Question: Data Normalization For Co-Expression Network Construction By Wgcna
gravatar for l0o0
6.7 years ago by
l0o0210 wrote:

I get fpkm value from different traits of different tissues by tophat and cufflinks workflow. Then i rearrange the values, traits as row names and gene id as col names. I want to use this dataset to construct co-expression network by WGCNA.

I know the first step is to do data normalization. There are many normalization methods, which one do i apply to this dataset for WGCNA?

normalization • 4.2k views
ADD COMMENTlink modified 4.6 years ago by paul.e.gradie100 • written 6.7 years ago by l0o0210
gravatar for Ashutosh Pandey
6.7 years ago by
Ashutosh Pandey12k wrote:

FPKM data is already normalised. Just follow a tutorial ( that is most relevant to your problem.

ADD COMMENTlink written 6.7 years ago by Ashutosh Pandey12k

Thank you for your quick reply :)

ADD REPLYlink written 6.7 years ago by l0o0210
gravatar for paul.e.gradie
4.6 years ago by
Australia/Melbourne/University of Melbourne
paul.e.gradie100 wrote:

To bump an old question:

Data normalization is handled internally within Cufflinks on a PER SAMPLE basis. For each transcriptome you assemble or quantify, calculation of the FPKM values include a normalization step using the DEseq geometric mean normalization method.

If you want to compare across multiple samples which were quantified independently, then you need to normalize these to one another by using a tool such as CuffNorm. However, if you run CuffDiff - or any other tool that automatically normalizes any input data sets - then normalization occurs using the default geometric normalization method between the samples included in the analysis.

ADD COMMENTlink written 4.6 years ago by paul.e.gradie100
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