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+# MSstatsConvert 1.22.0
+
+## Protein Turnover Support
+
+* **DIA-NN**: `DIANNtoMSstatsFormat` now accepts a `labeledAminoAcids` parameter to enable protein turnover workflows. Provide the single-letter amino acid codes that carry the SILAC label (e.g. `c("K")` or `c("K", "R")`). The converter automatically distinguishes heavy and light peptide forms — either from a `Channel` column in DIA-NN 2.x exports, or by parsing SILAC modification tags (e.g. `(SILAC-K-H)`) in DIA-NN 1.x exports — and populates the `IsotopeLabelType` column required by MSstats downstream.
+
+* **Spectronaut**: `SpectronauttoMSstatsFormat` now accepts a `heavyLabels` parameter to classify peptides in protein turnover experiments. Supply the label names as they appear in square brackets in the peptide sequence (e.g. `c("Lys6")` or `c("Lys6", "Arg10")`). Peptides are automatically assigned as heavy (`H`), light (`L`), or unlabeled. Any novel label name reported by Spectronaut (e.g. `"Leu6"`, `"Phe10"`) is supported.
+
+* **Spectronaut**: A new `peptideSequenceColumn` parameter lets you specify which column in your Spectronaut export contains the peptide sequence. This is especially useful for protein turnover reports, which may use a different column layout than a standard Spectronaut output.
+
+* **Spectronaut**: Protein turnover reports that lack fragment-level columns (e.g. `FFrgLossType`, `FFrgIon`) are now handled automatically — previously these required manual pre-processing before import.
+
+* **Fraction selection**: The algorithm that selects the best fraction for each peptide feature now correctly accounts for heavy and light isotope channels in protein turnover data, ensuring that light-channel coverage is prioritized when choosing fractions. When multiple fractions have identical coverage, the fraction with the highest mean intensity is chosen.
+
+## DIA-NN Quality Control: Anomaly Detection
+
+* `DIANNtoMSstatsFormat` now supports automated data quality scoring via an isolation-forest anomaly detection model (`calculateAnomalyScores = TRUE`). When enabled, each precursor-level feature receives an anomaly score that can be used downstream in MSstats to down-weight measurements that look like outliers. Users supply the quality metric columns to use as model features (`anomalyModelFeatures`) and, optionally, a run order table (`runOrder`) to engineer temporal trend features that detect gradual instrument drift across an experiment.
+
+## Spectronaut: MS1 Quantification
+
+* `SpectronauttoMSstatsFormat` now accepts `"FG.MS1Quantity"` (and other raw Spectronaut column names) as the `intensity` argument, in addition to the existing `"PeakArea"` and `"NormalizedPeakArea"` options. 
+
 # MSstatsConvert 1.16.0
 
 * Improved memory management for efficiency.