RN_calc_GPV: RN_calc_GPV

In RNentropy: Entropy Based Method for the Detection of Significant Variation in Gene Expression Data

RN_calc_GPV

Description

This function calculates global p-values from expression data, represented as -log10(p-values).

Usage

RN_calc_GPV(X, bind = TRUE)

Arguments

X	data.frame with expression values. It may contain additional non numeric columns (eg. a column with gene names)
bind	See Value (Default: TRUE)

Value

If bind is TRUE the function returns a data.frame with the original expression values from 'X' and an attached column with the -log10() of the global p-value, otherwise only the numeric vector of -log10(p-values) is returned.

Author(s)

Giulio Pavesi - Dep. of Biosciences, University of Milan

Federico Zambelli - Dep. of Biosciences, University of Milan

Examples

data("RN_Brain_Example_tpm")
GPV <- RN_calc_GPV(RN_Brain_Example_tpm)

## The function is currently defined as
function (X, bind = TRUE) 
{
    rnums <- sapply(X, is.numeric)
    GL_LPV <- apply(X[rnums], 1, ".RN_calc_GPV_row")
    if (bind) {
        GPV <- cbind(X, GL_LPV)
        return(GPV)
    }
    else {
        return(GL_LPV)
    }
  }

RNentropy documentation built on April 13, 2022, 5:22 p.m.