im trying to find the optimum number of clusters to fit to a gene expression dataset.
For this, Im using the packages
factoextra and the function
fviz_nbclust on my scaled dataframe (simple dataframe with genes in rows and samples in columns).
It scales (z-scoring) by column so im transposing first and then scaling. Then i retranspose and calculate the optimal number of clusters.
The problem is that i get a Warning message " did not converge in 10 iterations ".
The question is, do you know a way to modify the number of iteractions?
This is the code im using
df <- scale (t(mydata)) df <- t(df) fviz_nbclust(df, kmeans, method = "gap_stat") fit <- kmeans(df, ?) mydata2 <- data.frame(df, fit$cluster)
?: this value is dictated by the clusters prediction
Thanks in advance