examples/ipca-example.R

#' \dontrun{
## successful: TRUE

library(mixOmics.data)

# implement IPCA on a microarray dataset
ipca.res <- ipca(liver.toxicity$gene, ncomp = 3, mode="deflation")
ipca.res

# samples representation
plotIndiv(ipca.res, ind.names = as.character(liver.toxicity$treatment[, 4]),
          group = as.numeric(as.factor(liver.toxicity$treatment[, 4])))

# example with MultiAssayExperiment class
# --------------------------------

ipca.res <- ipca(liver.toxicity.mae, assay='gene', ncomp = 3, mode="deflation")
ipca.res



  plotIndiv(ipca.res, cex = 1,
            col = as.numeric(as.factor(liver.toxicity$treatment[, 4])),style="3d")

# variables representation with cutoff
plotVar(ipca.res, cex = 1, cutoff = 0.5)


  ## 3d
  plotVar(ipca.res, rad.in = 0.5, cex = 0.5,style="3d", cutoff = 0.8)

  #' }
ajabadi/mixOmics2 documentation built on Aug. 9, 2019, 1:08 a.m.