scplotter is an R package designed for straightforward and efficient visualization of single-cell sequencing data. It caters to bioinformaticians and researchers working with scRNA-seq, scTCR/BCR-seq, and spatial datasets, offering a unified interface to generate complex plots with minimal code. The package aims to simplify data exploration and interpretation through a comprehensive set of plotting functions and an innovative LLM-powered interface.

How It Works

Built upon the plotthis R package, scplotter provides a high-level API for creating publication-quality visualizations. It integrates with popular single-cell analysis frameworks like Seurat, LIANA, scRepertoire, and Giotto. A key differentiator is its LLM integration via tidyprompt, allowing users to generate plots using natural language prompts, abstracting away the underlying plotting functions and parameters.

Quick Start & Requirements

• Installation:
  • From GitHub: remotes::install_github("pwwang/scplotter") or devtools::install_github("pwwang/scplotter")
  • Using Conda: $ conda install pwwang::r-scplotter
• Prerequisites: R environment. Specific dependencies like Seurat, LIANA, scRepertoire, Giotto, and tidyprompt are managed by the installation process. OpenAI API key required for LLM features.
• Links: GitHub Repository (implied by install command)

Highlighted Details

• Extensive plotting capabilities for scRNA-seq (e.g., CellDimPlot, CellStatPlot, ClustreePlot), scTCR/BCR-seq (e.g., ClonalVolumePlot, ClonalAbundancePlot), and spatial data (SpatDimPlot, SpatFeaturePlot).
• Natural language plotting interface using tidyprompt and OpenAI API for interactive plot generation.
• Supports various data objects from popular single-cell analysis packages.
• Includes specialized plots for cell-cell communication (CCCPlot) and gene set enrichment analysis (GSEASummaryPlot, GSEAPlot).

Maintenance & Community

The project acknowledges contributions from packages like plotthis, tidyprompt, Seurat, LIANA, scRepertoire, and Giotto. Specific community channels or active maintainer information are not detailed in the provided README.

Licensing & Compatibility

The README does not explicitly state the software license. Compatibility is primarily within the R ecosystem, with specific support for data structures from mentioned packages.

Limitations & Caveats

The LLM-driven plotting feature requires an active OpenAI API key and incurs associated costs. The package is primarily an R library, limiting its use outside the R environment. Specific performance benchmarks or known bugs are not detailed.