annotatePC | R Documentation |
This function finds the RAV with the highest validation score (including RAVs with negative silhouette width) for specified PC of the dataset and returns the top enriched pathways.
annotatePC(
PCnum,
val_all,
RAVmodel,
n = 5,
scoreCutoff = 0.5,
nesCutoff = NULL,
simplify = TRUE,
abs = FALSE,
trimed_pathway_len = 45
)
PCnum |
A numeric vector. PC number of your dataset to retrieve
annotation results for. The vector can contain any integer number among
|
val_all |
The output from |
RAVmodel |
The RAVmodel used to generate the input for the argument,
|
n |
An integer. Default is 5. The number of the top enriched pathways
to print out. If there are fewer than n pathways passed the cutoff, it will
print out |
scoreCutoff |
A numeric value for the minimum correlation between loadings of the dataset principal component and the RAV. Default is 0.5. |
nesCutoff |
A numeric value for the minimum Normalized Enrichment Score
(NES) for the enrichment analysis. Default is |
simplify |
A logical. Under default ( |
abs |
Default is |
trimed_pathway_len |
Positive integer values, which is the display width of pathway names. Default is 45. |
A data frame of a list based on the simplify
argument. Check
the output detail above.
data(miniRAVmodel)
library(bcellViper)
data(bcellViper)
val_all <- validate(dset, miniRAVmodel)
annotatePC(2, val_all, miniRAVmodel)
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