# Omics Data Integration Project

## Documentation for package ‘mixOmics’ version 5.2.0

- DESCRIPTION file.
- Package NEWS.

## Help Pages

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

## -- B --

bin.color | Internal Functions
breast.tumors | Human Breast Tumors Data

## -- C --

cim | Clustered Image Maps (CIMs) ("heat maps")
color.GreenRed | Color Palette for mixOmics
color.jet | Color Palette for mixOmics
color.mixo | Color Palette for mixOmics
color.spectral | Color Palette for mixOmics
cov2 | Internal Functions

## -- D --

defl.select | Internal Functions
deflation | Internal Functions

## -- E --

estim.regul | Estimate the parameters of regularization for Regularized CCA
estim.regul.default | Estimate the parameters of regularization for Regularized CCA

## -- I --

ica.def | Internal Functions
ica.par | Internal Functions
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
initsvd | Internal Functions
ipca | Independent Principal Component Analysis

## -- L --

l2.norm | Internal Functions
linnerud | Linnerud Dataset
liver.toxicity | Liver Toxicity Data
loo | Internal Functions

## -- M --

map | Internal Functions
mat.rank | Matrix Rank
Mfold | Internal Functions
miscrossprod | Internal Functions
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
pcasvd | Internal Functions
pcatune | Tune the number of principal components in PCA
perf | Compute evaluation criteria for PLS, sPLS, PLS-DA and sPLS-DA
perf.pls | Compute evaluation criteria for PLS, sPLS, PLS-DA and sPLS-DA
perf.plsda | Compute evaluation criteria for PLS, sPLS, PLS-DA and sPLS-DA
perf.spls | Compute evaluation criteria for PLS, sPLS, PLS-DA and sPLS-DA
perf.splsda | Compute evaluation criteria for PLS, sPLS, PLS-DA and sPLS-DA
plot.perf | Plot for model performance
plot.rcc | Canonical Correlations Plot
plotArrow | Arrow sample plot
plotContrib | Contribution plot of variables
plotIndiv | Plot of Individuals (Experimental Units)
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.pls | Predict Method for PLS, sPLS, PLS-DA or sPLS-DA
predict.plsda | Predict Method for PLS, sPLS, PLS-DA or sPLS-DA
predict.spls | Predict Method for PLS, sPLS, PLS-DA or sPLS-DA
predict.splsda | Predict Method for PLS, sPLS, PLS-DA or sPLS-DA
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
prostate | Human Prostate Tumors Data

## -- R --

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

## -- S --

s.match | Plot of Paired Coordinates
scale2 | Internal Functions
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.plsda | Output of selected variables
selectVar.rgcca | Output of selected variables
selectVar.sgcca | Output of selected variables
selectVar.sipca | Output of selected variables
sipca | Independent Principal Component Analysis
soft.threshold | Internal Functions
soft_thresholding_L1 | Internal Functions
sparsity | Internal Functions
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
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 --

tau.estimate | Internal Functions
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.splsdalevel1 | Tuning functions for multilevel analyses
tune.splsdalevel2 | Tuning functions for multilevel analyses
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 | (Generalised Canonical Correlation Analysis
wrapper.sgcca | (Generalised Canonical Correlation Analysis
wrapper.sgccda | (Generalised Canonical Correlation Analysis

## -- Y --

yeast | Yeast metabolomic study