Entering edit mode
Hi,
I am new to statitics and RNAseq analysis, I am using DESeq2 for the anaylzing the RNAseq data. I would like to know what lfcSE(logfoldchangeStandard Error) and stat (wald ) columns tries to convey. For an example. how can I interpret the following:
log2FC:-1.4; lfcSE: 0.144; stat:-10.13
Kindly guide me.
Dear Michael,
Thanks for your quick response. By going throught he vignette, I undersatnd that smaller the lfcSe more significant the effect of fold change? Am I right? What does that a value in wald statistic columns conveys.
Kindly guide me
Thank you so much. Now I understood clearly. Also is the lesser the lfcSE, more singificant the log2fold change?
If basemean is the mean of normalized rowcounts, how log2foldchange is calculated.?
hi Deena,
You should look over our paper, if you want details about the method:
http://genomebiology.com/2014/15/12/550
Hi Michael,
Sorry to bring up an old post. I was reading your paper and noticed it says that the Wald statistic is a Z-score. Is this also true for the LRT statistic? If not, is it possible to convert it to a Z-score using scale() or are there considerations I need to consider? I am asking because I plan to meta-analyze different datasets.
Thanks a lot!
Only the Wald statistics are asymptotically Normal, not the LRT statistic. No, you should not need to adjust the Wald statistics.
Thanks so much for the advice. Can I substitute 0 for NA for Wald test statistic? Appreciate the help!
You can do what you want with these, thats up to you. They are 0 vs 0 genes.
Is ranking based on the
Wald stat
variable reasonable for gene ranking in the GSEA? Or ranking based on thelfcShrink
(shrinkage Log fold change) better thanstat
? Thank you.I think both are reasonable. I haven't evaluated these against each other in a benchmark for GSEA.
The main difference between these is that lfcShrink estimates the effect size, where as n grows, the estimate converges to the parameter of interest (assuming we do not have bias).
As sample size grows, the Wald statistic does not converge to any parameter.