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Main function "DeconRNASeq" implements an nonnegative decomposition by quadratic programming as datasets = signature*A, where "datasets" are the originally measured data matrix (e.g. genes by samples), "signature" is the signature matrix (genes by cell types) and "A" the cell type concentration matrix (cell types by samples)
● Data Source:
BioConductor
● Keywords: DeconRNASeq, methods
● Alias: DeconRNASeq.package, DeconRNASeq_package
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DeconRNASeq
(Package: DeconRNASeq) :
Function for Deconvolution of Complex Samples from RNA-Seq.
This function predicts proportions of constituting cell types from gene expression data generated from RNA-Seq data. Perform nonnegative quadratic programming to get per-sample based globally optimized solutions for constituting cell types .
● Data Source:
BioConductor
● Keywords: DeconSeq, methods
● Alias: DeconRNASeq
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A function is used to draw the plot of the condition number of signature matrices of all sizes, from a handful of genes in one extreme to the whole signature in the other.
● Data Source:
BioConductor
● Keywords:
● Alias: condplot
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A function is used to estimate the the confidence interval for the proportions predicted by deconvolution through bootstrapping.
● Data Source:
BioConductor
● Keywords:
● Alias: decon.bootstrap
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A function is used to draw the multiple plots of proportions of cells determined from deconvolution vs. proportions of the cells actually mixed. Each plot corresponds to one tissue/cell.
● Data Source:
BioConductor
● Keywords:
● Alias: multiplot
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A function is used to calculate the root-mean-square error (RMSE) for the accurracy of estimated proportions.
● Data Source:
BioConductor
● Keywords:
● Alias: rmse
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providing 
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