Question: Log-transformed RNA-Seq data and linear regression
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gravatar for Na Sed
4.2 years ago by
Na Sed280
United States
Na Sed280 wrote:

I would like to investigate about the relation of RNA-Seq data together, i.e. making gene networks.

Can I use linear regression model after log-transformation of  data, i.e. log(read_count+1)?

Actually, I have done it and the results appear meaningful, but I am doubted about the process.

Appreciate for any thought.

ADD COMMENTlink modified 4.2 years ago by Irsan7.0k • written 4.2 years ago by Na Sed280
2
gravatar for Steven Lakin
4.2 years ago by
Steven Lakin1.4k
Fort Collins, CO, USA
Steven Lakin1.4k wrote:

Liner regression models how well a set of points approximate to a line.  You can certainly use it on anything; your interpretation of what the trend means is the more meaningful part.  Just remember that if you find a linear correlation in your data, it actually is an exponential one.  Also understand the strengths and weaknesses of the model you're using (look at your residuals, understand how you can interpret goodness of fit, etc.).

 

For example:

Incremental doses of drug Y vs. log2(fold change) of transcript X

R^2 = 0.99

Might suggest that incremental doses of drug Y correlate with a base 2 exponential response (y = 2^x) in gene expression, not a linear one.

 

ADD COMMENTlink written 4.2 years ago by Steven Lakin1.4k
2

Agreed, but note that when you talk about an exponential gene expression, it's really an exponential read-count relationship. We don't know the real relationship between readcount and expression. Some people think log(reads) is proportional to expression already.

ADD REPLYlink written 4.2 years ago by karl.stamm3.5k

Yes I do think so as well (that log(reads) is proportional to expression). This is because the original RNA molecules are amplifified in an exponential fashion (PCR) before they are measured by microarray/RNAseq/Taqman/any other assay that measures PCR-amplified RNA

ADD REPLYlink written 4.2 years ago by Irsan7.0k

I think log transformed count indeed maintains the original proportion, no? However for the purpose of the linear model, would log transformed count cause non-linearity?

ADD REPLYlink written 8 months ago by CY370

Would log-transformed value violate the linearity assumption required for linear regression? Are independent variables and dependent variables still linear correlated after transformation?

ADD REPLYlink written 8 months ago by CY370
2
gravatar for Irsan
4.2 years ago by
Irsan7.0k
Amsterdam
Irsan7.0k wrote:

Use voom-transformation of RNAseq count data to use them in linear models (like in limma). How To Transform From Rna-Seq Deseq To Limma Voom() And Makecontrastsexplains how.

ADD COMMENTlink modified 4.2 years ago • written 4.2 years ago by Irsan7.0k
1
gravatar for Zhilong Jia
4.2 years ago by
Zhilong Jia1.4k
London
Zhilong Jia1.4k wrote:

The log is just kind of preprocess. if your results are biologically fine, I believe it's reasonable. Maybe you can check limma for RNA-seq as well.

ADD COMMENTlink written 4.2 years ago by Zhilong Jia1.4k
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