MoP4 - pipeline

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        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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        Tool Citations

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        About MultiQC

        This report was generated using MultiQC, version 1.27.1

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

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        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

        MoP4 - pipeline

        Please cite
        Cozzuto L, Liu H, Pryszcz LP, Pulido TH, Delgado-Tejedor A, Ponomarenko J, Novoa EM. MasterOfPores: A Workflow for the Analysis of Oxford Nanopore Direct RNA Sequencing Datasets. Front Genet. 2020 Mar 17;11:211. doi: 10.3389/fgene.2020.00211
        And
        Cozzuto L, Delgado-Tejedor A, Hermoso Pulido T, Novoa EM, Ponomarenko J. Nanopore Direct RNA Sequencing Data Processing and Analysis Using MasterOfPores. N. Methods Mol Biol. 2023;2624:185-205. doi: 10.1007/978-1-0716-2962-8_13.
        Report generated on 2025-04-10, 16:48 UTC based on data in: /Users/lcozzuto/ooo/master_of_pores/mop_preprocess/work/a0/dc0b50f2d80e69102d9682227981ee

        General Statistics

        Showing 1/1 rows and 4/16 columns.
        Sample NameReadsBasesRead N50Longest ReadShortest ReadMean LengthMedian LengthMean QualMedian QualMedian lengthRead N50Median QualMedian Identity# Reads (K)Total Bases (Mb)Aligned Bases (Mb)
        dRNA
        0.0M
        0.1Mb
        1424bp
        6389bp
        12bp
        1004.0bp
        625
        16.5
        16.9
        330bp
        472bp
        13.1
        91.4%
        0.0K
        0.0Mb
        0.0Mb

        Assigned counts

        Showing 1/1 rows.
        File nameCounts
        dRNA
        2

        Alignment QC

        Showing 1/1 rows and 7/7 columns.
        File nameMapped readsMap %BasesBases %Avg read lengthMax read lengthidentity
        dRNA_s.bam
        2
        100.0%
        638
        96.5%
        330
        472
        89.81%

        nanoq

        Reports read quality and length from nanopore sequencing data.URL: https://github.com/nerdna/nanoqDOI: 10.21105/joss.02991

        Nanoq Summary

        Statistics from Nanoq reports

        Showing 1/1 rows and 9/9 columns.
        Sample NameReadsBasesRead N50Longest ReadShortest ReadMean LengthMedian LengthMean QualMedian Qual
        dRNA
        0.0M
        0.1Mb
        1424bp
        6389bp
        12bp
        1004.0bp
        625
        16.5
        16.9

        Read quality

        Read counts categorised by read quality (Phred score).

        Sequencing machines assign each generated read a quality score using the Phred scale. The phred score represents the liklelyhood that a given read contains errors. High quality reads have a high score.

        Created with MultiQC

        Read lengths

        Read counts categorised by read length.

        Created with MultiQC

        NanoStat

        Reports various statistics for long read dataset in FASTQ, BAM, or albacore sequencing summary format (supports NanoPack; NanoPlot, NanoComp).URL: https://github.com/wdecoster/nanostat; https://github.com/wdecoster/nanoplotDOI: 10.1093/bioinformatics/bty149

        Programs are part of the NanoPack family for summarising results of sequencing on Oxford Nanopore methods (MinION, PromethION etc.)

        Summary Statistics (Aligned)

        Showing 1/1 rows and 7/10 columns.
        Sample NameMedian lengthMean lengthRead N50Median QualMean QualMedian IdentityMean Identity# Reads (K)Total Bases (Mb)Aligned Bases (Mb)
        dRNA
        330bp
        330bp
        472bp
        13.1
        13.1
        91.4%
        91.4%
        0.0K
        0.0Mb
        0.0Mb

        Reads by quality

        Read counts categorised by read quality (Phred score).

        Sequencing machines assign each generated read a quality score using the Phred scale. The phred score represents the liklelyhood that a given read contains errors. High quality reads have a high score.

        Created with MultiQC