geva.input.correct {geva} | R Documentation |
Helper functions used to edit the contents from a GEVAInput
.
geva.input.correct(ginput, na.rm = TRUE, inf.rm = TRUE, invalid.col.rm = TRUE) geva.input.filter( ginput, p.value.cutoff = 0.05, by.any = FALSE, na.val = 0, ... ) geva.input.rename.rows( ginput, attr.column, dupl.rm.method = c("least.p.vals", "order") )
ginput |
A |
na.rm |
|
inf.rm |
|
invalid.col.rm |
|
p.value.cutoff |
|
by.any |
|
na.val |
|
... |
optional arguments. Accepts |
attr.column |
|
dupl.rm.method |
|
geva.input.correct
corrects the numeric input data (values and weights), removing rows that include invalid values such as NA or infinite.
geva.input.filter
attempts to select the most relevant part of the input data, removing rows containing p.values (1 - weights) above a specific threshold.
geva.input.rename.rows
replaces the row names with a column from the feature table (see GEVAInput
). The column name specified for attr.column
must be included in the names(featureTable(ginput))
. Any duplicates are removed according to the dupl.rm.method
, and the selected duplicates are stored as a new column named "renamed_id"
inside the feature table from the returned object.
A modified GEVAInput
object
## geva.input.correct example colexample1 <- runif(1000, -1, 1) # Random column 1 colexample2 <- runif(1000, -1, 1) # Random column 2 colexample3 <- runif(1000, -1, 1) # Random column 3 colexample3[runif(1000, -1, 1) < 0] = NA # Random NA's ginput = geva.merge.input(col1=colexample1, col2=colexample2, col3=colexample3) # Before the correction: print(nrow(ginput)) # Returns 1000 # Applies the correction (removes rows with NA's) ginput <- geva.input.correct(ginput) # After the correction: print(nrow(ginput)) # Returns less than 1000 ## --- ## geva.input.filter example ginput <- geva.ideal.example(1000) # Generates a random input # Before the filter: print(nrow(ginput)) # Returns 1000 # Applies the filter ginput <- geva.input.filter(ginput) # After the filter: print(nrow(ginput)) # Returns less than 1000 ## --- ## geva.input.rename.rows example ginput <- geva.ideal.example() # Generates a random input # Renames to 'Symbol' ginput <- geva.input.rename.rows(ginput, attr.column = "Symbol") print(head(ginput)) # The row names are set now as the gene symbols