R Shiny App for the Analysis of Proteomics Data
This repository contains the code for a Shiny application designed for reproducible analysis of proteomics data. The app is built using R and leverages the DEP package to streamline common steps in a proteomics workflow, from data preprocessing to statistical analysis of the differentially expressed data.
The app could be installed locally via GitHub using the following commands (please note that devtools package should be installed before installing the app):
- Check if devtools is installed, and install if not
if (!requireNamespace("devtools", quietly = TRUE)) { install.packages("devtools") }
- Use
devtoolsto install the ShinyApp
devtools::install_github("sumuko98/ProteATO-app")
- Finally, run the app
library(ProteATO)
ProteATO::runApp()
Data Input: Upload of the proteomics data and experimental design files.
Preprocessing: Removes contaminants, handles duplicate gene names, and provides options for missing value filtering.
Normalization: Offers Variance Stabilizing Normalization (VSN) to correct systematic biases.
Imputation: Supports multiple methods for handling missing values, including "bpca", "knn", "MinProb", and "QRILC".
Exploratory Analysis: Includes a Venn diagram, overlap plots, protein counts visualization, missing value heatmaps, and intensity distribution plots.
Differential Analysis: Conducts differential enrichment analysis with customizable contrasts and visualizations like volcano plots and p-value histograms.
Functional Enrichment: Performs Gene Ontology (GO) and KEGG pathway enrichment analyses.
PCA and ANOVA: Provides PCA plots and supports ANOVA for selected conditions.