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omics4drug

An R toolkit to facilitate Mass Spectrometry-based Proteomics and Phosphoproteomics data analysis

omics4drug is designed for the analysis and visualization of Mass Spectrometry-based phosphoproteomics and proteomics data in drug discovery. The package provides functions for quality control, normalization, pathway enrichment analysis, and drug-target prediction.

Installation

To get the latest in-development features, install the development version from GitHub:

if(!requireNamespace("devtools", quietly = TRUE)) {
 install.packages("devtools")
}
devtools::install_github("yen-kim/omics4drug")

This package is also accessible for download via Zenodo with the DOI 10.5281/zenodo.17117624.

Functions

See Package index for full list of functions.

  1. Data Processing and Quality Control
  • get_count_phosphosite(): Counts and visualizes the number of unique phosphosites per sample or group, often based on a probability threshold.
  • get_count_protein(): Counts and visualizes the number of unique protein groups per sample or group.
  • get_cv(): Calculates and visualizes the coefficient of variation (CV) for a given dataset, useful for assessing data variability and quality.
  • get_sty(): Calculates and visualizes the count and percentage of phosphorylation sites (Serine (S), Threonine (T), Tyrosine (Y)).
  1. Data Normalization
  • get_norm_phos(): Normalizes phosphosite intensity data to account for variations between samples.
  • get_norm_prot(): Normalizes protein group intensity data.
  1. Functional and Pathway Enrichment Analysis
  • get_GO(): Performs Gene Ontology (GO) enrichment analysis to identify biological processes, molecular functions, or cellular components that are overrepresented in your data.
  • get_KEGG(): Performs KEGG pathway enrichment analysis to determine which biological pathways are significantly impacted.
  1. Kinase and Drug Prediction
  • get_KSEA(): Performs Kinase Substrate Enrichment Analysis (KSEA) to predict the activity of kinases based on the phosphorylation of their substrates.
  • get_inhibitor(): Predicts which drugs might target the kinases identified in your analysis, using an external database.
  1. Others

Acknowledgements

This R package was produced with support from the Copenhagen University through the DISCOVER PhD program.