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Getting Started

  • Installation
    • Creating a Virtual Environment
    • Installing ProteoPy
      • Basic Installation
      • With Notebook Support
      • Development Version
    • Dependencies
  • Tutorials
    • The proteodata format
      • 1. Anatomy of a proteodata object
      • 2. Building a valid protein-level proteodata
      • 3. Building a valid peptide-level proteodata
      • 4. is_proteodata vs check_proteodata
      • 5. Pitfalls: how valid proteodata can break
        • 5.1 Renaming an index without updating the corresponding metadata column
        • 5.2 Renaming protein_id, peptide_id, or sample_id without updating the corresponding index
        • 5.3 Infinite values from mathematical operations
      • 6. Validating layers
      • 7. Quick-reference checklist
      • Summary
    • Protein-Level Analysis Tutorial
      • Data Loading
        • Loading with pr.read.long()
        • Alternative: Annotating Data After Loading
        • Storing Metadata in .uns
        • Handling Missing Values and Zeros
      • Quality Control and Data Filtering
        • Protein Abundance Rank Plot
        • Binary Detection Heatmap
        • Removing Contaminants
        • Sample Distribution
        • Filtering Functions
        • Sample Quality Assessment
        • Coefficient of Variation (CV)
      • Data Transformations
        • Log Transformation
        • Normalization
        • Imputation
      • Dimensionality Reduction and Sample Clustering
        • Sample Correlation Matrix
      • Highly Variable Proteins
      • Differential Abundance Analysis
        • Running Statistical Tests
        • Accessing Test Results
        • Visualization
      • Hierarchical Clustering of Proteins
        • Profile Heatmap
        • Building the Hierarchical Clustering Tree
        • Determining Optimal Cluster Number
        • Cluster Assignment and Profile Visualization
      • Summary

API reference

  • proteopy
    • .read
      • .diann
        • diann()
      • .long
        • long()
    • .ann
      • .var
        • var()
      • .samples
        • samples()
      • .proteins_from_csv
        • proteins_from_csv()
    • .pp
      • .filter_samples
        • filter_samples()
      • .filter_samples_completeness
        • filter_samples_completeness()
      • .filter_var
        • filter_var()
      • .filter_var_completeness
        • filter_var_completeness()
      • .filter_proteins_by_peptide_count
        • filter_proteins_by_peptide_count()
      • .filter_samples_by_category_count
        • filter_samples_by_category_count()
      • .remove_zero_variance_vars
        • remove_zero_variance_vars()
      • .remove_contaminants
        • remove_contaminants()
      • .normalize_median
        • normalize_median()
      • .impute_downshift
        • impute_downshift()
      • .extract_peptide_groups
        • extract_peptide_groups()
      • .summarize_modifications
        • summarize_modifications()
      • .summarize_overlapping_peptides
        • summarize_overlapping_peptides()
      • .quantify_proteins
        • quantify_proteins()
      • .quantify_proteoforms
        • quantify_proteoforms()
      • .calculate_cv
        • calculate_cv()
    • .tl
      • .differential_abundance
        • differential_abundance()
      • .hclustv_tree
        • hclustv_tree()
      • .hclustv_cluster_ann
        • hclustv_cluster_ann()
      • .hclustv_profiles
        • hclustv_profiles()
      • .pairwise_peptide_correlations
        • pairwise_peptide_correlations()
      • .peptide_dendograms_by_correlation
        • peptide_dendograms_by_correlation()
      • .peptide_clusters_from_dendograms
        • peptide_clusters_from_dendograms()
      • .proteoform_scores
        • proteoform_scores()
    • .pl
      • .peptide_intensities
        • peptide_intensities()
      • .proteoform_intensities
        • proteoform_intensities()
      • .intensity_hist
        • intensity_hist()
      • .intensity_box_per_sample
        • intensity_box_per_sample()
      • .box
        • box()
      • .abundance_rank
        • abundance_rank()
      • .binary_heatmap
        • binary_heatmap()
      • .completeness
        • completeness()
      • .completeness_per_sample
        • completeness_per_sample()
      • .completeness_per_var
        • completeness_per_var()
      • .n_samples_per_category
        • n_samples_per_category()
      • .n_peptides_per_sample
        • n_peptides_per_sample()
      • .n_proteins_per_sample
        • n_proteins_per_sample()
      • .n_cat1_per_cat2_hist
        • n_cat1_per_cat2_hist()
      • .n_peptides_per_protein
        • n_peptides_per_protein()
      • .n_proteoforms_per_protein
        • n_proteoforms_per_protein()
      • .cv_by_group
        • cv_by_group()
      • .sample_correlation_matrix
        • sample_correlation_matrix()
      • .proteoform_scores
        • proteoform_scores()
      • .volcano_plot
        • volcano_plot()
      • .differential_abundance_box
        • differential_abundance_box()
      • .hclustv_profiles_heatmap
        • hclustv_profiles_heatmap()
      • .hclustv_silhouette
        • hclustv_silhouette()
      • .hclustv_elbow
        • hclustv_elbow()
      • .hclustv_profile_intensities
        • hclustv_profile_intensities()
    • .get
      • .proteoforms_df
        • proteoforms_df()
      • .differential_abundance_df
        • differential_abundance_df()
      • .tests
        • tests()
    • .datasets
      • .karayel_2020
        • karayel_2020()
    • .download
      • .contaminants
        • contaminants()
      • Frankenfield 2022 – Universal Protein Contaminant Library
      • CCP cRAP – Cambridge Centre for Proteomics cRAP
      • GPM cRAP – common Repository of Adventitious Proteins
      • MaxQuant – Contaminant Database
    • .utils
      • .is_proteodata
        • is_proteodata()
      • .check_proteodata
        • check_proteodata()
      • .is_log_transformed
        • is_log_transformed()
  • Changelog
    • [Unreleased]
      • Added
    • [0.1.0] - 2025-01-29
      • Added

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    • Bug Reports & Feature Requests
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  • Acknowledgements
    • Funding
    • Institutional support
    • Inspiration
    • Software dependencies
    • Contact
  • References
    • Citing ProteoPy
    • COPF algorithm
    • Related Publications
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