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SmartPhos

A phosphoproteomics data analysis package with an interactive ShinyApp

Bioconductor version: 3.23 · Package version: 1.2.0

To facilitate and streamline phosphoproteomics data analysis, we developed SmartPhos, an R package for the pre-processing, quality control, and exploratory analysis of phosphoproteomics data generated by MaxQuant and Spectronaut. The package can be used either through the R command line or through an interactive ShinyApp called SmartPhos Explorer. The package contains methods such as normalization and normalization correction, transformation, imputation, batch effect correction, PCA, heatmap, differential expression, time-series clustering, gene set enrichment analysis, and kinase activity inference.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("SmartPhos")

Details

MaintainerShubham Agrawal <shubhamagrawal2706@gmail.com>
AuthorShubham Agrawal [aut, cre] (ORCID: <https://orcid.org/0009-0005-2630-9342>), Junyan Lu [aut] (ORCID: <https://orcid.org/0000-0002-9211-0746>)
LicenseGPL-3
URLhttps://lu-group-ukhd.github.io/SmartPhos/
Bug Reportshttps://github.com/Bioconductor/SmartPhos/issues
Downloads rank74
Source branchRELEASE_3_23
biocViewsBatchEffect, Clustering, DifferentialExpression, GUI, GeneExpression, GeneSetEnrichment, MassSpectrometry, Normalization, Preprocessing, Proteomics, QualityControl, ShinyApps, Software, Visualization

Documentation

Download

Dependencies

Depends: R (>= 4.4.0)

Imports: MultiAssayExperiment, SummarizedExperiment, data.table, shiny, shinythemes, shinyjs, shinyBS, shinyWidgets, parallel, DT, tools, stats, ggplot2, plotly, ggbeeswarm, pheatmap, grid, XML, MsCoreUtils, imputeLCMD, missForest, limma, proDA, decoupleR, piano, BiocParallel, doParallel, doRNG, e1071, magrittr, matrixStats, rlang, stringr, tibble, dplyr, tidyr, Biobase, vsn, factoextra, cowplot

Suggests: knitr, BiocStyle, PhosR, testthat