We have a few manuscripts in the pipeline – some are available as preprint on bioRxiv.

  • Singh A, Gautier B, Shannon C, Vacher M, Rohart F, Tebbutt S, K-A. Lê Cao. DIABLO – multi-omics data integration for biomarker discovery.  [BioRxiv link]
  • Maxime H, Nicole F, Lê Cao K-A. Multivariate analysis of multiple datasets: a practical guide for chemical ecology. Journal of Chemical Ecology, 44(3): 215-234. [link]
  • Rohart F.,  Gautier, B, Singh, A and Lê Cao, K. A. mixOmics: an R package for ‘omics feature selection and multiple data integration.PLoS Comput Biol 13(11): e1005752. Pdf, Sweave and R scripts available here. [link]
  • Rohart F.,  Matigian N., Eslami A., Bougeard S and Lê Cao, K-A (2017).MINT: A multivariate integrative method to identify reproducible molecular signatures across independent experiments and platforms BMC Bioinformatics 18:128.

  • K-A. Lê Cao*, ME Costello*,  VA Lakis, F Bartolo, XY Chua, R Brazeilles, P Rondeau. (2016) MixMC: Multivariate insights into Microbial Communities.PLoS ONE 11(8): e0160169 [link]

  • Günther P., Shin H., Ng R.T., McMaster W. R. , McManus B. M. , Keown P. A. , Tebbutt S. J. , Lê Cao K-A. (2014), Novel multivariate methods for integration of genomics and proteomics data: Applications in a kidney transplant rejection study, OMICS: A journal of integrative biology, [link].
  • Tenenhaus A., Phillipe C., Guillemot V., Lê Cao K-A. , Grill J. , Frouin V.  (2014), ‘Variable selection for generalized canonical correlation analysis’, Biostatistics, doi: 10.1093/biostatistics. PMID: 24550197. [link]
  • González I., Lê Cao K.-A., Davis, M.D. and Déjean S. (2013) Insightful graphical outputs to explore relationships between two ‘omics’ data sets. BioData Mining 5:19. See a full version of the manuscript with enclosed figures here.
  • Liquet B&, Lê Cao K-A&, Hocini H, Thiebaut R (2012). A novel approach for biomarker selection and the integration of repeated measures experiments from two assays. BMC Bioinformatics 13:325.[link]
  • Yao F., Coquery J., Lê Cao K.-A. (2012) Independent Principal Component Analysis for biologically meaningful dimension reduction of large biological data sets, BMC Bioinformatics 13:24. [link]
  • Lê Cao K.-A., Boitard S. and Besse P. (2011) Sparse PLS Discriminant Analysis: biologically relevant feature selection and graphical displays for multiclass problems. BMC Bioinformatics, 22:253. [link]
  • Lê Cao K.-A., González I. and Déjean S. (2009) integrOmics: an R package to unravel relationships between two omics data sets. Bioinformatics, 25(21):2855-2856. [linkNOTE: the package ‘integrOmics’ has been renamed ‘mixOmics’.
  • González I., Déjean S., Martin P. and Baccini A. (2008) CCA: An R package to extend canonical correlation analysis. Journal of Statistical Sofware, 23(12). [link]
  • González I., Déjean S., Martin P.G.P., Gonçalves O., Besse P. and Baccini A. (2009) Highlighting Relationships Between Heteregeneous Biological Data Through Graphical Displays Based On Regularized Canonical Correlation Analysis. Journal of Biological Systems 17(2), pp 173-199. [link]
  • Lê Cao K.-A., Martin P.G.P, Robert-Granié C. and Besse, P. (2009) Sparse Canonical Methods for Biological Data Integration: application to a cross-platform study. BMC Bioinformatics, 10:34. [link]
  • Yergeau E., Schoondermark-Stolk S.A., Brodie E.L., Déjean S., DeSantis T.Z., Gonçalves O., Piceno Y.M., Andersen G.L. and Kowalchuk G.A. (2009) Environmental microarray analyses of Antarctic soil microbial communities. The International Society for Microbial Ecology Journal3(3), pp 340-351. [link]
  • Lê Cao K.-A., Rossouw D., Robert-Granié C. and Besse P. (2008) A Sparse PLS for Variable Selection when Integrating Omics data. Statistical Applications in Genetics and Molecular Biology 7(1), Article 35. [link]
  • Combes S., González I., Déjean S., Baccini A., Jehl N., Juin H., Cauquil L., Gabinaud B., Lebas F. and Larzul C. (2008) Relationships between sensorial and physicochemical measurements in meat of rabbit from three different breeding systems using canonical correlation analysis. Meat Science 3, pp 835-841. [link]