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MultiQC-Additional overview stat table #134

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merged 14 commits into from
Sep 30, 2024

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tillenglert
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This PR adds an overview summary table to the multiqc report, so users unexperienced with the pipeline can get an idea what the pipeline output contains.

full size test is currently running and test will be delivered after.

A current multiqc report is attached.
multiqc.zip

PR checklist

  • This comment contains a description of changes (with reason).
  • If you've fixed a bug or added code that should be tested, add tests!
  • If you've added a new tool - have you followed the pipeline conventions in the contribution docs
  • If necessary, also make a PR on the nf-core/metapep branch on the nf-core/test-datasets repository.
  • Make sure your code lints (nf-core lint).
  • Ensure the test suite passes (nextflow run . -profile test,docker --outdir <OUTDIR>).
  • Check for unexpected warnings in debug mode (nextflow run . -profile debug,test,docker --outdir <OUTDIR>).
  • Usage Documentation in docs/usage.md is updated.
  • Output Documentation in docs/output.md is updated.
  • CHANGELOG.md is updated.
  • README.md is updated (including new tool citations and authors/contributors).

…e output to table and add table to multiqc
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github-actions bot commented Sep 6, 2024

nf-core lint overall result: Passed ✅ ⚠️

Posted for pipeline commit 5f00c9b

+| ✅ 195 tests passed       |+
#| ❔   2 tests were ignored |#
!| ❗   3 tests had warnings |!

❗ Test warnings:

  • nextflow_config - Config manifest.version should end in dev: 1.0.0
  • readme - README contains the placeholder zenodo.XXXXXXX. This should be replaced with the zenodo doi (after the first release).
  • nfcore_yml - nf-core version not set in .nf-core.yml

❔ Tests ignored:

✅ Tests passed:

Run details

  • nf-core/tools version 2.14.1
  • Run at 2024-09-30 05:59:51


print("Done!", flush=True)
# peptide_id, condition_name, condition_peptide_count, highest_prediction_score, prediction_score_allele_0, prediction_score_allele_1,...prediction_score_allele_n
conditions_peptides = conditions_peptides.set_index("peptide_id").join(best_scored_peptides).join(predictions)
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I am not sure I understood all details of the new code, but since it caused quite some memory usage, I have a few questions/suggestions since I am wondering if you really need that many joins:

  • conditions_peptides: if the resulting df become too large, you could drop the condition_name (anyway the same within this context) and count before joining to the predictions
  • filter predictions directly after reading in for entries that are above the threshold, and drop the prediction_score to reduce the size
  • merge/join for each allele to get only peptides that are "binders" and count

Brings me to the next question: you just provide the count of unique binders, right? Maybe that should be stated somewhere more clearly.

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I managed to reduce the used Memory to around 50GB which is only 10GB more compared to the previous version not including peptide predictions!

@tillenglert tillenglert marked this pull request as ready for review September 16, 2024 14:45
@tillenglert tillenglert requested a review from skrakau September 16, 2024 14:46
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Minor comment regarding names, other than that it looks great!

@tillenglert tillenglert merged commit 68258d0 into nf-core:dev Sep 30, 2024
21 checks passed
@tillenglert tillenglert deleted the multiqc_additional_stats branch October 18, 2024 11:49
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2 participants