Question: Test the effect of numeric covariates in DEseq2
0
gravatar for Cecelia
10 months ago by
Cecelia20
Cecelia20 wrote:

It is a follow-up question linked to this post: C: Could the batch effect be a set of numeric values in DEseq2?

The numeric covariate here is the load and it is likely to have a linear effect:

X,Time,Treatment,load
sampe1,Treat1,1
sample2,Treat1,7
sample3,Treat1,23
sampe4,Treat2,4
sample5,Treat2,59
sample6,Treat2,10

I built a LRT to test to find genes related to load that is affecting gene expression:

full=~load + Treatment
reduced=~Treatment

DEload <- results(model, name="load", test="Wald", alpha=0.05)
summary(DEload)

I got a list of DEGs related to load looks like this:

       baseMean log2FoldChange      lfcSE        stat    pvalue         padj
      <numeric>      <numeric>  <numeric>   <numeric>    <numeric>    <numeric>
 gene1   1.301526     0.12255733 0.05282894   2.3198898 2.034684e-02 0.0746050758
 gene2   5.850844     0.11564624 0.02771495   4.1727025 3.010078e-05 0.0004198718
....

I understand that in some comparisons when the model is testing differential expression between two factor conditions the log2foldchange showes the foldchange of the gene expression in one treatment compared to another. But how do I interprete the log2foldchange in here since I am testing a numeric covariate?

Any help can be useful!

rna-seq design deseq2 • 374 views
ADD COMMENTlink written 10 months ago by Cecelia20
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 1223 users visited in the last hour