Package index • sigscores

Summary Scores

This is the main function to compute the summary scores

computeSigScores(): Compute the Summary Scores

Plot Summary Scores

These are the main functions to visualise the summary scores

heatmapSigScores(): Plot Summary Scores as Heatmap

heatmapCorSigScores(): Plot Correlation of Summary Scores as Heatmap

boxplotSigScores(): Plot Summary Scores as Box Plots

scatterplotSigScores(): Plot Summary Scores as Scatter Plots

histogramRndSigScores(): Plot Summary Scores as Histograms

Scorers

These are the scorers to compute the summary scores

sumScorer(): Sum Scorer

weightedSumScorer(): Weighted Sum Scorer

meanScorer(): Arithmetic Mean Scorer

trimmedMeanScorer(): Trimmed Mean Scorer

weightedMeanScorer(): Weighted Mean Scorer

medianScorer(): Median Scorer

modeScorer(): Mode Scorer

midrangeScorer(): Midrange Scorer

midhingeScorer(): Midhinge Scorer

trimeanScorer(): Trimean Scorer

iqrScorer(): Interquartile Range (IQR) Scorer

iqmScorer(): Interquartile Mean (IQM) Scorer

madScorer(): Median Absolute Deviation (MAD) Scorer

aadScorer(): Average Absolute Deviation (AAD) Scorer

ssgseaScorer(): Single Sample Gene Set Enrichment Analysis (ssGSEA) Scorer

gsvaScorer(): Gene Set Variation Analysis (GSVA) Scorer

plageScorer(): Pathway Level Analysis of Gene Expression (PLAGE) Scorer

zscoreScorer(): Z-Score Scorer

Statistical Measures for Matrix

These are the functions used to compute the statistical measures

computeColMeasures(): Computes Measure for Each Column in a Matrix

colSummations(): Column Sums

colWeightedSums(): Column Weighted Sums

colArithmeticMeans(): Column Means

colTrimmedMeans(): Column Trimmed Means

colWeightedArithmeticMeans(): Column Weighted Means

colMidpoints(): Column Medians

colModes(): Column Modes

colMidranges(): Column Midranges

colMidhinges(): Column Midhinges

colTrimeans(): Column Trimeans

colIQRs(): Column Interquartile Ranges

colIQMs(): Column Interquartile Mean

colMADs(): Column Median Absolute Deviation

colAADs(): Column Average Absolute Deviation

colSsgsea(): Single Sample Gene Set Enrichment Analysis (ssGSEA) Scores

colGsva(): Gene Set Variation Analysis (GSVA) Scores

colPlage(): Pathway Level Analysis of Gene Expression (PLAGE) Scores

colZscore(): Z-Scores

Statistical Measures for Vector

These are the functions used to compute the statistical measures

computeVectorMeasure(): Compute Measure

summation(): Sum

weightedSum(): Weighted Sum

arithmeticMean(): Arithmetic Mean

trimmedMean(): Trimmed Arithmetic Mean Score

weightedMean(): Weighted Arithmetic Mean

midpoint(): Median

modalValue(): Mode

midrange(): Midrange

midhinge(): Midhinge

trimean(): Tukey's Trimean

iqr(): Interquartile Range

IQM(): Interquartile Mean

MAD(): Median Absolute Deviation

AAD(): Average Absolute Deviation

ssgsea(): Enrichment Score

gsva(): Enrichment Score

plage(): Pathway Level Analysis of Gene Expression (PLAGE) Score

zscore(): Enrichment Score

Random Sampling

These functions are used to generate random samples of the data

sampleData(): Random Sampling

randomSignatures(): Random Sampling

Significance

Functions to compute statistical significance, confidence intervals, and standard errors.

computeSignificance(): Compute Significance of a Summary Statistic

Data Transformation

These functions are used to transform the data before computation

transformData(): Transform Data

stepFunctionTranformation(): Step Function Transformation

stepFunction(): Step Function

quantileNormalization(): Quantile Normalization

zStandardisation(): Z-Standardisation

Utility Functions

getAvailableScores(): Available Summary Scores

getAvailableDataTransformers(): Available Data Transformation Methods

getAvailableRandomSamplers(): Available Random Sampling Methods

getScorer(): Get Scorer

getScorers(): Get Scorers

getDataTransformer(): Get Data Transformation Function

createLogger(): Logger Class Constructor