Minor update

[yueqixuan]

PR Type

Bug fix, Enhancement, Documentation

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Description

• Enhanced label-free quantification detection with "lfq" keyword support

• Updated error messages for better clarity

• Improved README documentation with clearer examples

• Updated citation information with published journal reference

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Diagram Walkthrough

flowchart LR
  A["Label Detection"] --> B["Enhanced LFQ Recognition"]
  B --> C["Better Error Messages"]
  D["README Examples"] --> E["Clearer Documentation"]
  F["Citation"] --> G["Updated Journal Reference"]

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File Walkthrough

	Relevant files
Enhancement	quantification_type.py Enhanced LFQ detection and error messaging                              ibaqpy/model/quantification_type.py Added "lfq" keyword to label-free quantification detection Enhanced error message to include "lfq" in supported formats +4/-2
Documentation	README.md Documentation improvements and citation update                      README.md Updated command examples with generic dataset names Clarified parameter descriptions for better understanding Updated citation with published journal reference +4/-4

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[qodo-code-review]

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⏱️ Estimated effort to review: 2 🔵🔵⚪⚪⚪

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🔒 No security concerns identified

⚡ Recommended focus areas for review Logic Specificity The LFQ detection now checks any occurrence of "lfq" or "label free" across labels but only when len(labels) == 1; confirm this does not miss valid multi-label LFQ inputs or accidentally match substrings in unrelated terms. Consider anchoring or stricter matching if needed. if len(labels) == 1 and any( keyword in s.lower() for s in labels for keyword in ["lfq", "label free"] ): label_category = cls.LFQ Error Message Consistency The error message text was updated; ensure wording and capitalization are consistent with CLI/docs ("label-free" vs "label free", "LFQ") and that README reflects the exact accepted keywords. raise ValueError( f"Cannot infer labeling scheme from {labels}, only support label free (or lfq), TMT and ITRAQ experiment!" )

[qodo-code-review]

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[Copilot]

Pull Request Overview

This PR enhances the label-free quantification (LFQ) detection capabilities and improves documentation. The main purpose is to add support for the "lfq" keyword in quantification type classification and update project documentation.

• Enhanced LFQ detection to recognize both "lfq" and "label free" keywords
• Improved error messaging to include "lfq" as a supported format
• Updated README with clearer command examples and published citation information

Reviewed Changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 3 comments.

File	Description
ibaqpy/model/quantification_type.py	Added "lfq" keyword support for LFQ detection and updated error message
ibaqpy/ibaq/peptide_normalization.py	Added filtering logic for missing reference files in SDRF
README.md	Updated command examples and citation with published journal reference

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[Copilot]

The nested generator expression creates unnecessary iterations. Consider using a more efficient approach by checking if any label contains any of the keywords without nested loops.

[Copilot]

The command uses 'ibaqpyc' instead of 'ibaqpy'. This appears to be a typo in the documentation.

Suggested change

	ibaqpyc features2peptides -p PXD000000.ibaq.parquet -s PXD000000.sdrf.tsv --remove_ids data/contaminants_ids.tsv --remove_decoy_contaminants --remove_low_frequency_peptides --output PXD000000-peptides-norm.csv
	ibaqpy features2peptides -p PXD000000.ibaq.parquet -s PXD000000.sdrf.tsv --remove_ids data/contaminants_ids.tsv --remove_decoy_contaminants --remove_low_frequency_peptides --output PXD000000-peptides-norm.csv