ppc.fdr {ppc} | R Documentation |
Function to estimate False Discovery rates for peaks in PPC analysis
Description
Estimate False Discovery rates for peaks in FDR analysis, using permutations
of the sample labels
Usage
ppc.fdr(data, centroid.fit, peak.fit, split.fit, ppc.fit, user.parms)
Arguments
data |
List containing mass spec data |
centroid.fit |
Result of call to ppc.make.centroid.list |
peak.fit |
Result of call to ppc.predict.peaks |
split.fit |
Result of call to ppc.find.splits |
ppc.fit |
Result of call to ppc.predict |
user.parms |
List of user defined parameters |
Value
results |
Matrix with columns- threshold used, number of peaks found, FDR |
pi0 |
Esimate of proportion of truly null peaks |
threshold |
Vector of thresholds used |
Author(s)
Balasubramanian Narasimhan and Rob Tibshirani
Examples
## for a complete worked example of this function in a PPC analysis see
## http://www-stat.stanford.edu/~tibs/PPC/Rdist/Rscript.rawdata
[Package
ppc version 1.01
Index]