omics4drug

R/omics4drug: An R toolkit for Mass Spectrometry-based Proteomics and Phosphoproteomics data analysis

→ GitHub repository
→ Package Website

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.

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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.17117623.

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)).

2. Data Normalization

• get_norm_phos(): Normalizes phosphosite intensity data to account for variations between samples.
• get_norm_prot(): Normalizes protein group intensity data.

3. 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.

4. 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.

5. Others

• get_annotation(): Map Gene Identifiers

For a comprehensive overview of the package’s functions, check out the package website at
yen-kim.github.io/omics4drug.