Omics Data Integration Project

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Documentation for package ‘mixOmics’ version 6.0.0

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B C D E I K L M N P R S T U V W Y

-- B --

block.pls Horizontal Partial Least Squares (PLS) integration
block.plsda Horizontal Partial Least Squares - Discriminant Analysis (PLS-DA) integration
block.spls Horizontal sparse Partial Least Squares (sPLS) integration
block.splsda Horizontal sparse Partial Least Squares - Discriminant Analysis (sPLS-DA) integration
breast.TCGA Breast Cancer multi omics data from TCGA
breast.tumors Human Breast Tumors Data

-- C --

cim Clustered Image Maps (CIMs) ("heat maps")
cimDiablo Clustered Image Maps (CIMs) ("heat maps") for DIABLO
circosPlot circosPlot for DIABLO
color.GreenRed Color Palette for mixOmics
color.jet Color Palette for mixOmics
color.mixo Color Palette for mixOmics
color.spectral Color Palette for mixOmics

-- D --

diverse.16S 16S microbiome data: most diverse bodysites from HMP

-- E --

estim.regul Estimate the parameters of regularization for Regularized CCA
estim.regul.default Estimate the parameters of regularization for Regularized CCA
explained_variance Calculation of explained variance

-- I --

image.estim.regul Plot the cross-validation score.
image.tune.rcc Plot the cross-validation score.
imgCor Image Maps of Correlation Matrices between two Data Sets
ipca Independent Principal Component Analysis

-- K --

Koren.16S 16S microbiome atherosclerosis study

-- L --

linnerud Linnerud Dataset
liver.toxicity Liver Toxicity Data
logratio.transfo Log-ratio transformation

-- M --

map Classification given Probabilities
mat.rank Matrix Rank
mint.block.pls Horizontal and Vertical integration
mint.block.plsda Horizontal and Vertical Discriminant Analysis integration
mint.block.spls Horizontal and Vertical sparse integration with variable selection
mint.block.splsda Horizontal and Vertical Discriminant Analysis integration with variable selection
mint.pls Vertical integration
mint.plsda Vertical Discriminant Analysis integration
mint.spls Vertical integration with variable selection
mint.splsda Vertical Discriminant Analysis integration with variable selection
mixOmics PLS-derived methods: one function to rule them all
multidrug Multidrug Resistence Data
multilevel Multilevel analysis for repeated measurements (cross-over design)
multilevel.spls Multilevel analysis for repeated measurements (cross-over design)
multilevel.splsda Multilevel analysis for repeated measurements (cross-over design)

-- N --

nearZeroVar Identification of zero- or near-zero variance predictors
network Relevance Network for (r)CCA and (s)PLS regression
network.default Relevance Network for (r)CCA and (s)PLS regression
network.pls Relevance Network for (r)CCA and (s)PLS regression
network.rcc Relevance Network for (r)CCA and (s)PLS regression
network.spls Relevance Network for (r)CCA and (s)PLS regression
nipals Non-linear Iterative Partial Least Squares (NIPALS) algorithm
nutrimouse Nutrimouse Dataset

-- P --

pca Principal Components Analysis
pcatune Tune the number of principal components in PCA
perf Compute evaluation criteria for PLS, sPLS, PLS-DA, sPLS-DA, MINT and DIABLO
perf.mint.splsda Compute evaluation criteria for PLS, sPLS, PLS-DA, sPLS-DA, MINT and DIABLO
perf.pls Compute evaluation criteria for PLS, sPLS, PLS-DA, sPLS-DA, MINT and DIABLO
perf.plsda Compute evaluation criteria for PLS, sPLS, PLS-DA, sPLS-DA, MINT and DIABLO
perf.sgccda Compute evaluation criteria for PLS, sPLS, PLS-DA, sPLS-DA, MINT and DIABLO
perf.spls Compute evaluation criteria for PLS, sPLS, PLS-DA, sPLS-DA, MINT and DIABLO
perf.splsda Compute evaluation criteria for PLS, sPLS, PLS-DA, sPLS-DA, MINT and DIABLO
plot.perf Plot for model performance
plot.rcc Canonical Correlations Plot
plotArrow Arrow sample plot
plotContrib Contribution plot of variables
plotDiablo Graphical output for the DIABLO framework
plotIndiv Plot of Individuals (Experimental Units)
plotIndiv.mint.spls Plot of Individuals (Experimental Units)
plotIndiv.mint.splsda Plot of Individuals (Experimental Units)
plotIndiv.pca Plot of Individuals (Experimental Units)
plotIndiv.pls Plot of Individuals (Experimental Units)
plotIndiv.rcc Plot of Individuals (Experimental Units)
plotIndiv.rgcca Plot of Individuals (Experimental Units)
plotIndiv.sgcca Plot of Individuals (Experimental Units)
plotIndiv.sipca Plot of Individuals (Experimental Units)
plotIndiv.spls Plot of Individuals (Experimental Units)
plotLoadings Plot of Loading vectors
plotLoadings.block.pls Plot of Loading vectors
plotLoadings.block.plsda Plot of Loading vectors
plotLoadings.block.spls Plot of Loading vectors
plotLoadings.block.splsda Plot of Loading vectors
plotLoadings.mint.pls Plot of Loading vectors
plotLoadings.mint.plsda Plot of Loading vectors
plotLoadings.mint.spls Plot of Loading vectors
plotLoadings.mint.splsda Plot of Loading vectors
plotLoadings.pca Plot of Loading vectors
plotLoadings.pls Plot of Loading vectors
plotLoadings.plsda Plot of Loading vectors
plotLoadings.rcc Plot of Loading vectors
plotLoadings.rgcca Plot of Loading vectors
plotLoadings.sgcca Plot of Loading vectors
plotLoadings.sgccda Plot of Loading vectors
plotLoadings.spls Plot of Loading vectors
plotLoadings.splsda Plot of Loading vectors
plotVar Plot of Variables
plotVar.pca Plot of Variables
plotVar.pls Plot of Variables
plotVar.plsda Plot of Variables
plotVar.rcc Plot of Variables
plotVar.rgcca Plot of Variables
plotVar.sgcca Plot of Variables
plotVar.spca Plot of Variables
plotVar.spls Plot of Variables
plotVar.splsda Plot of Variables
pls Partial Least Squares (PLS) Regression
plsda Partial Least Squares Discriminant Analysis (PLS-DA).
predict.mint.block.pls Predict Method for (mint).(block).(s)pls(da) methods
predict.mint.block.plsda Predict Method for (mint).(block).(s)pls(da) methods
predict.mint.block.spls Predict Method for (mint).(block).(s)pls(da) methods
predict.mint.block.splsda Predict Method for (mint).(block).(s)pls(da) methods
predict.mint.pls Predict Method for (mint).(block).(s)pls(da) methods
predict.mint.plsda Predict Method for (mint).(block).(s)pls(da) methods
predict.mint.spls Predict Method for (mint).(block).(s)pls(da) methods
predict.mint.splsda Predict Method for (mint).(block).(s)pls(da) methods
predict.pls Predict Method for (mint).(block).(s)pls(da) methods
predict.plsda Predict Method for (mint).(block).(s)pls(da) methods
predict.spls Predict Method for (mint).(block).(s)pls(da) methods
predict.splsda Predict Method for (mint).(block).(s)pls(da) methods
print Print Methods for CCA, (s)PLS, PCA and Summary objects
print.pca Print Methods for CCA, (s)PLS, PCA and Summary objects
print.pls Print Methods for CCA, (s)PLS, PCA and Summary objects
print.rcc Print Methods for CCA, (s)PLS, PCA and Summary objects
print.rgcca Print Methods for CCA, (s)PLS, PCA and Summary objects
print.sgcca Print Methods for CCA, (s)PLS, PCA and Summary objects
print.spca Print Methods for CCA, (s)PLS, PCA and Summary objects
print.spls Print Methods for CCA, (s)PLS, PCA and Summary objects
print.summary Print Methods for CCA, (s)PLS, PCA and Summary objects

-- R --

rcc Regularized Canonical Correlation Analysis
rcc.default Regularized Canonical Correlation Analysis

-- S --

scatterutil.base Graphical utility functions from ade4
scatterutil.eti Graphical utility functions from ade4
scatterutil.grid Graphical utility functions from ade4
select.var Output of selected variables
selectVar Output of selected variables
selectVar.pca Output of selected variables
selectVar.pls Output of selected variables
selectVar.rgcca Output of selected variables
selectVar.sgcca Output of selected variables
selectVar.spls Output of selected variables
sipca Independent Principal Component Analysis
spca Sparse Principal Components Analysis
spls Sparse Partial Least Squares (sPLS)
splsda Sparse Partial Least Squares Discriminant Analysis (sPLS-DA)
srbct Small version of the small round blue cell tumors of childhood data
stemcells Human Stem Cells Data
study_split divides a data matrix in a list of matrices defined by a factor
summary Summary Methods for CCA and PLS objects
summary.pls Summary Methods for CCA and PLS objects
summary.rcc Summary Methods for CCA and PLS objects
summary.spls Summary Methods for CCA and PLS objects

-- T --

tune Overall tuning function that can be used to tune several methods
tune.mint.splsda Estimate the parameters of mint.splsda method
tune.multilevel Tuning functions for multilevel analyses
tune.pca Tune the number of principal components in PCA
tune.rcc Estimate the parameters of regularization for Regularized CCA
tune.rcc.default Estimate the parameters of regularization for Regularized CCA
tune.splsda Tuning functions for sPLS-DA method
tune.splslevel Tuning functions for multilevel analyses

-- U --

unmap Dummy matrix for an outcome factor

-- V --

vac18 Vaccine study Data
vac18.simulated Simulated data based on the vac18 study for multilevel analysis
vip Variable Importance in the Projection (VIP)

-- W --

withinVariation Within matrix decomposition for repeated measurements (cross-over design)
wrapper.rgcca mixOmics wrapper for Regularised Generalised Canonical Correlation Analysis (rgcca)
wrapper.sgcca mixOmics wrapper for Sparse Generalised Canonical Correlation Analysis (sgcca)
wrapper.sgccda Horizontal sparse Partial Least Squares - Discriminant Analysis (sPLS-DA) integration

-- Y --

yeast Yeast metabolomic study