EntrapmentAnalyses.jl

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EntrapmentAnalyses.jl is a Julia package for entrapment-based false discovery rate (FDR) analysis in proteomics data. It implements both combined and paired empirical FDR (EFDR) methods for precursor-level and protein-level analyses.

Features

  • Data Loading: Support for Parquet and TSV file formats
  • EFDR Calculation: Both combined and paired empirical FDR methods
  • Protein Analysis: Protein-level rollup and per-run analysis
  • Visualization: Automated generation of EFDR plots and reports
  • Performance: Optimized for large-scale proteomics datasets

Installation

Navigate to the EntrapmentAnalyses directory. Use ] to enter Pkg mode.


(@v1.11) pkg> activate .
  Activating project at `~/Projects/EntrapmentAnalysesJmod/EntrapmentAnalyses`

julia> using Revise, EntrapmentAnalyses
Precompiling EntrapmentAnalyses...
  1 dependency successfully precompiled in 6 seconds. 273 already precompiled.

Quick Start

using EntrapmentAnalyses

# Run precursor-level EFDR analysis
results = run_efdr_analysis(
    ["data/psm_results.parquet"],
    "data/spectral_library.tsv";
    output_dir="output"
)

# Run protein-level EFDR analysis
protein_results = run_protein_efdr_analysis(
    ["data/psm_results.parquet"],
    "data/spectral_library.tsv";
    output_dir="output"
)

Documentation Contents

Package Overview

EntrapmentAnalyses.jl provides a comprehensive toolkit for analyzing entrapment-based FDR in proteomics experiments. The package is designed to handle the complete workflow from data loading through analysis to visualization.

Key Components

  1. Data Loading: Robust handling of various input formats with automatic missing value management
  2. Pairing System: Sophisticated peptide pairing that respects both file and plex boundaries
  3. EFDR Methods: Implementation of both combined and paired EFDR calculations
  4. Protein Analysis: Tools for protein-level rollup and per-run analysis
  5. Visualization: Automated plot generation with customizable parameters

Workflow

  1. Load PSM results and spectral library data
  2. Compute peptide pairings with plex-aware complement scoring
  3. Calculate per-file q-values
  4. Perform EFDR analysis (combined and/or paired)
  5. Generate visualizations and reports
  6. Optional: Perform protein-level analysis

Getting Help