Dear mixOmics users,
It is with a huge relief and pride (and maybe some slight anticipatory anxiety of that very moment) that we announce the release of mixOmics_6_0_0 on CRAN. We are introducing three novel frameworks, mixMC, mixMINT and mixDIABLO, which are described (as best as we can, given the free remaining time we have on our hands not debugging) on the website. All manuscripts are in submission / revision so feel free to ask.
A special thanks to those who made that update possible, in particular Florian Rohart and Benoit Gautier, and the whole Lê Cao lab troop for the numerous layers of testing. We tested as much as we could but of course all data are different. Do no hesitate to report bugs or comments at mixomics[at]math.univ-toulouse.fr or on our bitbuket issue list.
Members of the mixOmics team will be present at the following summer conferences in the nothern hemisphere, feel free to say hello!
Rencontres R 2016: Toulouse, France, June 22-24, presentation on mixMINT
JOBIM 2016: Lyon, France, June 28-30, presentation on mixDIABLO
ISMB / ISCB 2016: Orlando, Florida, July 8 – July 12, attendance and presentation to the SBV crowd verification challenge, using our cousin package bootPLS
JSM 2016: Chicago, Illinois, July 30 – Aug 4, presentation on mixMC
INPPO 2016: Bratislava, Slovaquia, Sept 4-8, keynote
Below is the list of changes in the package. Please note the few argument names changes for some of the plots.
Changes in 6.0.0 (major, implementation improvements and new methods)
In short,
– argument names which changed in all plots for homogeneous call are: ‘main’ changed to ‘title’, ‘add.legend’ -> ‘legend’, ‘cex.xxx’ -> ‘size.xxx’, ‘plot.ellipse’ -> ‘ellipse’
– ncomp is now a single value in all wrapper. and block. functions (multiple integration)
Please refer to our help files for the functions listed below.
New features:
1- log.ratio transformation (log.ratio = c(‘CLR’, ‘ILR’)) in PCA and PLS-like methods to deal with compositional microbiome data (see website www.mixOmics.org/mixMC for details)
2 – plotLoadings is a novel graphical way of showing the regression coefficients of the selected variables (deprecated plotContrib)
3 – mixMINT module to analyse independent data sets on the same type of variable. See www.mixOmics.org/mixMINT for details.
Added methods: mint.pls, mint.plsda, mint.spls, mint.splsda;
S3 visualisations: plotIndiv, plotLoadings, plotVar;
Performance evaluation: perf (new, uses leave one out group), tune (new, uses leave one out group)
4 – mixDIABLO module to integrate different omics data sets performed on the same samples. See www.mixOmics.org/mixDIABLO for details.
Added methods: block.pls, block.plsda, block.spls, block.splsda;
S3 visualisations: circosPlot (new), cimDiablo (new), plotDiablo (new), plotIndiv, plotLoadings, plotVar;
Performance evaluation: perf, tune, predict (new with majority vote for DIABLO, $vote)
5 – new data sets: stemcell (for MINT), TCGA.breast.cancer (for DIABLO)
Enhancements:
1 – plotIndiv: displays explained variance for sPLS objects
2 – multilevel option is now included in PLS and PCA objects (argument multilevel = design or sample information)
3 – WARNING: in all plots, homogeneous arguments call: ‘main’ changed to ‘title’, ‘add.legend’ -> ‘legend’, ‘cex.xxx’ -> ‘size.xxx’, ‘plot.ellipse’ -> ‘ellipse’
4 – print.method functions updated to show the range of graphics / other functions to use with the object
5 – predict function now outputs class names in $class
6 – data set vac18 reduced number of genes is now 100 genes
7 – plotContrib has been depraceted for plotLoadings
8 – ncomp input is now a single value in wrapper.rgcca, wrapper.sgcca, block.pls, block.spls, block.plsda, block.splsda
Bug fixes:
1 – explained variance for NIPALS/PCA fixed
2 – plot3d mistmatch legend color, double titles for plotIndiv ggplot2 and lattice, order of group for ggpot2 and lattice
3 – retired: data set prostate
