View source: R/Optimum_KernelC.R
Optimum_KernelC | R Documentation |
This function is invoked by DeMixT_GS or DeMixT_DE and DeMixT_S2 to finish parameter estimation by iterated conditional mode algorithm and reconstitute gene expression profile of all components.
Optimum_KernelC(
inputdata,
groupid,
nspikein,
setting.pi,
givenpi,
givenpiT,
niter,
ninteg,
tol,
sg0 = 0.5^2,
mu0 = 0,
pi01 = NULL,
pi02 = NULL,
nthread = 1
)
inputdata |
A matrix of expression data (e.g gene expressions) from
reference (e.g. normal) and mixed samples (e.g. mixed tumor samples). It is a
|
groupid |
A vector of indicators to denote if the corresponding samples are reference samples or mixed tumor samples. DeMixT is able to deconvolve mixed tumor samples with at most three components. We use 1 and 2 to denote the samples referencing the first and the second known component in mixed tumor samples. We use 3 to indicate mixed tumor samples prepared to be deconvolved. For example, in two-component deconvolution, we have c(1,1,...,3,3) and in three-component deconvolution, we have c(1,1,...,2,2,...,3,3). |
nspikein |
The number of spikes in normal reference used for proportion
estimation. The default value is |
setting.pi |
If it is set to 0, then deconvolution is performed without any given proportions; if set to 1, deconvolution with given proportions for the first and the second known component is run; if set to 2, deconvolution is run with given tumor proportions. This option helps to perform deconvolution in different settings. In estimation of component-specific proportions, we use a subset of genes ; so when it is required to deconvolve another subset of genes, we just easily plug back our estimated proportions by setting this option to 1. In our two-step estimation strategy in a three-component setting, this option is set to 2 to implement the second step. |
givenpi |
|
givenpiT |
|
niter |
The number of iterations used in the algorithm of iterated conditional modes. A larger value can better guarantee the convergence in estimation but increase the computation time. |
ninteg |
The number of bins used in numerical integration for computing complete likelihood. A larger value can increase accuracy in estimation but also increase the running time. Especially in three-component deconvolution, the increase of number of bins can greatly lengthen the running time. |
tol |
The convergence criterion. The default is 10^(-5). |
sg0 |
Initial value for |
mu0 |
Initial value for |
pi01 |
Initialized proportion for first kown component. The default is
|
pi02 |
Initialized proportion for second kown component. pi02 is needed
only for running a three-component model. The default is |
nthread |
The number of threads used for deconvolution when OpenMP is available in the system. The default is the number of whole threads minus one. In our no-OpenMP version, it is set to 1. |
pi |
Matrix of estimated proportions for each known component. The first row corresponds to the proportion estimate of each sample for the first known component (groupid = 1) and the second row corresponds to that for the second known component (groupid = 2). |
decovExpr |
A matrix of deconvolved expression profiles corresponding to unknown (e.g tumor) component in mixed samples for a given subset of genes. Each row corresponds to one gene and each column corresponds to one sample. |
decovMu |
Estimated |
decovSigma |
Estimated |
pi1 |
An |
pi2 |
An |
Zeya Wang, Wenyi Wang
Wang Z, Cao S, Morris J S, et al. Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration. iScience, 2018, 9: 451-460.
http://bioinformatics.mdanderson.org/main/DeMixT
# Example 1: simulated two-component data
data(test.data.2comp)
# data.N1 <- SummarizedExperiment::assays(test.data.2comp$data.N1)[[1]]
# data.Y <- SummarizedExperiment::assays(test.data.2comp$data.Y)[[1]]
# inputdata <- cbind(data.N1, data.Y)
# groupid <- c(rep(1, ncol(data.N1)), rep(3, ncol(data.Y)))
# nspikein <- 0
# Optimum_KernelC(inputdata, groupid,
# nspikein = nspikein, setting.pi = 0,
# givenpi = rep(0, 2 * ncol(data.y)),
# niter = 10, ninteg = 30, tol = 10^(-4))
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