QFeaturesGUI

QFeaturesGUI is a collection of Shiny applications that provide graphical user interfaces for MS-based proteomics data analysis using the Bioconductor ecosystem. It supports both bulk and single-cell proteomics (SCP) workflows and builds on the QFeatures and scp packages.

Rather than a single application, QFeaturesGUI is composed of multiple apps, each dedicated to a specific step of the proteomics data analysis workflow.

Features

• Graphical interfaces for MS-based proteomics data analysis
• Support for bulk and single-cell proteomics
• Native integration with QFeatures and scp
• Modular design with task-specific applications
• Built using Shiny and shinydashboardPlus

Available applications

Currently available applications include:

• Data import (importQFeatures)
  Import quantitative proteomics data into QFeatures objects

• Data processing (processQFeatures)
  Perform common data processing steps on QFeatures and scp objects

Additional applications will be added in future releases.

Installation

Bioconductor (recommended)

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

BiocManager::install("UCLouvain-CBIO/QFeaturesGUI")

Documentation

Package website

Import App

Processing App

Related packages

QFeaturesGUI builds upon and integrates with several Bioconductor packages and projects for MS-based proteomics and single-cell data analysis:

• QFeatures
  Data infrastructure for MS-based quantitative proteomics.

• scp
  Extension of QFeatures for single-cell proteomics data analysis.

• RforMassSpectrometry
  A collection of R packages for the analysis and interpretation of mass spectrometry data.

• SingleCellExperiment
  Core Bioconductor data container for single-cell data.

• SummarizedExperiment
  Provides a general container for high-throughput assays and associated metadata.

• MultiAssayExperiment
  Infrastructure for managing and integrating multiple assays for the same set of samples.

Contributing

Contributions to QFeaturesGUI are welcome. This includes bug reports, feature requests, and suggestions for new applications or improvements to existing ones.

Issues and enhancement requests can be submitted via the GitHub issue tracker.

When reporting bugs, please include a minimal reproducible example when possible, along with information about your R session and package versions.