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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

        Please remember to cite the tools that you use in your analysis.

        To help with this, you can download publication details of the tools mentioned in this report:

        About MultiQC

        This report was generated using MultiQC, version 1.27

        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/MultiQC/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

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

        This report has been generated by the nf-core/pangenome analysis pipeline. For information about how to interpret these results, please see the documentation.
        Report generated on 2026-02-17, 18:34 UTC based on data in: /fusion/s3/nf-core-awsmegatests/work/pangenome/work-3d02bd1df79f48b4bfdb4ad95d4ca0d7f6aeb337/c6/4f78ab670b07bd84dc225b72b10bd0

        ODGI

        Analysis and manipulation of pangenome graphs structured in the variation graph model.URL: https://github.com/pangenome/odgi

        Detailed ODGI stats table.

        Showing 1/1 rows and 10/14 columns.
        Sample NameLengthNodesEdgesPathsComponentsACTGNSelf Loops NodesUnique Self Loops Nodes% GC% N
        scerevisiae8
        15216041
        620531
        839882
        136
        15
        4666015
        2886273
        4648388
        2893866
        121499
        3
        3
        38.0%
        0.8%

        Sum of path node distances

        For each path we iterate from node to node and count the node / nucleotide distance of nodes on the pangenome level normalized by the path length. If a node is reversed, we count the node distance twice.

        This value allows you to evaluate the sorting goodness - how linear the graph is.

        Created with MultiQC


        ODGI Compressed 1D visualization

        This image shows a 1D rendering of the built pangenome graph. The graph nodes are arranged from left to right, forming the pangenome sequence. Summarization of path coverage across all paths. A heatmap color-coding from https://colorbrewer2.org/#type=diverging&scheme=RdBu&n=11 is used. Dark blue means highest coverage. Dark red means lowest coverage. The path names are placed on the left. The black lines under the paths are the links, which represent the graph topology.


        ODGI 1D visualization

        This image shows a 1D rendering of the built pangenome graph. The graph nodes are arranged from left to right, forming the pangenome sequence. The colored bars represent the paths versus the pangenome sequence in a binary matrix. The path names are placed on the left. The black lines under the paths are the links, which represent the graph topology.


        ODGI 1D visualization by path position

        This shows a 1D rendering of the built pangenome graph where the paths are colored according to their nucleotide position. Light grey means a low path position, black is the highest path position.


        ODGI 1D visualization by path orientation

        This image shows a 1D rendering of the built pangenome graph where the paths are colored by orientation. Forward is black, reverse is red.


        ODGI 1D visualization by node depth

        This shows a 1D rendering of the built pangenome graph where the paths are colored according to path depth. Using the Spectra color palette with 4 levels of path depths, white indicates no depth, while grey, red, and yellow indicate depth 1, 2, and greater than or equal to 3, respectively.


        ODGI 1D visualization by uncalled bases

        This shows a 1D rendering of the built pangenome graph where the paths are colored according to the coverage of uncalled bases. The lighter the green, the higher the 'N' content of a node is.


        ODGI 2D drawing

        This image shows a 2D rendering of the built pangenome graph.


        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        GroupSoftwareVersion
        EXTRACT_COMMUNITIESsamtools1.17
        GFAFFIXgfaffix0.1.5b
        NET2COMMUNITIESpggb0.5.4
        ODGI_BUILDodgi0.9.0
        ODGI_DRAW_HEIGHTodgi0.9.0
        ODGI_DRAW_MULTIQCodgi0.9.0
        ODGI_LAYOUTodgi0.9.0
        ODGI_SORTodgi0.9.0
        ODGI_SQUEEZEodgi0.9.0)
        ODGI_STATSodgi0.9.0
        ODGI_UNCHOPodgi0.9.0
        ODGI_VIEWodgi0.9.0
        ODGI_VIZ_COLORodgi0.9.0
        ODGI_VIZ_COMPRodgi0.9.0
        ODGI_VIZ_DEPTHodgi0.9.0
        ODGI_VIZ_INVodgi0.9.0
        ODGI_VIZ_POSodgi0.9.0
        ODGI_VIZ_UNCALLEDodgi0.9.0
        PAF2NETpggb0.5.4
        SAMTOOLS_FAIDXsamtools1.19.2
        SEQWISHseqwish0.7.9
        SMOOTHXGsmoothxg0.8.0
        TABIX_BGZIPtabix1.12
        WFMASH_MAP_ALIGNwfmash0.10.4
        WFMASH_MAP_COMMUNITYwfmash0.10.4
        WorkflowNextflow25.10.2
        nf-core/pangenomev1.1.3-g3d02bd1

        nf-core/pangenome Methods Description

        Suggested text and references to use when describing pipeline usage within the methods section of a publication.URL: https://github.com/nf-core/pangenome

        Methods

        Data was processed using nf-core/pangenome v1.1.3 (doi: 10.5281/zenodo.8202636) of the nf-core collection of workflows (Ewels et al., 2020), utilising reproducible software environments from the Bioconda (Grüning et al., 2018) and Biocontainers (da Veiga Leprevost et al., 2017) projects.

        The pipeline was executed with Nextflow v25.10.2 (Di Tommaso et al., 2017) with the following command:

        nextflow run 'https://github.com/nf-core/pangenome' -name nf-core-pangenome-megatest -params-file 'https://api.cloud.seqera.io/ephemeral/hiGehbQWeSeeX1AYYTrE_A.yaml' -with-tower -r 3d02bd1df79f48b4bfdb4ad95d4ca0d7f6aeb337 -profile test_full

        References

        • Di Tommaso, P., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., & Notredame, C. (2017). Nextflow enables reproducible computational workflows. Nature Biotechnology, 35(4), 316-319. doi: 10.1038/nbt.3820
        • Ewels, P. A., Peltzer, A., Fillinger, S., Patel, H., Alneberg, J., Wilm, A., Garcia, M. U., Di Tommaso, P., & Nahnsen, S. (2020). The nf-core framework for community-curated bioinformatics pipelines. Nature Biotechnology, 38(3), 276-278. doi: 10.1038/s41587-020-0439-x
        • Grüning, B., Dale, R., Sjödin, A., Chapman, B. A., Rowe, J., Tomkins-Tinch, C. H., Valieris, R., Köster, J., & Bioconda Team. (2018). Bioconda: sustainable and comprehensive software distribution for the life sciences. Nature Methods, 15(7), 475–476. doi: 10.1038/s41592-018-0046-7
        • da Veiga Leprevost, F., Grüning, B. A., Alves Aflitos, S., Röst, H. L., Uszkoreit, J., Barsnes, H., Vaudel, M., Moreno, P., Gatto, L., Weber, J., Bai, M., Jimenez, R. C., Sachsenberg, T., Pfeuffer, J., Vera Alvarez, R., Griss, J., Nesvizhskii, A. I., & Perez-Riverol, Y. (2017). BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics (Oxford, England), 33(16), 2580–2582. doi: 10.1093/bioinformatics/btx192
        Notes:
        • The command above does not include parameters contained in any configs or profiles that may have been used. Ensure the config file is also uploaded with your publication!
        • You should also cite all software used within this run. Check the "Software Versions" of this report to get version information.

        nf-core/pangenome Workflow Summary

        - this information is collected when the pipeline is started.URL: https://github.com/nf-core/pangenome

        Input/output options

        input
        s3://ngi-igenomes/test-data/pangenome/scerevisiae8.fasta.gz
        n_haplotypes
        8
        outdir
        s3://nf-core-awsmegatests/pangenome/results-3d02bd1df79f48b4bfdb4ad95d4ca0d7f6aeb337

        Wfmash Options

        wfmash_map_pct_id
        90.0

        Seqwish Options

        seqwish_sparse_factor
        0.0

        Community

        communities
        true

        Institutional config options

        config_profile_description
        Full test dataset to check pipeline function
        config_profile_name
        Full test profile

        Generic options

        trace_report_suffix
        2026-02-17_18-21-02

        Core Nextflow options

        configFiles
        /.nextflow/assets/nf-core/pangenome/nextflow.config, /nextflow.config
        launchDir
        /
        profile
        test_full
        projectDir
        /.nextflow/assets/nf-core/pangenome
        revision
        1.1.3
        runName
        nf-core-pangenome-megatest
        userName
        root
        workDir
        /nf-core-awsmegatests/work/pangenome/work-3d02bd1df79f48b4bfdb4ad95d4ca0d7f6aeb337