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.

Install the latest version of this package by entering the following in R:
install.packages("mixOmics")
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 publication2017-02-27 08:41:34
MaintainerKim-Anh Le Cao <k.lecao@uq.edu.au>
LicenseGPL (>= 2)
Version6.1.2
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

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

Functions

auroc Man page
auroc.mint.plsda Man page
auroc.mint.splsda Man page
auroc.plsda Man page
auroc.sgccda Man page
auroc.splsda Man page
block.pls Man page
block.plsda Man page
block.spls Man page
block.splsda Man page
breast.TCGA Man page
breast.tumors Man page
cim Man page
cimDiablo Man page
circosPlot Man page
color.GreenRed Man page
color.jet Man page
color.mixo Man page
color.spectral Man page
diverse.16S Man page
estim.regul Man page
estim.regul.default Man page
explained_variance Man page
image.estim.regul Man page
image.tune.rcc Man page
imgCor Man page
ipca Man page
Koren.16S Man page
linnerud Man page
liver.toxicity Man page
logratio.transfo Man page
map Man page
mat.rank Man page
mint.block.pls Man page
mint.block.plsda Man page
mint.block.spls Man page
mint.block.splsda Man page
mint.pca Man page
mint.pls Man page
mint.plsda Man page
mint.spls Man page
mint.splsda Man page
mixOmics Man page
multidrug Man page
nearZeroVar Man page
network Man page
network.default Man page
network.pls Man page
network.rcc Man page
network.spls Man page
nipals Man page
nutrimouse Man page
pca Man page
pcatune Man page
perf Man page
perf.mint.splsda Man page
perf.pls Man page
perf.plsda Man page
perf.sgccda Man page
perf.spls Man page
perf.splsda Man page
plotArrow Man page
plotContrib Man page
plotDiablo Man page
plotIndiv Man page
plotIndiv.mint.spls Man page
plotIndiv.mint.splsda Man page
plotIndiv.pca Man page
plotIndiv.pls Man page
plotIndiv.rcc Man page
plotIndiv.rgcca Man page
plotIndiv.sgcca Man page
plotIndiv.sipca Man page
plotIndiv.spls Man page
plotLoadings Man page
plotLoadings.block.pls Man page
plotLoadings.block.plsda Man page
plotLoadings.block.spls Man page
plotLoadings.block.splsda Man page
plotLoadings.mint.pls Man page
plotLoadings.mint.plsda Man page
plotLoadings.mint.spls Man page
plotLoadings.mint.splsda Man page
plotLoadings.pca Man page
plotLoadings.pls Man page
plotLoadings.plsda Man page
plotLoadings.rcc Man page
plotLoadings.rgcca Man page
plotLoadings.sgcca Man page
plotLoadings.sgccda Man page
plotLoadings.spls Man page
plotLoadings.splsda Man page
plot.perf Man page
plot.perf.mint.plsda.mthd Man page
plot.perf.mint.splsda.mthd Man page
plot.perf.plsda.mthd Man page
plot.perf.pls.mthd Man page
plot.perf.sgccda.mthd Man page
plot.perf.splsda.mthd Man page
plot.perf.spls.mthd Man page
plot.rcc Man page
plot.tune Man page
plot.tune.splsda Man page
plotVar Man page
plotVar.pca Man page
plotVar.pls Man page
plotVar.plsda Man page
plotVar.rcc Man page
plotVar.rgcca Man page
plotVar.sgcca Man page
plotVar.spca Man page
plotVar.spls Man page
plotVar.splsda Man page
pls Man page
plsda Man page
predict.mint.block.pls Man page
predict.mint.block.plsda Man page
predict.mint.block.spls Man page
predict.mint.block.splsda Man page
predict.mint.pls Man page
predict.mint.plsda Man page
predict.mint.spls Man page
predict.mint.splsda Man page
predict.pls Man page
predict.plsda Man page
predict.spls Man page
predict.splsda Man page
print Man page
print.pca Man page
print.pls Man page
print.rcc Man page
print.rgcca Man page
print.sgcca Man page
print.spca Man page
print.spls Man page
print.summary Man page
rcc Man page
rcc.default Man page
select.var Man page
selectVar Man page
selectVar.pca Man page
selectVar.pls Man page
selectVar.rgcca Man page
selectVar.sgcca Man page
selectVar.spls Man page
sipca Man page
spca Man page
spls Man page
splsda Man page
srbct Man page
stemcells Man page
study_split Man page
summary Man page
summary.pls Man page
summary.rcc Man page
summary.spls Man page
tune Man page
tune.block.splsda Man page
tune.mint.splsda Man page
tune.multilevel Man page
tune.pca Man page
tune.rcc Man page
tune.rcc.default Man page
tune.splsda Man page
tune.splslevel Man page
unmap Man page
vac18 Man page
vac18.simulated Man page
vip Man page
withinVariation Man page
wrapper.rgcca Man page
wrapper.sgcca Man page
wrapper.sgccda Man page
yeast Man page

Files

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

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