Hi there!
This is my first time posting but I've always been a frequent lurker on previous posts that have been super helpful, so apologies if I'm not following any appropriate etiquette. I am working on an RNA sequencing project and looking have different outputs, which provides either a likehood ratio test statistic and p-value or wald test statistic and p-value. I prefer the LRT over Wald due to some subsets having smaller sample size. If it matters, this is an output from DESeq2.
I am currently looking into meta-analyzing different datasets and was wondering whether I would need to Z-score normalize my LRT statistic to do this? I recall learning it is similar to a chi-square distribution, so would it be okay to square it? Or should I use scale() in R? Or maybe there is a better way of meta-analyzing RNAseq datasets that produce LRT / Wald statistics, but I'm not too familiar.
Thank you all for your help! I truly appreciate it. Let me know if there is any clarification you may need.
This is my first time posting but I've always been a frequent lurker on previous posts that have been super helpful, so apologies if I'm not following any appropriate etiquette. I am working on an RNA sequencing project and looking have different outputs, which provides either a likehood ratio test statistic and p-value or wald test statistic and p-value. I prefer the LRT over Wald due to some subsets having smaller sample size. If it matters, this is an output from DESeq2.
I am currently looking into meta-analyzing different datasets and was wondering whether I would need to Z-score normalize my LRT statistic to do this? I recall learning it is similar to a chi-square distribution, so would it be okay to square it? Or should I use scale() in R? Or maybe there is a better way of meta-analyzing RNAseq datasets that produce LRT / Wald statistics, but I'm not too familiar.
Thank you all for your help! I truly appreciate it. Let me know if there is any clarification you may need.