Entering edit mode
7.3 years ago
forever
▴
80
Hi everyone, I have 100 samples x100 features dataset. The 100 samples are belong to 4 different class. PCA can not show any difference between these 4 classes. Also, k-means only shows 2 clusters. What do you suggest me to do further? I appreciate your help.
Perhaps you could explain in more depth? As it stands, your question is unrelated to bioinformatics.
I used k-means and NMF and they show only 2 clusters. I want to analysis my dataset as it produced from different sources. I expect to see 4 different patterns, maybe you can suggest me something else other than PCA, k-means and NMF?
tSNE? But really, the question of what you're actually trying to do still stands. If you know already that the samples come from 4 different sources then you don't need to find that out with PCA/k-means/etc. At most, you're just finding out that the sources produces largely indistinguishable samples as assayed by your 100 features.
Just checking: Did you set k to 4?
Hi forever,
first please avoid 'blinded' questions, as such do not serve a purpose for neither you nor the community. Your problem description is insufficient to provide a good answer. Please state the nature of your data,
pre-processing/transformation
If these are not of biological origin, your question does not fit here.