SWAP.CalculateScores: Function to calculate the pair-wise scores with any given...

In switchBox: Utilities to train and validate classifiers based on pair switching using the K-Top-Scoring-Pair (KTSP) algorithm

Description

SWAP.CalculateScores calculates the pair-wise scores between features pairs. The user may pass a filtering function to reduce the number of starting features, or provide a restricted set of pairs to limit the reported scores to this list. The user can also pass a score-calculating function by either passing one of the scoring functions available in the package(i.e. SWAP.Calculate.SignedTSPScores and SWAP.Calculate.BasicTSPScores) or a custom function.

Usage

SWAP.CalculateScores(inputMat, phenoGroup, classes = NULL, FilterFunc = SWAP.Filter.Wilcoxon, 
  RestrictedPairs = NULL, handleTies = FALSE, verbose = FALSE, 
  score_fn = signedTSPScores, score_opts = list(), ...)

Arguments

inputMat	is a numerical matrix containing the measurements (e.g., gene expression data) to be used to build the K-TSP classifier. The columns represent samples and the rows represent the features (e.g., genes). The number of columns must agree with the length of phenoGroup. Note that rownames(inputMat) will be construed as feature names (e.g., gene symbols) in all subsequent analyses.
phenoGroup	is a factor containing the training phenotypes with two levels.
classes	is a character vector of length 2 providing the phenotype class labels (case followed by control). If NULL, the levels of phenoGroup will be taken as the labels.
FilterFunc	is a filtering function to reduce the starting number of features to be used to identify the Top Scoring Pairs (TSPs). The default filter is based on the Wilcoxon rank-sum test and alternative filtering functions can be passed too (see SWAP.Filter.Wilcoxon for details). Note the filtering function must return feature names, i.e. a subset of rownames(inputMat).
RestrictedPairs	is a character matrix with two columns containing the feature pairs to be considered for score calculations. Each row should contain a pair of feature names matching the rownames(inputMat). If RestrictedPairs is missing all available feature pairs will be considered.
handleTies	is a logical value indicating whether tie handling should be enabled or not. FALSE by default.
verbose	is a logical value indicating whether status messages will be printed or not throughout the function. FALSE by default.
score_fn	is a function for calculating TSP scores. By default, the signed TSP scores as calculated by SWAP.Calculate.SignedTSPScores will be used. The user can also provide SWAP.Calculate.BasicTSPScores to obtain basic TSP scores. The output of any custom function should correspond to the same strucure as the output from these two functions.
score_opts	is a list of additional variables that will be passed on to the scoring function as the score_opts argument.
...	Additional argument passed to the filtering function FilterFunc.

Value

The output is a list containing the following items:

labels	the levels (phenotypes) in phenoGroup.
score	is a vector containing the pair-wise scores.

Author(s)

Bahman Afsari [e-mail], Luigi Marchionni [e-mail], Wikum Dinalankara [e-mail]

References

See switchBox for the references.

See Also

See SWAP.KTSP.Train, SWAP.Filter.Wilcoxon, SWAP.Calculate.BasicTSPScores, SWAP.Calculate.SignedTSPScores, and SWAP.KTSP.Statistics.

Examples

### Load gene expression data for the training set
data(trainingData)

### Show group variable for the TRAINING set
table(trainingGroup)

### Compute the scores using all features (a matrix will be returned)
scores <- SWAP.CalculateScores(matTraining,  trainingGroup, FilterFunc=NULL)

switchBox documentation built on Nov. 8, 2020, 5:43 p.m.