quantiReg: Quantify regulatory intensities of regulations

In SCBIT-YYLab/DysRegSig: Gene dysregulation analysis and construction of mechanistic signature in cancer

Description

Quantify regulatory intensities and its confidence intervals with de-biased LASSO.

Usage

quantiReg(exp.data, net, ci)

Arguments

exp.data	Expression matrix. Columns correspond to genes, rows correspond to experiments. The matrix is expected to be already normalized.
net	Conditioanl GRN output from condiGRN.
ci	Confidence interval of coefficient.

Value

A data frame containing the regulatory intensity and its confidence invertal for each regulation.

References

Javanmard A, Montanari A. Confidence intervals and hypothesis testing for high-dimensional regression. Journal of Machine Learning Research. 2014, 15(1): 2869-909.

Examples

data(ExpData)
data(tf2tar)
data(ClinData)

group.1 <- ClinData$sample[which(ClinData$binaryResponse == 'CR/PR')]
exp.1 <- ExpData[,colnames(ExpData) %in% group.1]

## using method Boruta
net.1 <- condiGRN(exp.data = exp.1, tf2tar = tf2tar, method = 'Boruta', pValue = 0.01)

## Quantify regulatory intensity
quanti.net.1 <- quantiReg(exp.data = exp.1, net = net.1, ci = 0.90)

SCBIT-YYLab/DysRegSig documentation built on July 19, 2021, 4:38 a.m.