PathogenicityRanking

An R package for computing composite pathogenicity scores to rank missense variants using multiple predictors like AlphaMissense, CADD, GERP++, and others.

Installation

You can install the development version from GitHub:

# Install devtools if you haven't already
install.packages("devtools")

# Install PathogenicityRanking
devtools::install_github("MohammadDeen/PathogenicityRanking")

Quick Start

library(PathogenicityRanking)

# Basic analysis
results <- run_pathogenicity_analysis(
  input_file = "your_variants.xlsx",
  pdf_output = "pathogenicity_ranking.pdf", 
  png_output = "pathogenicity_ranking.png",
  show_plot = TRUE
)

# Enhanced analysis with multiple visualizations
enhanced_results <- run_enhanced_analysis(
  input_file = "your_variants.xlsx",
  output_prefix = "comprehensive_analysis",
  create_heatmap = TRUE,
  create_scatter = TRUE,
  create_distribution = TRUE
)

✨ Features

• Multiple file formats: CSV, TXT, XLSX support
• Comprehensive scoring: Integrates 8 pathogenicity predictors
• Advanced visualizations: Bar charts, heatmaps, scatter plots, distributions
• Flexible analysis: Basic and enhanced analysis workflows
• Publication-ready: High-quality PDF and PNG outputs
• Real-world examples: Comprehensive vignette with practical applications

📂 Contents

• PathogenicityRankingProject.Rproj: RStudio project file
• run_pathogenicity_analysis.R: R script defining the function
• composite_score_results.csv: Output file generated after running the function (created after first run)
• variant_pathogenicity_ranking.pdf/png: Visualization outputs

🧪 Available Functions

Core Functions

run_pathogenicity_analysis()

Basic pathogenicity analysis with ranking visualization.

Argument	Description
input_file	Path to a .csv, .txt, or .xlsx file with variant data
pdf_output	Output filename for the PDF plot
png_output	Output filename for the PNG plot
show_plot	Whether to display the plot in RStudio (default: TRUE)

run_enhanced_analysis()

Comprehensive analysis with multiple visualization types.

Argument	Description
input_file	Path to variant file
output_prefix	Prefix for all output files
create_heatmap	Generate heatmap visualization
create_scatter	Generate scatter plots
create_distribution	Generate distribution plot

Visualization Functions

• create_score_heatmap(): Individual score heatmap across predictors
• create_composite_scatter(): Composite vs individual score relationships
• create_score_distribution(): Distribution analysis of composite scores | show_plot | Whether to display the plot in RStudio (default: TRUE) |

Required Columns in Input File

The input file must contain the following columns:

• AAChange.refGeneWithVer
• AlphaMissense_score
• CADD_phred
• GERP++_RS
• phyloP17way_primate
• MPC_score
• REVEL_score
• MetaSVM_score

✅ Output

• A composite pathogenicity score is calculated and visualized for each variant.
• Results are saved to CSV and plots are saved in both PDF and PNG format.

✍️ Author

Mohammad Deen Hayatu

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Feel free to customize the scoring system or add additional predictors as needed.