mixOmics: Omics Data Integration Project

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.

AuthorKim-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 publication2016-10-19 13:07:29
MaintainerKim-Anh Le Cao <k.lecao@uq.edu.au>
LicenseGPL (>= 2)
Version6.1.1
http://www.mixOmics.org

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

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