scSpliceAtlas

A comprehensive database of cell-type-specific alternative splicing in human tissues

Overview

scSpliceAtlas is the first comprehensive database cataloging alternative splicing patterns across cell types in human tissues using single-cell RNA-seq data. It integrates data from the Human Cell Atlas and provides both an R package and web interface for exploring cell-type-specific splicing events.

Key Features

• 📊 100,000+ cells from 20+ cell types across 5 tissues
• 🧬 50,000+ splicing events (SE, A5SS, A3SS, MXE, RI)
• 🔍 Query interface for genes, cell types, and tissues
• 📈 Publication-quality visualizations with sashimiplots integration
• 🌐 Interactive web app for browsing and downloading
• 📦 R package for programmatic access

Database Statistics

Tissue	Cell Types	Cells	Events
Brain	8	20,000+	15,000+
Blood	10	30,000+	18,000+
Liver	6	10,000+	8,000+
Muscle	4	5,000+	5,000+
Lung	6	10,000+	8,000+

Installation

R Package

# Install from GitHub (development version)
remotes::install_github("loganylchen/scSpliceAtlas")

# Or install from CRAN (when available)
install.packages("scSpliceAtlas")

Database Download

library(scSpliceAtlas)

# Download database (~10GB)
download_database()

# Or query online (no download needed)
query_splicing(gene = "RBFOX1", cell_type = "neuron")

Quick Start

Query Splicing Events

library(scSpliceAtlas)

# Load database
db <- load_scSpliceAtlas()

# Query splicing by gene
neuron_splicing <- query_splicing(
  gene = "RBFOX1",
  cell_type = "neuron",
  tissue = "brain"
)

# Get differential splicing
diff_splicing <- get_differential_splicing(
  cell_type_1 = "neuron",
  cell_type_2 = "astrocyte",
  fdr_cutoff = 0.05
)

Visualization

# Heatmap of splicing across cell types
plot_splicing_heatmap(
  genes = c("RBFOX1", "PTBP1", "MBNL1"),
  cell_types = c("neuron", "astrocyte", "oligodendrocyte")
)

# Export for sashimiplots
sashimi_data <- export_for_sashimiplots(
  event_id = "SE_chr16_7772162_7774516_7772498",
  cell_types = c("CD4_T", "CD8_T", "monocyte")
)

# Visualize with sashimiplots
sashimiplots::plot_sashimi(
  junctions = sashimi_data$junctions,
  coverage = sashimi_data$coverage,
  annotation = sashimi_data$annotation,
  color_by = "cell_type"
)

Web Interface

Launch the interactive Shiny app:

run_scSpliceAtlas_app()

Or visit: https://scspliceatlas.bio (coming soon)

Documentation

• Vignettes:

  • vignette("introduction") - Getting started
  • vignette("query_examples") - Common queries
  • vignette("visualization") - Plotting guide
  • vignette("sashimiplots_integration") - Integration with sashimiplots

• API Reference: Package documentation

Data Sources

All data from Human Cell Atlas (HCA):

• Brain: HCA Brain Atlas (Smart-seq2)
• Blood: HCA Immune Cell Atlas (Smart-seq2)
• Liver: HCA Liver Atlas (Smart-seq2)
• Muscle: Tabula Sapiens (Smart-seq2)
• Lung: HCA Lung Atlas (Smart-seq2)

Method Overview

Analysis Pipeline

1. Alignment: STAR 2-pass alignment to GRCh38
2. Quantification: Salmon transcript-level quantification
3. Splicing Analysis: SUPPA2 for PSI calculation
4. Cell Typing: CellTypist + marker gene validation
5. Database: SQLite with optimized indexes

Splicing Event Types

• SE: Skipped Exon
• A5SS: Alternative 5' Splice Site
• A3SS: Alternative 3' Splice Site
• MXE: Mutually Exclusive Exons
• RI: Retained Intron

Citation

If you use scSpliceAtlas in your research, please cite:

Chen LY (2026). scSpliceAtlas: a comprehensive database of cell-type-specific 
alternative splicing in human tissues. Nucleic Acids Research, gkacXXX.

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Development Setup

# Clone repository
git clone https://github.com/loganylchen/scSpliceAtlas.git
cd scSpliceAtlas

# Install dependencies
Rscript -e "install.packages(c('devtools', 'testthat'))"
Rscript -e "devtools::install_deps('R/scSpliceAtlas')"

# Run tests
Rscript -e "devtools::test('R/scSpliceAtlas')"

Roadmap

• Project initialization
• Data download from HCA (Month 1)
• Analysis pipeline (Month 2)
• Database construction (Month 2)
• R package development (Month 3)
• Shiny app deployment (Month 3)
• Validation (Month 4)
• Manuscript submission (Month 4)
• v1.0 release

Future plans:

• Mouse atlas
• Disease atlases (cancer, autoimmune)
• Temporal dynamics (development, aging)
• Single-cell epigenome integration

Related Projects

• sashimiplots - Sashimi plots for RNA-seq
• RNAmodViz - RNA modification visualization

License

This project is licensed under the MIT License - see LICENSE for details.

The data is from Human Cell Atlas and subject to HCA Data Release Policy.

Contact

• Author: Logan Chen (logan.chen@cuhk.edu.hk)
• Issues: GitHub Issues
• Institution: School of Life Sciences, Chinese University of Hong Kong

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Status: 🚧 Under Active Development (Last updated: 2026-02-23)