compute_power_and_fdr: Calculate power and FDR
In liangyy/silver-standard-performance: Generating PR/ROC curves in light and flexible way
Description
Usage
Arguments
Value
Examples
Description
Given the set of true signals and the set of proposed signals, calculate power and false discovery rate
Usage
1
compute_power_and_fdr(discovered_genes, true_genes)
Arguments
discovered_genes
a set of proposed signals (their IDs as string)
true_genes
a set of true signals (their IDs as string)
Value
data.frame with power and fdr as columns along with nTP (number of true positives), nP (number of positives, i.e. proposed signals), and nT (number of true signals)
Examples
1
2
3
4
compute_power_and_fdr(
discovered_genes = c('g1', 'g3', 'g4'),
true_genes = c('g1', 'g2')
)
liangyy/silver-standard-performance documentation built on Dec. 5, 2019, 8:53 a.m.
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Description Usage Arguments Value Examples
Description
Given the set of true signals and the set of proposed signals, calculate power and false discovery rate
Usage
1 | compute_power_and_fdr(discovered_genes, true_genes)
|
Arguments
discovered_genes |
a set of proposed signals (their IDs as string) |
true_genes |
a set of true signals (their IDs as string) |
Value
data.frame with power and fdr as columns along with nTP (number of true positives), nP (number of positives, i.e. proposed signals), and nT (number of true signals)
Examples
1 2 3 4 | compute_power_and_fdr(
discovered_genes = c('g1', 'g3', 'g4'),
true_genes = c('g1', 'g2')
)
|
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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