DeMixT_S2 {DeMixT} | R Documentation

## Deconvolves expressions of each individual sample for unknown component

### Description

This function is designed to estimate the deconvolved expressions of individual mixed tumor samples for unknown component for each gene.

### Usage

    DeMixT_S2(data.Y, data.comp1, data.comp2 = NULL, givenpi, nbin = 50,
    nthread = parallel::detectCores() - 1)

### Arguments

`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.

### Value

`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).

### Author(s)

Zeya Wang, Wenyi Wang

### References

J. Besag. "On the statistical analysis of dirty pictures". In: Journal of the Royal Statistical Society. Series B (Methodological) (1986), pp. 259-302.

### See Also

http://bioinformatics.mdanderson.org/main/DeMix:Overview

### Examples

    # 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)

[Package DeMixT version 1.0.4 Index]