DeMixT_S2 {DeMixT} | R Documentation |
This function is designed to estimate the deconvolved expressions of individual mixed tumor samples for unknown component for each gene.
DeMixT_S2(data.Y, data.comp1, data.comp2 = NULL, givenpi, nbin = 50, nthread = parallel::detectCores() - 1)
data.Y |
A SummarizedExperiment object of expression data from mixed tumor samples. It is a G by Sy matrix where G is the number of genes and Sy is the number of mixed samples. Samples with the same tissue type should be placed together in columns. |
data.comp1 |
A SummarizedExperiment object of expression data from reference component 1 (e.g., normal). It is a G by S1 matrix where G is the number of genes and S1 is the number of samples for component 1. |
data.comp2 |
A SummarizedExperiment object of expression data from additional reference samples. It is a G by S2 matrix where G is the number of genes and S2 is the number of samples for component 2. Component 2 is needed only for running a three-component model. |
givenpi |
A vector of proportions for all mixed tumor samples. In two-component analysis, it gives the proportions of the known reference component, and in three-component analysis, it gives the proportions for the two known components. |
nbin |
The number of bins used in numerical integration for computing complete likelihood. A larger value increases accuracy in estimation but increases the running time, especially in a three-component deconvolution problem. The default is 50. |
nthread |
The number of threads used for deconvolution when OpenMP is availble in the system. The default is the number of whole threads minus one. In our no-OpenMP version, it is set to 1. |
decovExprT |
Matrix of deconvolved expression profiles corresponding to T-component in mixed samples for a given subset of genes. Each row corresponds to one gene and each column corresponds to one sample. |
decovExprN1 |
Matrix of deconvolved expression profiles corresponding to N1-component in mixed samples for a given subset of genes. Each row corresponds to one gene and each column corresponds to one sample. |
decovExprN2 |
Matrix of deconvolved expression profiles corresponding to N2-component in mixed samples for a given subset of genes in a three-component setting. Each row corresponds to one gene and each column corresponds to one sample. |
decovMu |
Estimated μ of log2-normal distribution for both known (MuN1, MuN2) and unknown component (MuT). |
decovSigma |
Estimated σ of log2-normal distribution for both known (SigmaN1, SigmaN2) and unknown component (SigmaT). |
Zeya Wang, Wenyi Wang
J. Besag. "On the statistical analysis of dirty pictures". In: Journal of the Royal Statistical Society. Series B (Methodological) (1986), pp. 259-302.
http://bioinformatics.mdanderson.org/main/DeMix:Overview
# Example 1: two-component deconvolution given proportions data(test.data1.truth) data(test.data1.y) data(test.data1.comp1) givenpi <- c(t(as.matrix(test.data1.truth[-2,]))) res <- DeMixT_S2(data.Y = test.data1.y, data.comp1 = test.data1.comp1, givenpi = givenpi) # Example 2: three-component deconvolution given proportions # This example takes 10 minutes to finish running # data(test.data2.truth) # data(test.data2.y) # data(test.data2.comp1) # data(test.data2.comp2) # givenpi <- c(t(test.data2.truth[-3,])) # res <- DeMixT_S2(data.Y = test.data2.y, data.comp1 = test.data2.comp1, # data.comp2 = test.data2.comp2, givenpi = givenpi)