Category Archives: Publications

New publication with multiple integration

Our paper ‘Novel Multivariate Methods for Integration of Genomics and Proteomics Data: Applications in a Kidney Transplant Rejection Study‘ has just been accepted in OMICS: a journal of integrative Biology, from a collaboration with scientists from the PRevention Of Organ Failure … Continue reading

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Article published explaining correlation circle plots, relevance networks and CIM

Our manuscript ‘Insightful graphicalt outputs to explore relationships between two “omics” data sets has been published and explains how to interpret Correlation Circle plots, how relevance networks and CIM are generated from rCCA and sPLS. Check this very colourful manuscript[intlink … Continue reading

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Another presentation about mixOmics

Another general presentation of mixOmics dating Dec 2012, which presents some preliminary but exciting results about time course data and the generalisation of PLS to multi block data sets using the approach of our collaborator Arthur Tenenhaus and colleagues. Go[intlink … Continue reading

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General presentation about mixOmics

A new general presentation about mixOmics is available (and should be updated for major update of the package) in the [intlink id=”204″ type=”page”]Presentation Section[/intlink]. Lê Cao K.-A. Unravelling `omics’ data with the mixOmics R package, Illustration on several studies. General presentation on mixOmics … Continue reading

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(s)IPCA

Independent Principal Component Analysis (IPCA) In some case studies, we have identified some limitations when using PCA: PCA assumes that gene expression follows a multivariate normal distribution and recent studies have demonstrated that microarray gene expression measurements follow instead a … Continue reading

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New methods: multilevel analyses

A multilevel approach has been added for cross-over design experiments (up to two cross factors), in collaboration with A/Prof B. Liquet (Universite de Bordeaux, France).  This approach takes into account the complex structure of repeated measurements from different assays, where different treatments are applied … Continue reading

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Web-interface

R package and Methods: IPCA and sparse IPCA functions have been implemented (as well as their associated S3 functions). IPCA stands for Principal Component Analysis with Independent Loadings. It is a combination of the advantages of both PCA and Independent … Continue reading

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New Graphics: network & cim

New S3 method network and cim for results from PLS model New code for the valid function to PLS-DA and SPLS-DA models validation The S3 method plot.valid was modified to display graphical results from valid function for PLS-DA and SPLS-DA models cim and network functions were … Continue reading

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New Function: (s)PCA added

New function pca and spca are now available to perform Principal Component Analysis (PCA) and sparse PCA for variable selection The S3 methods plotVar, plot3dVar, plotIndiv, plot3dIndiv were modified to generate graphical results for pca and spca

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New function: plot.valid

New function plot.valid to display the results of the valid function New code for imgCor function for a nicer representation of the correlation matrices In predict function the argument ‘method’ were replaced by method = c(“max.dist”, “class.dist”, “centroids.dist”, “mahalanobis.dist”) The arguments dendrogram, ColSideColors and RowSideColors were added to the cim … Continue reading

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