top.genes {geva} | R Documentation |
Extracts the genes with a relevant classification according to the GEVA results.
top.genes( gevaresults, classif = c("similar", "factor-dependent", "factor-specific"), which.spec = levels(gevaresults), add.cols = NULL, ..., names.only = FALSE )
gevaresults |
a |
classif |
|
which.spec |
|
add.cols |
|
... |
optional arguments (not used in this version) |
names.only |
|
If names.only
is FALSE
(the default), returns a subset of the resultstable
slot (data.frame
) from the gevaresults
that includes only the filtered genes according to the function parameters.
Otherwise, if names.only
is TRUE
, returns only the row names (character
vector) of this table subset.
## Basic usage with a random generated input ginput <- geva.ideal.example() # Generates a random input example gresults <- geva.quick(ginput) # Performs the entire analysis (default parameters) # Gets a table that includes all the top genes dtgenes <- top.genes(gresults) # Gets the top genes table head(dtgenes) # Prints the first results # Appends the "Symbol" column to the results table dtgenes <- top.genes(gresults, add.cols="Symbol") head(dtgenes) # Prints the first results # Appends all feature columns to the results table dtgenes <- top.genes(gresults, add.cols=names(featureTable(gresults))) head(dtgenes) # Prints the first results # Gets only the factor-specific genes dtgenes <- top.genes(gresults, "factor-specific") head(dtgenes) # Prints the first results # Gets only the factor-specific genes for "Cond_1" factor (if any) dtgenes <- top.genes(gresults, "factor-specific", "Cond_1") head(dtgenes) # Prints the first results