Question: SampleNetwork in WGCNA
1
gravatar for 2323982403
14 months ago by
232398240320
232398240320 wrote:

The paper "Oldham, M.C., P. Langfelder and S. Horvath, Network methods for describing sample relationships in genomic datasets: application to Huntington's disease. BMC Syst Biol, 2012. 6: p. 63." Provided a method called SampleNetwork to identify sample outliers, but the URL doesn't work anymore, thus I can't find the code to do my analysis. Can anyone give me some help?

The not working URL: http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/SampleNetwork.

 

 

wgcna wgcna package • 410 views
ADD COMMENTlink modified 14 months ago • written 14 months ago by 232398240320
Answer: SampleNetwork in WGCNA
0
gravatar for Peter Langfelder
14 months ago by
United States
Peter Langfelder2.2k wrote:

Apologies for that, UCLA just changed the server and folders for our web pages... here's the new address:

https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/SampleNetwork/

Hope you find it useful!

Peter

ADD COMMENTlink written 14 months ago by Peter Langfelder2.2k

Another question concerned SampleNetwork. Should I apply SampleNetwork to unnormalized data or normalized data. As mentioned in the tutorial:

"To derive maximum utility from the function, we prefer to apply SampleNetwork to gene expression data that have been minimally processed in a consistent fashion, as described in Materials and Methods from the journal article."

It seemed that we'd better apply SampleNetwork followed by normalization.

But in the paper "Oldham, M.C., P. Langfelder and S. Horvath, Network methods for describing sample relationships in genomic datasets: application to Huntington's disease. BMC Syst Biol, 2012. 6: p. 63.", in the Microarray data pre-processing part, the data pre-processing steps:

"Expression values were generated in R using the “expresso” function of the “affy” package (http://www.bioconductor.org/)  with “mas” settings and no normalization, followed by scaling of arrays to the same average intensity (200)."

It seems that the author first did a scaling steps and then using SampleNetwork to identify outliers.

Further, in the paper "Gandal, M.J., et al., Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap. 2018. 359(6376): p. 693 - 697.", they also first used RMA followed by SampleNetwork. 

 

I'm wondering whether sample filtering should come before or after normalization, and why?

ADD REPLYlink written 14 months ago by 232398240320

I personally run low-level preprocessing and normalization (RMA or MASS5 for Affy chips; for RNA-seq, I would normalize the data and perhaps do a log- or variance stabilizing transformation) first, then (the equivalent of) SampleNetworks. SampleNetworks does sample filtering for you; I don't think it does probe/feature filtering, so you may want to do that  yourself. Both before and after SampleNetworks are valid, although they may give you slightly different results.

Peter

ADD REPLYlink written 14 months ago by Peter Langfelder2.2k
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