Predictive Genes

gistfile1.r

# Data frame for which genes to include by disease
excl <- data.frame('gene' = c(NA), 'round' = c(NA))

# Remove 30% of genes each round
while(nrow(excl) < nrow(d.qn)) {
  cat('Running with', excl.n, 'genes excluded...\n')
  
  # Run SVM
  svm.model <- svm(t(as.matrix(d.qn[-excl$gene,])), # features, minus excluded genes
                  tc, # class of each sample
                  kernel='linear',
                  cost=1)
 
  # Calculate weights
  w <- t(svm.model$coefs) %*% svm.model$SV
  
  # Pick the genes to remove
  excl <- rbind(excl,
           data.frame(
             'round' = nrow(excl),
             'gene' = which(rownames(d.qn) %in%
               rownames(d.qn)[order(abs(w[1,]))[1:(0.3*(nrow(d.qn)-nrow(excl)))]])))
}