MethScope

MethScope is an R package for ultra-fast analysis of sparse DNA methylome data using Most Recurrent Methylation Patterns (MRMPs).

It supports downstream analysis for:

• Cell type annotation
• Cell type deconvolution
• Unsupervised clustering
• Cancer cell-of-origin prediction
• Missing value imputation

Why MethScope?

Sparse single-cell and spatial methylome data are difficult to analyze directly. MethScope compresses methylation signals into MRMP-based embeddings so you can run robust and scalable downstream tasks with standard analysis workflows.

Method overview

MethScope converts high-dimensional methylation atlas signals into compact MRMP features and applies these features across multiple analysis tasks.

Core workflow:

• Binarize methylation atlas profiles and consolidate recurrent patterns
• Select top recurrent methylation patterns (MRMPs)
• Encode each sample, cell, or pixel into an MRMP-based representation
• Run downstream modeling for annotation, deconvolution, imputation, and representation learning

Use cases supported in the current pipeline:

• Cell-type annotation in sparse single-cell methylome profiles
• Mini-bulk deconvolution for mixed-cell samples
• Missing-value imputation for sparse CpG measurements
• Representation learning for clustering and embedding analysis

Installation

Install from CRAN:

install.packages("MethScope")

Or install the development version from GitHub:

remotes::install_github("zhou-lab/MethScope")

Quick start

library(MethScope)

# 1) Generate MRMP embedding from your .cg file and MRMP reference
example_file <- "example.cg"
reference_pattern <- "Liu2021_MouseBrain.cm"
input_pattern <- GenerateInput(example_file, reference_pattern)

# 2) Predict cell types with a built-in model
pred <- PredictCellType(MethScope:::Liu2021_MouseBrain_P1000, input_pattern)

# 3) Visualize prediction results
PlotUMAP(input_pattern, pred)

Tutorials and documentation

• Documentation website: zhou-lab.github.io/MethScope
• End-to-end tutorial: MethScope-Tutorial
• Building MRMP references: MethScope-MRMP

Data resources

• Example and reference data: zhou-lab/methscope_data
• .cg generation and preprocessing: YAME
• Pattern interpretation: knowYourCG

Citation

If you use MethScope, please cite (comming soon):

Fu H, Xu H, Lee CN, Cloud C, Deng Y, Zhou W.
MethScope: Ultra-Fast Analysis of Sparse DNA Methylome via Recurrent Pattern Encoding.