methFuse

methFuse implements FUSE: FUnctional SEgmentation of DNA methylation data through hierarchical clustering.

For further details please refer to our publication.

Features

• Hierarchical clustering based on methylation count matrices
• Detection of optimal number of clusters
• Summarization of segments, including stability flag
• Per-segment methylation estimates per sample

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Installation

From GitHub (Development Version)

Either using remotes: (recommended)

# Install remotes if needed
install.packages("remotes")

# Install fuseR from GitHub
# remotes::install_github("holmsusa/methFuse")
install.packages("methFuse", repos = c('https://holmsusa.r-universe.dev', 'https://cloud.r-project.org'))

or using devtools:

# Install devtools if needed
install.packages("devtools")

# Install fuseR from GitHub
# devtools::install_github("holmsusa/methFuse")
install.packages("methFuse", repos = c('https://holmsusa.r-universe.dev', 'https://cloud.r-project.org'))

System Requirements

• R version ≥ 4.0
• C++ toolchain for native code compilation

You may need platform-specific tools:

• macOS: Xcode Command Line Tools (xcode-select --install)
• Linux: build-essential
• Windows: Rtools

Supported input types

fuse.segment() supports the following input formats:

• Matrix input

  • Unmethylated counts (K0)
  • Methylated counts (K1)
  • Explicit chromosome (chr) and position (pos) vectors

• BSseq objects (Bioconductor)

  • Counts and genomic coordinates are extracted automatically
  • Requires bsseq package

• methrix objects (Bioconductor)

  • Supports large datasets via DelayedMatrix
  • Counts and genomic coordinates are extracted automatically
  • Requires methrix and DelayedArray packages

Install needed packages with

BiocManager::install(c("bsseq", "methrix", "DelayedArray"))

Quick Example

library(fuseR)
set.seed(1234)

# Generate sample data
# Unmethylated counts, T's
K0 <- matrix(
  rep(c(sample(0:20, 200, replace = TRUE), sample(20:40, 200, replace = TRUE)), 2),
  nrow = 100, byrow = TRUE
)
# Methylated counts, C's
K1 <- matrix(
  rep(c(sample(20:40, 200, replace = TRUE), sample(0:20, 200, replace = TRUE)), 2),
  nrow = 100, byrow = TRUE
)

# Perform segmentation
segment_result <- fuse.segment(
  K0, K1, 
  chr = sub("\\..*$", "", rownames(K0)), 
  pos = as.numeric(sub("^.*\\.", "", rownames(K0)))
)

# Access summary and per-segment betas
head(segment_result$summary)
head(segment_result$betas_per_segment)

Check out a full example workflow in the vignette.

License

This package is licensed under the MIT License. See LICENSE for details.

Author

Susanna Holmstrom