self-organizing map in R
[This article was first published on One Tip Per Day, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
This is my first SOM figure 🙂
Thanks to the som package and example code from Jun Yan. Here is my code for the figure:
require(som)
rpkm <- Tx_rpkm[, -c(1:4)]
rpkm.f <- filtering(rpkm, lt=10, ut=30000, mmr=2, mmd=10)
# rpkm.f=log(rpkm.f+0.1) # this doesn’t really change much of the result
rpkm.f.n <- normalize(rpkm.f)
foo <- som(rpkm.f.n, xdim=5, ydim=5, topol="rect", neigh="bubble")
png(“../results/clustering.SOM.RNAseq.png”,width=800, height=800)
plot(foo,yadj=0.15, main=”Expression profiles obtained by self-organizing map (SOM) clustering \nof individual mRNA transcript throughout the time-course”, xlab=”Stage: D13 – D14 – D15 – D16 – D17 – D18″)
dev.off()
I am still not very clear how to choose the proper xdim and ydim. Also, what’s the color code for the bar mean? Hope anyone know SOM could leave comment here. Or, I will read article myself 🙂
Is the normalization necessary?
To leave a comment for the author, please follow the link and comment on their blog: One Tip Per Day.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.