WGCNA cannot be done to compare two conditions?
2
0
Entering edit mode
2.0 years ago
galiciaa • 0

Hello,

I have been told I cannot use WGCNA with only two conditions (control and treatment). I am not sure why that would be the case and I would like to confirm if this is true? I have 3 samples for each condition so a total of 6 samples and I am not correlating to a quantifiable trait, I am only correlating the modules to the conditions.

Thank you

WGCNA RNA-Seq rna-seq • 1.3k views
ADD COMMENT
1
Entering edit mode
2.0 years ago
Ar ★ 1.1k

I believe it is not the condition but the number of replicates that are required for running WGCNA. Typically, you are required to have more than 15 samples. Ideally, I would recommend more than 30 replicates for each condition.

Here is the list of frequently asked questions: https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/faq.html

Another advice would be plotting PCA/MDS plots to check if there are no Batch Effects or technical effects such as sex, non-biologicals effects.

Good luck!

ADD COMMENT
1
Entering edit mode
5 weeks ago

I posted this as an answer outside of Biostars:



There is no correct or incorrect answer to this. To me, it makes more sense to perform WGCNA separately, so, one network for disease and one network for control:

Analysis 1:

  1. generate network in Control
  2. identify modules and hub genes
  3. perform gene enrichment on the genes in each module

Analysis 2:

  1. generate network in Disease
  2. identify modules and hub genes
  3. perform gene enrichment on the genes in each module

Analysis 3:

  1. discuss differences between hub genes between Disease network and Control network
  2. discuss differences between modules (and their gene enrichments) between Disease network and Control network


If you generate a single network for all samples (Disease + Control), then, after you identify modules, you can still try this: perform a linear regression between DiseaseStatus and the module eigenvalues:

  summary(lm(BlueModule ~ DiseaseStatus))
  summary(lm(RedModule ~ DiseaseStatus))
  summary(lm(YellowModule ~ DiseaseStatus))
  *et cetera*

Then, in this way, you would focus on the modules from which the regression produces p<0.05, as these modules may contain information about DiseaseStatus.

Kevin

ADD COMMENT

Login before adding your answer.

Traffic: 2521 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