length (nt)Length Range (nt)Total Reads
        SRR9113062_GSM3791723_iPSC_harringtonine-treated_Homo_sapiens_qual
        64.0%
        47.5%
        74.3%
        28
        30
        25-34
        20755546
        SRR9113063_GSM3791724_Cardiomyocyte_harringtonine-treated_Homo_sapiens_qual
        72.8%
        68.5%
        80.7%
        28
        29
        25-34
        8067784
        SRR9113064_GSM3791725_iPSC_no_drug_treatment_replicate_1_Homo_sapiens_qual
        74.7%
        70.5%
        81.7%
        30
        30
        25-34
        15012625
        SRR9113065_GSM3791726_iPSC_no_drug_treatment_replicate_2_Homo_sapiens_qual
        73.6%
        69.3%
        82.1%
        28
        30
        25-34
        12387378
        SRR9113066_GSM3791727_iPSC_no_drug_treatment_replicate_3_Homo_sapiens_qual
        73.9%
        70.0%
        82.6%
        28
        30
        25-34
        11301689
        SRR9113067_GSM3791728_Cardiomyocyte_no_drug_treatment_replicate_1_Homo_sapiens_qual
        68.1%
        64.1%
        76.7%
        28
        29
        25-34
        2078698
        SRR9113068_GSM3791729_Cardiomyocyte_no_drug_treatment_replicate_2_Homo_sapiens_qual
        72.5%
        68.1%
        81.7%
        28
        29
        25-34
        4201556
        SRR9113069_GSM3791730_Cardiomyocyte_no_drug_treatment_replicate_3_Homo_sapiens_qual
        74.2%
        70.3%
        82.9%
        28
        29
        25-34
        4597558

        Ribo-TISH

        Identifies translated ORFs from Ribo-seq data and reports reading frame quality metrics.https://github.com/zhpn1024/ribotishDOI: 10.1186/s13059-017-1316-1

        Reading Frame Proportions

        Proportion of reads in each reading frame (Frame 0, 1, 2) for different read lengths (25-34nt). Frame assignment is based on P-site positions as determined by Ribo-TISH. Some degree of frame preference (enrichment in Frame 0) is typically expected in Ribo-seq data.

        This plot shows the distribution of reads across the three reading frames for each read length, based on P-site positions.

        • Frame 0: The primary reading frame
        • Frame 1: Offset by 1 nucleotide from Frame 0
        • Frame 2: Offset by 2 nucleotides from Frame 0

        Ribo-seq data typically shows enrichment in Frame 0, particularly for read lengths 28-30nt, though the degree of frame preference can vary depending on the experimental protocol (e.g., RNase I vs. MNase treatment).

        Red dashed reference lines mark the expected proportions (33.3% and 66.7%) if reads were randomly distributed across frames. Good quality Ribo-seq data should show Frame 0 proportions well above the 33.3% threshold.

        Read lengths are shown as separate bars for each sample.

        Created with MultiQC

        Read Length Distribution

        Percentage of reads at each read length for each sample. Ribo-seq data typically shows enrichment around 28-30nt, representing ribosome-protected fragments.

        This plot shows what percentage of total reads each read length represents for each sample.

        • Each line represents a different sample
        • Peaks indicate the most common read lengths
        • Multiple samples can be easily compared

        The expected read length distribution can vary depending on the experimental protocol and organism.

        Created with MultiQC

        Read Length Distribution (Heatmap)

        Alternative heatmap view of read length distribution. Useful for comparing many samples at once.

        This heatmap shows what percentage of total reads each read length represents for each sample.

        • Rows are samples, columns are read lengths
        • Darker blue indicates higher percentage of reads
        • Lighter colors indicate fewer reads

        This view is particularly useful when comparing many samples simultaneously.

        Created with MultiQC