Quick link

Function	Code
V4	https://github.com/WonyoungCho/MethylCIBERSORT/blob/main/R/V4_Functions.R
toptable	https://github.com/WonyoungCho/MethylCIBERSORT/blob/main/R_ref/toptable.R
lmfit	https://github.com/WonyoungCho/MethylCIBERSORT/blob/main/R_ref/lmfit.R

MethylCIBERSORT

Pan-cancer deconvolution of tumour composition using DNA methylation (2018)

MethylCIBERSORT v2.0.1 https://zenodo.org/record/1298968#.YiMc5ehBzmg

pak::local_install("pak/MethylCIBERSORT")

#!/usr/bin/env Rscript

args = commandArgs(trailingOnly=TRUE)
beta_file <- args[1]
project <- args[2]

## Mat <- read.table(file="beta_values.tsv", sep = '\t', header = TRUE, row.names=1)
Mat <- read.table(file=beta_file, sep = '\t', header = TRUE, row.names=1)
head(Mat)

library("MethylCIBERSORT")

data("StromalMatrix_V2")

Stromal_v2 <- Stromal_v2[sort(rownames(Stromal_v2)),]

Int <- intersect(rownames(Mat), rownames(Stromal_v2))
Mat <- Mat[match(Int, rownames(Mat)),]
Stromal_v2 <- Stromal_v2[match(Int, rownames(Stromal_v2)),]

RefData <- Stromal_v2
RefPheno <- Stromal_v2.pheno

Signature <- FeatureSelect.V4(CellLines.matrix = NULL,
                              Heatmap = TRUE,
                              export = TRUE,
                              sigName = "MyReference",
                              Stroma.matrix = RefData,
                              deltaBeta = 0.2,
                              FDR = 0.01,
                              MaxDMRs = 100,
                              Phenotype.stroma = RefPheno)
prep <- Prep.CancerType(Beta = Mat, Probes = rownames(Signature$SignatureMatrix), fname = "ExportData")

Cell type

CD4+ : regulatory T (Treg) cells and conventional T helper (Th) cells.
CD14+ : Monocyte and macrophages.
CD19+ : B cells
CD56+ : NK cells

Reference