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A Comprehensive and Integrated Framework for Transcriptomic Data Analysis

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omicScope

Codecov test coverage Lifecycle: experimental GitHub issues

Overview

omicScope is a comprehensive R package for one-stop RNA-seq data analysis and visualization. Built on the SummarizedExperiment data structure and modern S4 object-oriented framework, omicScope provides a unified interface for the entire RNA-seq analysis workflow - from mapped BAM files or raw count matrices to meaningful biological insights. By leveraging the well-established Bioconductor infrastructure, omicScope ensures seamless integration with the broader ecosystem of genomic analysis tools.

We recommend using the GTF file from Ensembl for quantification and annotation for now.

Key Features

  • 📦 Data Normalization: Multiple normalization methods (CPM, TPM, RPKM/FPKM)
  • 📦 Dimensionality Reduction: PCA, t-SNE, UMAP analysis
  • 📦 Differential Expression: Integration with DESeq2, edgeR, and limma
  • 📦 Functional Enrichment: GO, KEGG, and custom gene set enrichment analysis
  • 📦 Activity Inference: Pathway and transcription factor activity estimation using decoupleR
  • 📦 TME Analysis: Seamless integration with IOBR package for tumor microenvironment deconvolution and signature scoring
  • 📦 Multi-Source Data Support: Direct compatibility with TCGAbiolinks and UCSC Xena datasets for streamlined downstream analysis
  • 📦 Rich Visualizations: Publication-ready plots including heatmaps, volcano plots, and correlation matrices
  • 📦 S4 Object System: Organized data management and reproducible analysis workflows

⚠️ Development Status: omicScope is currently under active development. We welcome feedback, suggestions, and contributions from the community. If you have ideas for new features or improvements, please feel free to submit pull requests or open issues!

Installation

You can install the development version of omicScope from GitHub:

# Install from GitHub
if (!requireNamespace("devtools", quietly = TRUE)) {
    install.packages("devtools")
}
devtools::install_github("junjunlab/omicScope")

# Or using pak (recommended)
if (!requireNamespace("pak", quietly = TRUE)) {
    install.packages("pak")
}
pak::pak("junjunlab/omicScope")

Documentation

A detailed documentation is at https://junjunlab.github.io/omicScope-documentation/.

Contributing

omicScope is an open-source project and we actively encourage community contributions! Whether you're interested in:

  • 💡 Bug fixes - Help us identify and resolve issues.
  • 💡 New features - Propose and implement new analytical capabilities.
  • 💡 Documentation - Improve examples, tutorials, or function documentation.
  • 💡 Testing - Add unit tests or test with your own datasets.
  • 💡 Ideas - Share suggestions for improvements or new directions.

Future plan

Subsequent versions will incorporate enhanced functionality and additional features to extend the package's analytical capabilities.

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