fix(spectronaut): Enable Fraction column to be processed#137
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📝 WalkthroughWalkthroughThis PR extends Spectronaut data cleaning to include the ChangesFraction column support in Spectronaut cleaning
Estimated code review effort🎯 1 (Trivial) | ⏱️ ~5 minutes Poem
🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
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Motivation and Context
Spectronaut experimental files include an
RFractioncolumn that represents sample fractionation information, but the.cleanRawSpectronaut()function was not processing this column. This fix enables the function to properly recognize, extract, and rename theRFractioncolumn from the input data to align with the MSstats output schema, where it is expected as theFractionfield.Changes
Column Selection Enhancement: Added
"RFraction"to the list of columns selected from the raw Spectronaut input (line 32 inclean_Spectronaut.R)Column Renaming Mapping: Updated the
data.table::setnames()call to include a mapping from"RFraction"(source) to"Fraction"(output schema name) (line 44-47 inclean_Spectronaut.R)Graceful Handling of Missing Column: Added
skip_absent = TRUEparameter to thesetnames()function to ensure the function continues to work correctly when theRFractioncolumn is absent from the input, maintaining backward compatibility with existing Spectronaut files that don't include fractionation informationUnit Tests
Backward Compatibility Test: Verifies that when
R.Fractionis absent from the input data, noFractioncolumn is added to the output, preserving existing behavior (lines 12-13 intest_clean_Spectronaut.R)RFraction Transfer Test: Confirms that when
R.Fractionis present in the input, it is properly transferred to the output as theFractioncolumn with the correct values (lines 15-25 intest_clean_Spectronaut.R)Column Naming Verification: Asserts that the intermediate column name
RFractiondoes not appear in the output (only the renamedFractioncolumn is present), ensuring correct schema compliance (line 24 intest_clean_Spectronaut.R)Code Guidelines
No violations identified. The implementation follows the existing code patterns in the repository, uses appropriate R/data.table idioms, and maintains consistency with how other optional columns are handled in the cleaning pipeline.