% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/estimateLC.R
\name{estimateLC}
\alias{estimateLC}
\title{Estimate saliva cell proportions from DNA methylation beta values}
\usage{
estimateLC(meth, ref, constrained = FALSE)
}
\arguments{
\item{meth}{Numeric matrix of beta values with CpGs in rows and samples in
columns. Row names must contain probe identifiers compatible with the
selected reference.}

\item{ref}{Character. Reference panel name. Supported values are \code{'saliva'}
and \code{'salivaEPIC'}.}

\item{constrained}{Logical. If \code{TRUE}, estimated cell proportions are
constrained to sum to one.}
}
\value{
A \code{data.table} with one row per sample and one column per estimated
cell type.
}
\description{
Estimate cell-type proportions with the saliva reference panels bundled in
\code{dnaEPICO}. This function keeps the original \code{estimateLC()} interface used by
the package while using the internal reference files distributed in
\code{inst/extdata}.
}
\examples{
ref_file <- system.file("extdata", "saliva.txt", package = "dnaEPICO")
ref_panel <- as.matrix(utils::read.table(ref_file))
meth <- ref_panel[1:20, , drop = FALSE]
colnames(meth) <- c("sample1", "sample2")
estimateLC(
    meth = meth,
    ref = "saliva",
    constrained = FALSE
)

}
\references{
Murat K, et al. Ewastools: Infinium Human Methylation BeadChip pipeline for
population epigenetics integrated into Galaxy. \emph{GigaScience}.
2020;9(5):giaa049.
Houseman EA, Accomando WP, Koestler DC, et al. DNA methylation arrays as
surrogate measures of cell mixture distribution. \emph{BMC Bioinformatics}.
2012;13:86.
Reinius LE, Acevedo N, Joerink M, et al. Differential DNA methylation in
purified human blood cells: implications for cell lineage and studies on
disease susceptibility. \emph{PLoS One}. 2012;7(7):e41361.
Bakulski KM, Feinberg JI, Andrews SV, et al. DNA methylation of cord blood
cell types: applications for mixed cell birth studies. \emph{Epigenetics}.
2016;11(5):354-362.
de Goede OM, Razzaghian HR, Price EM, et al. Nucleated red blood cells
impact DNA methylation and expression analyses of cord blood hematopoietic
cells. \emph{Clinical Epigenetics}. 2015;7:95.
Gervin K, Salas LA, Bakulski KM, et al. Cell type specific DNA methylation
in cord blood: a 450K reference data set and cell count-based validation of
estimated cell type composition. \emph{Epigenetics}. 2016;11(9):690-698.
Gervin K, Salas LA, Bakulski KM, et al. Systematic evaluation and validation
of reference and library selection methods for deconvolution of cord blood
DNA methylation data. \emph{bioRxiv}. 2019. doi:10.1101/570457.
Salas LA, Koestler DC, Butler RA, et al. An optimized library for
reference-based deconvolution of whole-blood biospecimens assayed using the
Illumina HumanMethylationEPIC BeadArray. \emph{Genome Biology}. 2018;19:64.
Heiss JA, Just AC, Brenner H. Training a model for estimating leukocyte
composition using whole-blood DNA methylation and cell counts as reference.
\emph{Epigenomics}. 2017;9(1):13-20.
Middleton LYM, Dou J, Mill J, et al. Saliva cell type DNA methylation
reference panel for epidemiology studies in children. 2020.
}
