diff --git a/CHANGELOG.md b/CHANGELOG.md index 6c6225bc..d106fc5b 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -19,6 +19,7 @@ Pipeline has been re-implemented in [Nextflow DSL2](https://www.nextflow.io/docs - [#70](https://github.com/nf-core/metapep/pull/70) - Added check for supported models and functionality to output all supported models. - [#75](https://github.com/nf-core/metapep/pull/75) - Peptide lengths are checked if supported generally and unified if models are not available in `UNIFY_MODEL_LENGTHS` - [#80](https://github.com/nf-core/metapep/pull/80) - Add mean comparison to entity binding ratios plots. +- [#84](https://github.com/nf-core/metapep/pull/84) - Added MultiQC again with updated method description and updated references - [#88](https://github.com/nf-core/metapep/pull/88) - Updated Citations.md ### `Changed` diff --git a/assets/methods_description_template.yml b/assets/methods_description_template.yml index 7f487ed5..0bb2ec52 100644 --- a/assets/methods_description_template.yml +++ b/assets/methods_description_template.yml @@ -3,11 +3,11 @@ description: "Suggested text and references to use when describing pipeline usag section_name: "nf-core/metapep Methods Description" section_href: "https://github.com/nf-core/metapep" plot_type: "html" -## TODO nf-core: Update the HTML below to your preferred methods description, e.g. add publication citation for this pipeline -## You inject any metadata in the Nextflow '${workflow}' object + data: |

Methods

-

Data was processed using nf-core/metapep v${workflow.manifest.version} ${doi_text} 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.

+

Data was processed using nf-core/metapep v${workflow.manifest.version} ${doi_text} 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. Briefly the pipeline uses prodigal (Hyatt, D., Chen, GL., LoCascio, P.F. et al., 2010) to predict proteins from the genomic input files or downloads the proteins from the taxid input directly using Entrez (Maglott et al., 2005). Peptides are generated in discrete lengths from proteins and predicted against chosen alleles using either SYFPEITHI (Rammensee et al., 1999), MHCFlurry (O'Donnel et al., 2020) or MHCnuggets (Shao et al., 2019), which are embedded in the epytope framework (Schubert et al., 2016). + Resulting epitopeprediction scores distributions and entity binding ratios are plotted using R (R Core Team, 2022). The large amounts of data are handled using a python (Python Core Team, 2022) framework. All specific software versions and used libraries can be found in the following section and the CITATIONS.md file.

The pipeline was executed with Nextflow v${workflow.nextflow.version} (Di Tommaso et al., 2017) with the following command:

${workflow.commandLine}

${tool_citations}

@@ -16,6 +16,14 @@ data: |
  • 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
    • +
  • Hyatt, D., Chen, GL., LoCascio, P. F., Land M. L., Larimer F. W., Hauser L. J. (2010). Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11, 119. doi: 10.1186/1471-2105-11-119
    • +
  • Maglott D, Ostell J, Pruitt KD, Tatusova T. (2005) Entrez Gene: gene-centered information at NCBI. Nucleic Acids Res. 2005 Jan 1;33(Database issue):D54-8. Update in: Nucleic Acids Res. 2007 Jan;35(Database issue):D26-31. doi: 10.1093/nar/gki031.
    • +
  • O'Donnell T. J., Rubinsteyn A., Laserson U., (2020). MHCflurry 2.0: Improved Pan-Allele Prediction of MHC Class I-Presented Peptides by Incorporating Antigen Processing. Cell Systems 11, 42-48. doi: 10.1016/j.cels.2020.06.010.
    • +
  • Python Core Team (2022). Python: A dynamic, open source programming language. Python Software Foundation. https://www.python.org/.
    • +
  • Rammensee H., Bachmann J., Emmerich N. P., Bachor O. A., Stevanović S. (1999). SYFPEITHI: database for MHC ligands and peptide motifs. Immunogenetics 1999 Nov;50(3-4):213-9. doi: 10.1007/s002510050595.
    • +
  • R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
    • +
  • Schubert, B., Walzer, M., Brachvogel, H-P., Sozolek, A., Mohr, C., and Kohlbacher, O. (2016). FRED 2 - An Immunoinformatics Framework for Python. Bioinformatics 2016. doi: 10.1093/bioinformatics/btw113.
    • +
  • Shao X. M., Bhattacharya R., Huang J., Sivakumar I. K. A., Tokheim C., Zheng L., Hirsch D., Kaminow B., Omdahl A., Bonsack M., Riemer A. B., Velculescu V. E., Anagnostou V., Pagel K. A., Karchin R. (2020). High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets. Cancer Immunol Res. 2020 Mar;8(3):396-408. doi: 10.1158/2326-6066.cir-19-0464.
  • 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
    • ${tool_bibliography} diff --git a/assets/multiqc_config.yml b/assets/multiqc_config.yml index ea17e0c9..009b23a0 100644 --- a/assets/multiqc_config.yml +++ b/assets/multiqc_config.yml @@ -1,3 +1,7 @@ +custom_logo: "nf-core-metapep_logo_light.png" +custom_logo_url: https://github.com/nf-core/metapep/ +custom_logo_title: "nf-core/metapep" + report_comment: > This report has been generated by the nf-core/metapep analysis pipeline. For information about how to interpret these results, please see the diff --git a/docs/output.md b/docs/output.md index 4ecdca08..ce654d45 100644 --- a/docs/output.md +++ b/docs/output.md @@ -171,7 +171,7 @@ The pipeline generates some basic visualisations comparing the results for the d - +Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQC. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see . ## Pipeline information diff --git a/modules.json b/modules.json index 3226deb7..16286925 100644 --- a/modules.json +++ b/modules.json @@ -13,7 +13,8 @@ "multiqc": { "branch": "master", "git_sha": "911696ea0b62df80e900ef244d7867d177971f73", - "installed_by": ["modules"] + "installed_by": ["modules"], + "patch": "modules/nf-core/multiqc/multiqc.diff" }, "prodigal": { "branch": "master", diff --git a/modules/nf-core/multiqc/main.nf b/modules/nf-core/multiqc/main.nf index 1fc387be..1f1b7a41 100644 --- a/modules/nf-core/multiqc/main.nf +++ b/modules/nf-core/multiqc/main.nf @@ -8,6 +8,7 @@ process MULTIQC { input: path multiqc_files, stageAs: "?/*" + path custom_logo path(multiqc_config) path(extra_multiqc_config) path(multiqc_logo) diff --git a/modules/nf-core/multiqc/multiqc.diff b/modules/nf-core/multiqc/multiqc.diff new file mode 100644 index 00000000..a02a2334 --- /dev/null +++ b/modules/nf-core/multiqc/multiqc.diff @@ -0,0 +1,13 @@ +Changes in module 'nf-core/multiqc' +--- modules/nf-core/multiqc/main.nf ++++ modules/nf-core/multiqc/main.nf +@@ -8,6 +8,7 @@ + + input: + path multiqc_files, stageAs: "?/*" ++ path custom_logo + path(multiqc_config) + path(extra_multiqc_config) + path(multiqc_logo) + +************************************************************ diff --git a/workflows/metapep.nf b/workflows/metapep.nf index 24fb6a00..57e39605 100644 --- a/workflows/metapep.nf +++ b/workflows/metapep.nf @@ -33,6 +33,7 @@ if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { */ ch_multiqc_config = Channel.fromPath("$projectDir/assets/multiqc_config.yml", checkIfExists: true) +ch_metapep_logo = Channel.fromPath("$projectDir/assets/nf-core-metapep_logo_light.png") ch_multiqc_custom_config = params.multiqc_config ? Channel.fromPath( params.multiqc_config, checkIfExists: true ) : Channel.empty() ch_multiqc_logo = params.multiqc_logo ? Channel.fromPath( params.multiqc_logo, checkIfExists: true ) : Channel.empty() ch_multiqc_custom_methods_description = params.multiqc_methods_description ? file(params.multiqc_methods_description, checkIfExists: true) : file("$projectDir/assets/methods_description_template.yml", checkIfExists: true) @@ -304,6 +305,7 @@ workflow METAPEP { MULTIQC ( ch_multiqc_files.collect(), + ch_metapep_logo.collect(), ch_multiqc_config.toList(), ch_multiqc_custom_config.toList(), ch_multiqc_logo.toList()