SPIA (version 2.24.0)

plotP: SPIA two-way evidence plot

Description

Plots each pathway as a point, using the over-representation p-value, pNDE, and perturbations accumulation p-value, pPERT, as coordinates. In addition the regions where FDR and FWER adjusted pG values are less than the specified threshold are plotted. The function determines automatically which method (fisher or norminv) was used to combine the two p-values into pG, and plots the regions described above accordingly.

Usage

plotP(x,threshold=0.05)

Arguments

x
A data frame produced by spia function.
threshold
A numerical value between 0 and 1 to be used as significance threshold in inferring pathway significance.

Value

This function does not return any value. It only generates a plot.

Details

In this plot each pathway is a point and the coordinates are the log of pNDE (using a hypergeometric model) and the p-value from perturbations, pPERT. The oblique lines in the plot show the significance regions based on the combined evidence.

References

Adi L. Tarca, Sorin Draghici, Purvesh Khatri, et. al, A Signaling Pathway Impact Analysis for Microarray Experiments, 2008, Bioinformatics, 2009, 25(1):75-82.

See Also

spia

Examples

Run this code
# Examples use colorectal cancer dataset
data(colorectalcancer)

# pathway analysis based on combined evidence of ORA and perturbations
# use nB=2000 or larger for more accurate results
res<-spia(de=DE_Colorectal, all=ALL_Colorectal, organism="hsa",nB=200,plots=FALSE,verbose=TRUE,beta=NULL,combine="fisher")

#Generate the evidence plot
plotP(res,threshold=0.1)

res<-spia(de=DE_Colorectal, all=ALL_Colorectal, organism="hsa",nB=200,plots=FALSE,verbose=TRUE,beta=NULL,combine="norminv")

#Generate the evidence plot
plotP(res,threshold=0.1)

Run the code above in your browser using DataCamp Workspace