% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/deconvo_tme.R
\name{deconvo_ref}
\alias{deconvo_ref}
\title{Deconvolve Using Custom Reference}
\usage{
deconvo_ref(
  eset,
  project = NULL,
  arrays = TRUE,
  method = c("svr", "lsei"),
  perm = 100,
  reference,
  scale_reference = TRUE,
  absolute.mode = FALSE,
  abs.method = "sig.score"
)
}
\arguments{
\item{eset}{Gene expression matrix.}

\item{project}{Optional project name. Default is `NULL`.}

\item{arrays}{Logical: use quantile normalization. Default is `TRUE`.}

\item{method}{Method: `"svr"` or `"lsei"`. Default is `"svr"`.}

\item{perm}{Permutations for SVR. Default is 100.}

\item{reference}{Custom reference matrix (e.g., lm22, lm6).}

\item{scale_reference}{Logical: scale reference. Default is `TRUE`.}

\item{absolute.mode}{Logical: absolute mode for SVR. Default is `FALSE`.}

\item{abs.method}{Method for absolute mode. Default is `"sig.score"`.}
}
\value{
Data frame with cell fractions. Columns suffixed with `_CIBERSORT`.
}
\description{
Cell fraction estimation using SVR or lsei methods with custom reference.
}
\examples{
# Simulate data
set.seed(123)
sim_ref <- matrix(rnorm(100 * 5), 100, 5)
rownames(sim_ref) <- paste0("Gene", 1:100)
colnames(sim_ref) <- paste0("CellType", 1:5)

sim_eset <- matrix(rnorm(100 * 3), 100, 3)
rownames(sim_eset) <- paste0("Gene", 1:100)
colnames(sim_eset) <- paste0("Sample", 1:3)

# Run deconvolution
result <- deconvo_ref(eset = sim_eset, reference = sim_ref, method = "lsei")
if (!is.null(result)) head(result)
}
\author{
Dongqiang Zeng, Rongfang Shen
}
