Light-Weight Methods for Normalization and Visualization of
Microarray Data using Only Basic R Data Types
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Documentation for package ‘aroma.light’ version 3.38.0
Help Pages
| aroma.light-package | Package aroma.light |
| 1. Calibration and Normalization | 1. Calibration and Normalization |
| aroma.light | Package aroma.light |
| averageQuantile | Gets the average empirical distribution |
| averageQuantile.list | Gets the average empirical distribution |
| averageQuantile.matrix | Gets the average empirical distribution |
| backtransformAffine | Reverse affine transformation |
| backtransformAffine.matrix | Reverse affine transformation |
| backtransformPrincipalCurve | Reverse transformation of principal-curve fit |
| backtransformPrincipalCurve.matrix | Reverse transformation of principal-curve fit |
| backtransformPrincipalCurve.numeric | Reverse transformation of principal-curve fit |
| backtransformXYCurve | Fitting a smooth curve through paired (x,y) data |
| backtransformXYCurve.matrix | Fitting a smooth curve through paired (x,y) data |
| calibrateMultiscan | Weighted affine calibration of a multiple re-scanned channel |
| calibrateMultiscan.matrix | Weighted affine calibration of a multiple re-scanned channel |
| callNaiveGenotypes | Calls genotypes in a normal sample |
| callNaiveGenotypes.numeric | Calls genotypes in a normal sample |
| distanceBetweenLines | Finds the shortest distance between two lines |
| distanceBetweenLines.default | Finds the shortest distance between two lines |
| fitIWPCA | Robust fit of linear subspace through multidimensional data |
| fitIWPCA.matrix | Robust fit of linear subspace through multidimensional data |
| fitNaiveGenotypes | Fit naive genotype model from a normal sample |
| fitNaiveGenotypes.numeric | Fit naive genotype model from a normal sample |
| fitPrincipalCurve | Fit a principal curve in K dimensions |
| fitPrincipalCurve.matrix | Fit a principal curve in K dimensions |
| fitXYCurve | Fitting a smooth curve through paired (x,y) data |
| fitXYCurve.matrix | Fitting a smooth curve through paired (x,y) data |
| iwpca | Fits an R-dimensional hyperplane using iterative re-weighted PCA |
| iwpca.matrix | Fits an R-dimensional hyperplane using iterative re-weighted PCA |
| medianPolish | Median polish |
| medianPolish.matrix | Median polish |
| normalizeAffine | Weighted affine normalization between channels and arrays |
| normalizeAffine.matrix | Weighted affine normalization between channels and arrays |
| normalizeAverage | Rescales channel vectors to get the same average |
| normalizeAverage.list | Rescales channel vectors to get the same average |
| normalizeAverage.matrix | Rescales channel vectors to get the same average |
| normalizeCurveFit | Weighted curve-fit normalization between a pair of channels |
| normalizeCurveFit.matrix | Weighted curve-fit normalization between a pair of channels |
| normalizeDifferencesToAverage | Rescales channel vectors to get the same average |
| normalizeDifferencesToAverage.list | Rescales channel vectors to get the same average |
| normalizeFragmentLength | Normalizes signals for PCR fragment-length effects |
| normalizeFragmentLength.default | Normalizes signals for PCR fragment-length effects |
| normalizeLoess | Weighted curve-fit normalization between a pair of channels |
| normalizeLoess.matrix | Weighted curve-fit normalization between a pair of channels |
| normalizeLowess | Weighted curve-fit normalization between a pair of channels |
| normalizeLowess.matrix | Weighted curve-fit normalization between a pair of channels |
| normalizeQuantile | Normalizes the empirical distribution of one of more samples to a target distribution |
| normalizeQuantile.default | Normalizes the empirical distribution of one of more samples to a target distribution |
| normalizeQuantileRank | Normalizes the empirical distribution of one of more samples to a target distribution |
| normalizeQuantileRank.list | Normalizes the empirical distribution of one of more samples to a target distribution |
| normalizeQuantileRank.matrix | Normalizes the empirical distribution of a set of samples to a common target distribution |
| normalizeQuantileRank.numeric | Normalizes the empirical distribution of one of more samples to a target distribution |
| normalizeQuantileSpline | Normalizes the empirical distribution of one or more samples to a target distribution |
| normalizeQuantileSpline.list | Normalizes the empirical distribution of one or more samples to a target distribution |
| normalizeQuantileSpline.matrix | Normalizes the empirical distribution of one or more samples to a target distribution |
| normalizeQuantileSpline.numeric | Normalizes the empirical distribution of one or more samples to a target distribution |
| normalizeRobustSpline | Weighted curve-fit normalization between a pair of channels |
| normalizeRobustSpline.matrix | Weighted curve-fit normalization between a pair of channels |
| normalizeSpline | Weighted curve-fit normalization between a pair of channels |
| normalizeSpline.matrix | Weighted curve-fit normalization between a pair of channels |
| normalizeTumorBoost | Normalizes allele B fractions for a tumor given a match normal |
| normalizeTumorBoost.numeric | Normalizes allele B fractions for a tumor given a match normal |
| pairedAlleleSpecificCopyNumbers | Calculating tumor-normal paired allele-specific copy number stratified on genotypes |
| pairedAlleleSpecificCopyNumbers.numeric | Calculating tumor-normal paired allele-specific copy number stratified on genotypes |
| plotDensity | Plots density distributions for a set of vectors |
| plotDensity.data.frame | Plots density distributions for a set of vectors |
| plotDensity.density | Plots density distributions for a set of vectors |
| plotDensity.list | Plots density distributions for a set of vectors |
| plotDensity.matrix | Plots density distributions for a set of vectors |
| plotDensity.numeric | Plots density distributions for a set of vectors |
| plotMvsA | Plot log-ratios vs log-intensities |
| plotMvsA.matrix | Plot log-ratios vs log-intensities |
| plotMvsAPairs | Plot log-ratios/log-intensities for all unique pairs of data vectors |
| plotMvsAPairs.matrix | Plot log-ratios/log-intensities for all unique pairs of data vectors |
| plotMvsMPairs | Plot log-ratios vs log-ratios for all pairs of columns |
| plotMvsMPairs.matrix | Plot log-ratios vs log-ratios for all pairs of columns |
| plotXYCurve | Plot the relationship between two variables as a smooth curve |
| plotXYCurve.matrix | Plot the relationship between two variables as a smooth curve |
| plotXYCurve.numeric | Plot the relationship between two variables as a smooth curve |
| robustSmoothSpline | Robust fit of a Smoothing Spline |
| robustSmoothSpline.default | Robust fit of a Smoothing Spline |
| sampleCorrelations | Calculates the correlation for random pairs of observations |
| sampleCorrelations.matrix | Calculates the correlation for random pairs of observations |
| sampleTuples | Sample tuples of elements from a set |
| sampleTuples.default | Sample tuples of elements from a set |
| wpca | Light-weight Weighted Principal Component Analysis |
| wpca.matrix | Light-weight Weighted Principal Component Analysis |