# How to start/do WGCNA of microarray datasets?
**URL:** https://community.brain-map.org/t/how-to-start-do-wgcna-of-microarray-datasets/5073
**Category:** How To
**Tags:** transcriptomics, rna-seq, how-to
**Created:** [September 18, 2026, 6:36am UTC](https://community.brain-map.org/t/how-to-start-do-wgcna-of-microarray-datasets/5073 "2026-09-18T06:36:43Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@Navy](https://community.brain-map.org/u/Navy)
#### Post date: [September 18, 2026, 6:36am UTC](https://community.brain-map.org/t/how-to-start-do-wgcna-of-microarray-datasets/5073/1 "2026-09-18T06:36:43Z")
i have four datasets whcih i worked on, i used limma as they were mcroarray platforms. then i did GSE for each dataset, also did several other downstream in silico test etc. but my guide said she want me to perform wgcna, i dont know any thing about it and tbh i dont know if i will do wgcna like gsea, like for every dataste or for largest dataset. i dont have nay idea, can somebody tell me how to do it??
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### Author:  [@Alexy](https://community.brain-map.org/u/Alexy)
#### Post date: [September 18, 2026, 9:01am UTC](https://community.brain-map.org/t/how-to-start-do-wgcna-of-microarray-datasets/5073/2 "2026-09-18T09:01:13Z")
WGCNA is different from GSEA: it groups genes with similar expression patterns across samples into **modules** , then examines whether those modules are associated with your phenotype.
You don’t necessarily need to run it on all four datasets. A reasonable approach is to use one sufficiently large, good-quality dataset for module discovery, then test module preservation and phenotype associations in the others, assuming the tissues and conditions are comparable. Don’t choose solely by sample size—study design and data quality matter too.
Start with your **normalized expression matrix, not just significant DEGs**. The basic workflow is quality control → select a soft-thresholding power → identify modules → test module–trait associations → functional enrichment and validation. The official WGCNA tutorials walk through this in R. Your sample sizes and tissue types will determine which multi-dataset approach makes sense.