Description Usage Arguments Value Author(s) References See Also Examples

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

1 2 3 4 5 6 7 8 | ```
DeMixT_S2(
data.Y,
data.N1,
data.N2 = NULL,
givenpi,
nbin = 50,
nthread = parallel::detectCores() - 1
)
``` |

`data.Y` |
A SummarizedExperiment object of expression data from mixed
tumor samples. It is a |

`data.N1` |
A SummarizedExperiment object of expression data
from reference component 1 (e.g., normal). It is a |

`data.N2` |
A SummarizedExperiment object of expression data from
additional reference samples. It is a |

`givenpi` |
A vector of proportions for all mixed tumor samples. In two-component analysis, it gives the proportions of the unknown reference component, and in three-component analysis, it gives the proportions for the two known components. |

`nbin` |
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 available in the system. The default is the number of whole threads minus one. In our no-OpenMP version, it is set to 1. |

`decovExprT` |
A 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` |
A 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` |
A 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` |
A matrix of estimated |

`decovSigma` |
Estimated |

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
# Example 1: two-component deconvolution given proportions
data(test.data.2comp)
givenpi <- c(t(as.matrix(test.data.2comp$pi[-2,])))
res.S2 <- DeMixT_S2(data.Y = test.data.2comp$data.Y,
data.N1 = test.data.2comp$data.N1,
data.N2 = NULL,
givenpi = givenpi,
nbin = 50)
#
# Example 2: three-component deconvolution given proportions
# data(test.data.3comp)
# givenpi = c(t(test.data.3comp$pi[-3,]))
# res <- DeMixT_S2(data.Y = test.data.3comp$data.Y,
# data.N1 = test.data.3comp$data.N1,
# data.N2 = test.data.3comp$data.N2,
# givenpi = givenpi,
# nbin = 50)
``` |

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