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Category Archives: News
mixOmics 5.0-2 update
The major changes of this new update is the perf() function that supersedes valid() and offers a variable stability measure across the different folds. The pls() and spls() functions have been modified and are now following the same framework coding. … Continue reading
ECCB’14 Tutorial on mixOmics
ECCB Tutorial T04. Multivariate methodologies for the exploration of large biological data sets. Application in R using the mixOmics package Date: Sunday Sept 7, 2014 Venue: FORUM building, Faculté de Médecine, 4, rue Kirschleger, Strasbourg Time: 9am – 5.30pm (registration starts … Continue reading
Version 4.1-3 is on CRAN now
Changes in 4.1 ================ New features: ————- – New S3 method valid for objects of class psl, spls, plsda and splsda – New select.var function to directly extract the selected variables from spls, spca, sipca – New data set vac18 … 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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Tagged multi block, time course
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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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