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DeconRNASeq (version 1.14.0)

Deconvolution of Heterogeneous Tissue Samples for mRNA-Seq data

Description

DeconSeq is an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It modeled expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles.

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Version

Version

1.14.0

License

GPL-2

Maintainer

Ting Gong

Last Published

February 15th, 2017

Functions in DeconRNASeq (1.14.0)

DeconRNASeq

Function for Deconvolution of Complex Samples from RNA-Seq.
condplot

Draw the plot of the condition numbers vs. the number of genes in the signature matrix
datasets

data objects for liver and kidney mixing samples
decon.bootstrap

Estimate the confidence interval for the proportions predicted by deconvolution
fraction

mixing fractions for multi-tissues mixing samples
array.signatures

data objects for rat liver and brain pure samples
multi_tissue

data objects for multi-tissues mixing samples
liver_kidney

data objects for liver and kidney mixing samples
signatures

data objects for liver and kidney pure samples
DeconRNASeq-package

package DeconRNASeq contains function "DeconRNASeq", implementing the decomposition of RNA-Seq expression profilings of heterogeneous tissues into cell/tissue type specific expression and cell type concentration based on cell-type-specific reference measurements.
x.signature.filtered.optimal

selected signatures from multi-tissues pure samples
multiplot

Draw the plots of proportions of cells determined from deconvolution vs. proportions of the cells actually mixed (when available) with RMSE.
proportions

proportions for liver and kidney mixing samples
all.datasets

data objects for rat liver_brain samples
x.signature

data objects for multi-tissues pure samples
array.proportions

proportions for rat liver and brain mixing samples
rmse

Calculate the differences between proportions predicted by deconvolution and the values actually measured
x.data

data objects for multi-tissues mixing samples
x.signature.filtered

filtered signatures for multi-tissues pure samples