mixOmics: Omics Data Integration Project

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Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducing the dimension of the data by using instrumental variables (components), which are defined as combinations of all variables. Those components are then used to produce useful graphical outputs that enable better understanding of the relationships and correlation structures between the different data sets that are integrated. mixOmics offers a wide range of multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. The package proposes several sparse multivariate models we have developed to identify the key variables that are highly correlated, and/or explain the biological outcome of interest. The data that can be analysed with mixOmics may come from high throughput sequencing technologies, such as omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data. A non exhaustive list of methods include generalised Canonical Correlation Analysis, sparse Partial Least Squares and sparse Discriminant Analysis. Recently we implemented integrative methods to combine multiple data sets: horizontal integration with regularised Generalised Canonical Correlation Analysis and vertical integration with multi-group Partial Least Squares.

Author
Kim-Anh Le Cao, Florian Rohart, Ignacio Gonzalez, Sebastien Dejean with key contributors Benoit Gautier, Francois Bartolo and contributions from Pierre Monget, Jeff Coquery, FangZou Yao, Benoit Liquet.
Date of publication
2016-10-19 13:07:29
Maintainer
Kim-Anh Le Cao <k.lecao@uq.edu.au>
License
GPL (>= 2)
Version
6.1.1
URLs

View on CRAN

Man pages

auroc
Area Under the Curve (AUC) and Receiver Operating...
block.pls
Horizontal Partial Least Squares (PLS) integration
block.plsda
Horizontal Partial Least Squares - Discriminant Analysis...
block.spls
Horizontal sparse Partial Least Squares (sPLS) integration
block.splsda
Horizontal sparse Partial Least Squares - Discriminant...
breast.TCGA
Breast Cancer multi omics data from TCGA
breast.tumors
Human Breast Tumors Data
cim
Clustered Image Maps (CIMs) ("heat maps")
cimDiablo
Clustered Image Maps (CIMs) ("heat maps") for DIABLO
circosPlot
circosPlot for DIABLO
colors
Color Palette for mixOmics
diverse.16S
16S microbiome data: most diverse bodysites from HMP
estim.regul
Estimate the parameters of regularization for Regularized CCA
explained_variance
Calculation of explained variance
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
Koren.16S
16S microbiome atherosclerosis study
linnerud
Linnerud Dataset
liver.toxicity
Liver Toxicity Data
logratio.transfo
Log-ratio transformation
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...
mint.block.splsda
Horizontal and Vertical Discriminant Analysis integration...
mint.pca
Vertical Principal Component integration
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...
mixOmics
PLS-derived methods: one function to rule them all
multidrug
Multidrug Resistence Data
nearZeroVar
Identification of zero- or near-zero variance predictors
network
Relevance Network for (r)CCA and (s)PLS regression
nipals
Non-linear Iterative Partial Least Squares (NIPALS) algorithm
nutrimouse
Nutrimouse Dataset
pca
Principal Components Analysis
pcatune
Tune the number of principal components in PCA
perf
Compute evaluation criteria for PLS, sPLS, PLS-DA, sPLS-DA,...
plotArrow
Arrow sample plot
plotContrib
Contribution plot of variables
plotDiablo
Graphical output for the DIABLO framework
plotIndiv
Plot of Individuals (Experimental Units)
plotLoadings
Plot of Loading vectors
plot.perf
Plot for model performance
plot.rcc
Canonical Correlations Plot
plot.tune
Plot for model performance
plotVar
Plot of Variables
pls
Partial Least Squares (PLS) Regression
plsda
Partial Least Squares Discriminant Analysis (PLS-DA).
predict
Predict Method for (mint).(block).(s)pls(da) methods
print.methods
Print Methods for CCA, (s)PLS, PCA and Summary objects
rcc
Regularized Canonical Correlation Analysis
scatterutil
Graphical utility functions from ade4
selectVar
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...
stemcells
Human Stem Cells Data
study_split
divides a data matrix in a list of matrices defined by a...
summary
Summary Methods for CCA and PLS objects
tune
Overall tuning function that can be used to tune several...
tune.block.splsda
Tuning function for block.splsda method
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.splsda
Tuning functions for sPLS-DA method
unmap
Dummy matrix for an outcome factor
vac18
Vaccine study Data
vac18.simulated
Simulated data based on the vac18 study for multilevel...
vip
Variable Importance in the Projection (VIP)
withinVariation
Within matrix decomposition for repeated measurements...
wrapper.rgcca
mixOmics wrapper for Regularised Generalised Canonical...
wrapper.sgcca
mixOmics wrapper for Sparse Generalised Canonical Correlation...
yeast
Yeast metabolomic study

Files in this package

mixOmics
mixOmics/NAMESPACE
mixOmics/NEWS
mixOmics/data
mixOmics/data/liver.toxicity.rda
mixOmics/data/stemcells.rda
mixOmics/data/nutrimouse.rda
mixOmics/data/vac18.rda
mixOmics/data/yeast.rda
mixOmics/data/Koren.16S.rda
mixOmics/data/srbct.rda
mixOmics/data/linnerud.rda
mixOmics/data/datalist
mixOmics/data/breast.tumors.rda
mixOmics/data/diverse.16S.rda
mixOmics/data/vac18.simulated.rda
mixOmics/data/multidrug.rda
mixOmics/data/breast.TCGA.rda
mixOmics/R
mixOmics/R/plotLoadings.splsda.R
mixOmics/R/plot.tune.R
mixOmics/R/mint.pls.R
mixOmics/R/internal_predict.DA.R
mixOmics/R/cim.R
mixOmics/R/withinVariation.R
mixOmics/R/pca.R
mixOmics/R/vip.R
mixOmics/R/tune.mint.splsda.R
mixOmics/R/splsda.R
mixOmics/R/block.plsda.R
mixOmics/R/rcc.R
mixOmics/R/block.pls.R
mixOmics/R/LOGOCV.R
mixOmics/R/color.GreenRed.R
mixOmics/R/pls.R
mixOmics/R/plotDiablo.R
mixOmics/R/network.R
mixOmics/R/perf.mint.splsda.R
mixOmics/R/perf.diablo.R
mixOmics/R/check_entry.R
mixOmics/R/plotIndiv.pca.R
mixOmics/R/wrapper.rgcca.R
mixOmics/R/plotLoadings.spls.R
mixOmics/R/mint.spls.R
mixOmics/R/mint.splsda.R
mixOmics/R/spls.R
mixOmics/R/internal_mint.block_helpers.R
mixOmics/R/AUC_ROC.R
mixOmics/R/mint.pca.R
mixOmics/R/tune.pca.R
mixOmics/R/plsda.R
mixOmics/R/plotIndiv.pls.R
mixOmics/R/tune.rcc.R
mixOmics/R/nipals.R
mixOmics/R/selectVar.R
mixOmics/R/block.spls.R
mixOmics/R/internal_wrapper.mint.R
mixOmics/R/roc_utils.R
mixOmics/R/print.methods.R
mixOmics/R/tune.multilevel.R
mixOmics/R/plotLoadings.mint.splsda.R
mixOmics/R/mat.rank.R
mixOmics/R/explained_variance.R
mixOmics/R/wrapper.ilr.R
mixOmics/R/block.splsda.R
mixOmics/R/plotIndiv.mint.R
mixOmics/R/imgCor.R
mixOmics/R/nearZeroVar.R
mixOmics/R/internal_mint.block.R
mixOmics/R/unmap.R
mixOmics/R/circosPlot.R
mixOmics/R/image.tune.rcc.R
mixOmics/R/mixOmics.R
mixOmics/R/mint.block.plsda.R
mixOmics/R/bin.color.R
mixOmics/R/perf.R
mixOmics/R/plotContrib.R
mixOmics/R/MCVfold.R
mixOmics/R/tune.splslevel.R
mixOmics/R/plotIndiv.sgcca.R
mixOmics/R/plotLoadings.pca.R
mixOmics/R/sipca.R
mixOmics/R/cimDiablo.R
mixOmics/R/mint.block.spls.R
mixOmics/R/color.mixo.R
mixOmics/R/plot.pca.R
mixOmics/R/predict.mint.block.pls.R
mixOmics/R/mint.block.pls.R
mixOmics/R/scatterutil.R
mixOmics/R/internal_graphic.perf.R
mixOmics/R/plotIndiv.R
mixOmics/R/mint.block.splsda.R
mixOmics/R/pcasvd.R
mixOmics/R/summary.R
mixOmics/R/plot.rcc.R
mixOmics/R/plotArrow.R
mixOmics/R/plotLoadings.R
mixOmics/R/wrapper.sgcca.R
mixOmics/R/internal_wrapper.mint.block.R
mixOmics/R/ipca.R
mixOmics/R/color.spectral.R
mixOmics/R/imageMap.R
mixOmics/R/tune.diablo.R
mixOmics/R/plotVar.R
mixOmics/R/color.jet.R
mixOmics/R/plot.perf.R
mixOmics/R/tune.R
mixOmics/R/plotLoadings.mint.spls.R
mixOmics/R/zzz.R
mixOmics/R/mint.plsda.R
mixOmics/R/internal_graphicModule.R
mixOmics/R/ica.def.par.R
mixOmics/R/spca.R
mixOmics/R/tune.splsda.R
mixOmics/MD5
mixOmics/README
mixOmics/DESCRIPTION
mixOmics/man
mixOmics/man/plotIndiv.Rd
mixOmics/man/mint.spls.Rd
mixOmics/man/spca.Rd
mixOmics/man/scatterutil.Rd
mixOmics/man/srbct.Rd
mixOmics/man/mint.block.splsda.Rd
mixOmics/man/plot.perf.Rd
mixOmics/man/tune.Rd
mixOmics/man/wrapper.rgcca.Rd
mixOmics/man/vip.Rd
mixOmics/man/print.methods.Rd
mixOmics/man/cimDiablo.Rd
mixOmics/man/block.pls.Rd
mixOmics/man/sipca.Rd
mixOmics/man/plsda.Rd
mixOmics/man/plotLoadings.Rd
mixOmics/man/tune.rcc.Rd
mixOmics/man/tune.multilevel.Rd
mixOmics/man/map.Rd
mixOmics/man/stemcells.Rd
mixOmics/man/mint.block.pls.Rd
mixOmics/man/estim.regul.Rd
mixOmics/man/mint.block.spls.Rd
mixOmics/man/pls.Rd
mixOmics/man/auroc.Rd
mixOmics/man/mint.pls.Rd
mixOmics/man/image.tune.rcc.Rd
mixOmics/man/circosPlot.Rd
mixOmics/man/mint.splsda.Rd
mixOmics/man/logratio.transfo.Rd
mixOmics/man/diverse.16S.Rd
mixOmics/man/breast.tumors.Rd
mixOmics/man/block.spls.Rd
mixOmics/man/tune.block.splsda.Rd
mixOmics/man/withinVariation.Rd
mixOmics/man/plotContrib.Rd
mixOmics/man/tune.pca.Rd
mixOmics/man/explained_variance.Rd
mixOmics/man/breast.TCGA.Rd
mixOmics/man/predict.Rd
mixOmics/man/multidrug.Rd
mixOmics/man/spls.Rd
mixOmics/man/plot.tune.Rd
mixOmics/man/image.estim.regul.Rd
mixOmics/man/imgCor.Rd
mixOmics/man/perf.Rd
mixOmics/man/network.Rd
mixOmics/man/unmap.Rd
mixOmics/man/rcc.Rd
mixOmics/man/plotDiablo.Rd
mixOmics/man/tune.mint.splsda.Rd
mixOmics/man/nipals.Rd
mixOmics/man/selectVar.Rd
mixOmics/man/block.plsda.Rd
mixOmics/man/plotArrow.Rd
mixOmics/man/pca.Rd
mixOmics/man/vac18.Rd
mixOmics/man/yeast.Rd
mixOmics/man/plotVar.Rd
mixOmics/man/ipca.Rd
mixOmics/man/nutrimouse.Rd
mixOmics/man/tune.splsda.Rd
mixOmics/man/mixOmics.Rd
mixOmics/man/linnerud.Rd
mixOmics/man/mat.rank.Rd
mixOmics/man/wrapper.sgcca.Rd
mixOmics/man/study_split.Rd
mixOmics/man/plot.rcc.Rd
mixOmics/man/pcatune.Rd
mixOmics/man/mint.plsda.Rd
mixOmics/man/Koren.16S.Rd
mixOmics/man/colors.Rd
mixOmics/man/mint.block.plsda.Rd
mixOmics/man/vac18.simulated.Rd
mixOmics/man/summary.Rd
mixOmics/man/mint.pca.Rd
mixOmics/man/cim.Rd
mixOmics/man/liver.toxicity.Rd
mixOmics/man/splsda.Rd
mixOmics/man/nearZeroVar.Rd
mixOmics/man/block.splsda.Rd