Unbiased clustering from bulk tissue RNA-seq?
3
0
Entering edit mode
20 months ago
gspirito ▴ 10

Hello everyone, I have a question:

I have bulk tissue whole RNA-seq data from patients and controls. I would like to know whether I could find different sub-groups of patients based solely on the transcriptional landscape, so no pre-defined sample groups. I performed a simple k-mean clustering analysis with R's function kmeans() (both on raw counts and on TPM), by imposing an arbitrary number of clusters. The results could make sense, but I would like to compare these results with some coming from a method more specific to RNA-seq data.

Could anyone point me to some tool?

Thanks in advance,

Giovanni

RNA-Seq clustering • 664 views
ADD COMMENT
1
Entering edit mode
20 months ago

The results could make sense, but I would like to compare these results with some coming from a method more specific to RNA-seq data.

k-means is fine to use for the TPM expression levels. Do not worry.

Please take a look at the ComplexHeatmap examples, where a lot of this can be made easier for you:

Kevin

ADD COMMENT
1
Entering edit mode
20 months ago

People use PCA for this as well, to eyeball how the samples group. Check out a deseq tutorial to see how to do that right.

ADD COMMENT
1
Entering edit mode
20 months ago
ATpoint 55k

Very recently published is SDCM, an unsupervised clustering technique for expression data that you can check. The talk I heard was impressive since they managed to find a very recently published subgroup of DLBCL with it but without specifically tuning parameters for it. Afaik it contains a link to the GitHub repository. https://www.nature.com/articles/s41467-019-12713-5

ADD COMMENT

Login before adding your answer.

Traffic: 2250 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6