Clustering Challenges in Gene Expression Analysis Using WGCNA
0
0
Entering edit mode
3 months ago
NDA ▴ 20

Hi, I am currently analyzing a dataset that includes gene expression data from approximately 400 patient and control samples. My objective is to run WGCNA on this dataset. To enhance the analysis, I aim to identify the most variable genes using the CV (coefficient of variation) parameter. However, I have encountered a challenge: the variability among the genes is substantial, with a minimum CV value of 0.1116, a maximum of 999.2749, and a mean of 0.6288. Consequently, the clustering results of the samples have not yielded satisfactory outcomes. I would appreciate any guidance or recommendations on how to address this issue. Thank you.

r • 349 views
ADD COMMENT
0
Entering edit mode

Consequently, the clustering results of the samples have not yielded satisfactory outcomes.

Could you elaborate?

ADD REPLY

Login before adding your answer.

Traffic: 1906 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