deconvolute {granulator} | R Documentation |
deconvolute
predicts cell type proportions from bulk
RNAseq data by applying multiple deconvolution methods.
deconvolute(m, sigMatrix, methods = get_decon_methods(), use_cores = 1)
m |
Bulk RNAseq: a genes (rows) by samples (columns) matrix containing transcript-per-million (TPM)-normalized gene expression values. |
sigMatrix |
Reference profile: a matrix or a named list of matrices. Each signature matrix should be a genes (rows) by cell types (columns) data frame containing TPM-normalized gene expression values of signature genes. |
methods |
Deconvolution methods: a character vector containing the names of the deconvolution methods to be applied. By default, all methods are run. Functions are either reimplementations of published methods or wrapper functions for published packages:
|
use_cores |
Number of cores to use for parallel processing |
Returns a list containing two elements:
coefficients: estimated cell type coefficients
proportions: estimated cell type proportions in percentage
combinations: combination of methods and signatures tested
Vincent Kuettel, Sabina Pfister
# load demo PBMCS data load_ABIS() # generate list of reference profiles to be tested sigMatrix <- list( sig1 = sigMatrix_ABIS_S0, sig2 = sigMatrix_ABIS_S1) # deconvolute decon <- deconvolute(m = bulkRNAseq_ABIS, sigMatrix = sigMatrix)