methFuse implements FUSE: FUnctional SEgmentation of DNA methylation data through hierarchical clustering.
Either using remotes: (recommended)
# Install remotes if needed
install.packages("remotes")
# Install fuseR from GitHub
remotes::install_github("holmsusa/methFuse")or using devtools:
# Install devtools if needed
install.packages("devtools")
# Install fuseR from GitHub
devtools::install_github("holmsusa/methFuse")You may need platform-specific tools:
fuse.segment() supports the following input formats:
K0)K1)chr) and position
(pos) vectorsDelayedMatrixInstall needed packages with
BiocManager::install(c("bsseq", "methrix", "DelayedArray"))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.
This package is licensed under the MIT License. See LICENSE for details.
Susanna Holmstrom