Estimate saliva cell proportions from DNA methylation beta values

Source: R/estimateLC.R

Estimate cell-type proportions with the saliva reference panels bundled in dnaEPICO. This function keeps the original estimateLC() interface used by the package while using the internal reference files distributed in inst/extdata.

estimateLC(meth, ref, constrained = FALSE)

Arguments

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.

ref

Character. Reference panel name. Supported values are "saliva" and "salivaEPIC".

constrained

Logical. If TRUE, estimated cell proportions are constrained to sum to one.

Value

A data.table with one row per sample and one column per estimated cell type.

References

Murat K, et al. Ewastools: Infinium Human Methylation BeadChip pipeline for population epigenetics integrated into Galaxy. GigaScience. 2020;9(5):giaa049. Houseman EA, Accomando WP, Koestler DC, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. 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. 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. 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. 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. 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. 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. 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. 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.

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
)
#>    Leukocytes Epithelial.cells
#>         <num>            <num>
#> 1:          1                0
#> 2:          0                1