top.genes {geva}

R Documentation

Top Results from GEVA

Description

Extracts the genes with a relevant classification according to the GEVA results.

Usage

top.genes(
  gevaresults,
  classif = c("similar", "factor-dependent", "factor-specific"),
  which.spec = levels(gevaresults),
  add.cols = NULL,
  ...,
  names.only = FALSE
)

Arguments

gevaresults	a GEVAResults object
classif	character vector, filters the returned genes by their final classification. Possible options are "similar", "factor-dependent", "factor-specific", "sparse", and "basal". Multiple options can be combined
which.spec	factor, filters the specific factors to be returned
add.cols	character vector with column names from the feature table (accessed by featureTable(gevaresults)). The matching columns will be added to the returned table
...	optional arguments (not used in this version)
names.only	logical, set to TRUE to return only the table row names

Value

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.

Examples

## 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

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