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Changelog

All notable changes to ProteoPy will be documented in this file. The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]

[0.1.1] - 2025-03-24

Added

  • Preprocessing (pr.pp): summarize_modifications() for modification summarization
  • Analysis (pr.tl): ANOVA support in differential_abundance()
  • Visualization (pr.pl): binary_heatmap(), box(), volcano(), peptides_on_sequence(), peptides_on_prot_sequence(); print_stats parameter across multiple plot functions
  • Datasets (pr.datasets): williams_2018() and karayel_2020() download functions
  • Utilities (pr.utils): Public API with is_proteodata(), check_proteodata(), is_log_transformed()
  • Documentation: Sphinx documentation site; proteoform inference and protein-level analysis tutorials

Changed

  • Reader (pr.read): diann() now supports version >=1.9.1 with automatic version dispatch
  • Preprocessing (pr.pp): impute_downshift() now supports group_by; normalize_median() gains method parameter; remove_contaminants() defaults to inplace=True
  • Validation: is_proteodata() now checks for NaN in ID columns, infinite values in .X/layers, and obs/var index sync

Fixed

  • volcano_plot type incompatibility and label display
  • n_cat1_per_cat2_hist minimum bin width

[0.1.0] - 2025-01-29

Initial release of ProteoPy.

Added

  • Data import (pr.read): Support for DIA-NN and generic long-format tables
  • Annotation (pr.ann): Functions to annotate samples (.obs) and variables (.var)
  • Quality control (pr.pp): Completeness filtering, CV calculation, contaminant removal
  • Preprocessing (pr.pp): Median normalization, downshift imputation
  • Differential abundance (pr.tl): t-test, Welch's test, ANOVA with multiple testing correction
  • Proteoform inference (pr.tl): COPF algorithm reimplementation for detecting functional proteoform groups
  • Visualization (pr.pl): Volcano plots, abundance rank plots, intensity distributions, CV plots, correlation matrices, hierarchical clustering profiles
  • Datasets (pr.datasets): Built-in example datasets (Karayel 2020)