Dear mixOmics users,
We have submitted an updated version to the CRAN. The changes are listed below. Few points in particular to keep in mind:
- select.var() was renamed selectVar() (clash with our dependency to the package MASS)
- we borrowed the function tau.estim() to the RGCCA package in order to estimate the regularisation parameters from the rCCA – a way to bypass tune.rcc() with large matrices
- the multilevel module has been updated, with some changes in the call of the function and a new function called withinVariation() (see details on the website http://mixomics.org/methods/multilevel/)
We thank you all for your interest in the package. There are important upcoming developments so please keep in touch via the website.
Changes in 5.0-4
1- new set of palettes have been added: color.jet, color.spectral, color.GreenRed and color.mixo
2- the multilevel module has been updated. A new function called withinVariation() calculates the within matrix. Our new website www.mixOmics.org will be updated shortly
3- the function tau.estim was borrowed from the RGCCA package and included in mixOmics in order to estimate the regularisation parameters from rcc more efficiently than tune.rcc(). We noted differences in those parameters estimates between tune.rcc() and tau.estim() as the methods use either cross-validation or the formula from Shaefer and Strimmer (2005). When using tau.estim() we also advise to center and scale the input data in rcc(). See help tau.estim().
4- because of a S3 method clash with the MASS package with the current R version we had to rename select.var to selectVar
1- select.var.sgcca has been fixed (the outputs were messy)
2- minor bug in plotVar.sgcca and plotVar.rgcca fixed
3- the algorithm in perf.pls and perf.spls has been almost entirely changed. We are now using a different algorithm to estimate the Q2, as presented in the help Rd file (unfortunately the reference is in French so contact us for more details if needed). plot.perf() has been updated
1- network default color set to color.GreenRed
2- output feature.final in perf S3 function has been removed. Better to use select.var() to obtain the list of selected variables
3- the multilevel module has been updated. The argument names were changed to ‘design’ instead of ‘cond’. The pheatmap.multilevel() function has been improved.
4- the nearZeroVar function that was borrowed from the caret package has been enhanced to improve computational time as this is costly in the pls/spls functions