fdrThreshold: Calculate p-value threshold for given FDR
In assaron/BioNet: Routines for the functional analysis of biological networks
Description
Usage
Arguments
Value
Author(s)
References
See Also
Examples
Description
The function calculates the p-value threshold tau for a given false discovery rate.
Tau is used for the scoring function.
Usage
1
fdrThreshold(fdr, fb)
Arguments
fdr
False discovery rate.
fb
Model from the beta-uniform mixture fitting.
Value
P-value threshold tau.
Author(s)
Marcus Dittrich
References
S. Pounds, S.W. Morris (2003) Estimating the occurrence of false positives and false negatives in microarray studies by approximating and partitioning the empirical distribution of p-values. Bioinformatics, 19(10): 1236-1242.
See Also
Examples
1
2
3
4
5
data(pvaluesExample)
pvals <- pvaluesExample[,1]
bum.mle <- fitBumModel(pvals, plot=FALSE)
tau <- fdrThreshold(fdr=0.001, fb=bum.mle)
tau
assaron/BioNet documentation built on Sept. 18, 2020, 12:02 a.m.
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Description Usage Arguments Value Author(s) References See Also Examples
Description
The function calculates the p-value threshold tau for a given false discovery rate. Tau is used for the scoring function.
Usage
1 | fdrThreshold(fdr, fb)
|
Arguments
fdr |
False discovery rate. |
fb |
Model from the beta-uniform mixture fitting. |
Value
P-value threshold tau.
Author(s)
Marcus Dittrich
References
S. Pounds, S.W. Morris (2003) Estimating the occurrence of false positives and false negatives in microarray studies by approximating and partitioning the empirical distribution of p-values. Bioinformatics, 19(10): 1236-1242.
See Also
Examples
1 2 3 4 5 | data(pvaluesExample)
pvals <- pvaluesExample[,1]
bum.mle <- fitBumModel(pvals, plot=FALSE)
tau <- fdrThreshold(fdr=0.001, fb=bum.mle)
tau
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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