Hi there,

I am stuck here creating S-plots after generating a OPLS-DA plot.

I apply this code:

library(ropls)
oplsda <- opls(t(assay(vsd3)), as.factor(data$group), predI = 1, orthoI = NA)
png("figure4-OPLS-da.png", width = 500, height = 500, res = 72)
plot(oplsda, typeVc = "x-score", parPaletteVc = c("#57b993", "#c94a3d"))
dev.off()

I dont know how can generate S-plots from here, can you help me with that?

Thanks in advance.

Hello,

I am facing the same issue. I'm not confortable with the OPLS-DA modelisation but here is the solution I found, I hope it can help. It is based on the S-plot description made by Wiklund et al. (2008) (doi:10.1021/ac0713510) and a script found here. This function return a dataframe of the covariance (Cov) and correlation (Corr) loading profiles from the predictive component of an OPLS-DA model. The arguments datamatrix is the matrix used to perform the OPLS-DA and opls is the S4 object resulting of the ropls::opls() function. Up to you to create and customize the S-plot as you wich.

DataSplot <- function(datamatrix, opls) {

  s <- datamatrix
  T <- as.matrix(opls@scoreMN)

  p1 <- c()
  for (i in 1:ncol(s)) {
    scov <- cov(s[,i], T)
    p1 <- matrix(c(p1, scov), ncol=1)
  }

  pcorr1 <- c()
  for (i in 1:nrow(p1)) {
    den <- apply(T, 2, sd)*sd(s[,i])
    corr1 <- p1[i,]/den
    pcorr1 <- matrix(c(pcorr1, corr1), ncol=1)
  }

  datasplot <- data.frame(Cov = p1, Corr = pcorr1)
  rownames(datasplot) <- colnames(datamatrix)

  return(datasplot)
}

df <- DataSplot(t(assay(vsd3)), oplsda)

plot(df$Cov, df$Corr)