Function reference • featscreen

Main Screening Function

This function provides easy access and uniform syntax to the screening methodologies.

screen(): Feature Screening

Featscreen Class

Methods to handle objects of class featscreen

featscreen(): Constructor of the featscreen class

is.featscreen(): Check a featscreen object

print(<featscreen>): Print a featscreen object

getScreeningMethodId(): Get the screening method id

getMultiresponseAggregationMethodId(): Get the multi-response aggregation method id

getSelectionMethodId(): Get the selection method id

getSummary(): Get the screening summary

getFeatureDimensionality(): Get the dimension of the feature space

getFeatureNames(): Get the feature names

getScreenedFeatures(): Get the screened features

getFeatureRanks(): Get the feature ranks

Selection Functions

These functions are used to determine which feature to keep

selectByCutoff(): Select by Cutoff

selectByRanking(): Select by Ranking

selectByPercentile(): Select by Percentile

selectByFpr(): Select by False Positive Rate (FPR)

selectByFdr(): Select by False Discovery Rate

Supervised Biostatistical Functions

These supervised functions are used to compute statistic and significance values used in the screening process.

rowEBayesStatistics(): Empirical Bayes Moderated Statistics

rowModeratedT(): Empirical Bayes Moderated t-Statistic

rowModeratedOneWayAnova(): Empirical Bayes Moderated F-Statistic

rowSamStatistics(): Significance Analysis of Microarrays

Supervised Statistical Functions

These statistical test functions are used to compute the statistic and significance values used in the screening process.

rowCor(): Row Correlations

rowPearsonCor(): Pearson's Correlation

rowSpearmanCor(): Spearman's Correlation

rowKendallCor(): Kendall's Correlation

rowTwoSampleT(): Two-sample t-Test

rowEqualVarT(): Student's t-Test

rowUnequalVarT(): Welch's t-Test

rowPairedT(): Paired t-Test

rowTwoSampleWilcoxonT(): Two-Sample Wilcoxon Rank Sum and Signed Rank Tests

rowWilcoxonT(): Wilcoxon Rank-Sum Test

rowPairedWilcoxonT(): Wilcoxon Signed-Rank Test

rowOneWayAnova(): Fit an Analysis of Variance Model

rowEqualVarOneWayAnova(): Fit an Analysis of Variance Model

rowUnequalVarOneWayAnova(): Fit an Analysis of Variance Model

rowKruskalWallis(): Kruskal-Wallis Rank Sum Test

rowPearsonChiSq(): Pearson's Chi-squared Test of Independence

rowCoxPH(): Fit Univariate Proportional Hazards Regression Model

Unupervised Statistical Functions

These unsupervised statistical functions are used to compute the statistic values used in the screening process.

rowMissingValueRatio(): Missing Value Ratio

rowAboveMedianFreqRatio(): Above-Median Frequency Ratio

rowAboveMinFreqRatio(): Above-Minimum Frequency Ratio

rowMedians(): Medians

rowVariability(): Variability

sd(): Standard Deviation

rsd(): Relative Standard Deviation (Coefficient of Variation)

iqr(): Interquartile Range

mad(): Median Absolute Deviation

snr(): Signal-to-noise Ratio

vmr(): Variance-to-mean Ratio

efficiency(): Efficiency

Filter Functions

Ready-to-use filter functions

rowFilterByMissingValueRatio(): Filter by Missing Value Ratio

rowFilterByAboveMedianRatio(): Filter by Above-Median Frequency Ratio

rowFilterByAboveMinRatio(): Filter by Above-Minimum Frequency Ratio

rowFilterByMedianAboveMinExpr(): Filter by Median Above Minimum Expression

rowFilterByLowVariability(): Filter by Low Variability

Utility Functions

multiresponse(): Combine multi-response

defaultRanking(): Default Ranking

listAvailableScreeningMethods(): Available Screening Methods

listAvailableSelectionMethods(): Available Selection Methods

listDefaultRankingOptions(): Default Ranking Options

listAvailableScreeningFunctions(): Available Screening Functions

listAvailableSelectionFunctions(): Available Selection Functions

getStatFunction(): Get Statistical Function

getSelectionFunction(): Get Selection Function

Log Functions

Logger(): Logger Class Constructor

getLogLine(): Log Line