Combining t and P value adjustment with TREAT

[ndeimler99]

Hello, I have a DIA dataset I am working with. I am interested in using the "treat" method (limma-voom and edgeR offer functions to do so) to determine if the logFC of a protein is significantly higher than that of a biologically meaningful value such as 0.5 instead of comparing it to 0. It is my understanding DEqMS simply adjusts the t and p-statistics reported by eBayes() based on the number of precursors used to identify and quantify each protein. I was wondering if there would be a way to combine these two methodologies.

Thanks,

Nathaniel Deimler

[yafeng]

In theory, it works if the treat method returns a object similar to the function eBayes() in Limma. The pseudo step Would be： 1. Fit1 <- limma(treat) 2. Fit1$count <- The precursor number 3. Fit2 <- spectraCounteBayes(fit1) Hope it could give you a hint. Yafeng 在 2023年7月20日，下午8:49，ndeimler99 ***@***.***> 写道：  Hello, I have a DIA dataset I am working with. I am interested in using the "treat" method (limma-voom and edgeR offer functions to do so) to determine if the logFC of a protein is significantly higher than that of a biologically meaningful value such as 0.5 instead of comparing it to 0. It is my understanding DEqMS simply adjusts the t and p-statistics reported by eBayes() based on the number of precursors used to identify and quantify each protein. I was wondering if there would be a way to combine these two methodologies. Thanks, Nathaniel Deimler — Reply to this email directly, view it on GitHub<#13>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AAXG6N36T3YRJPKINSM7ZMTXRESNNANCNFSM6AAAAAA2RMDFFA>. You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>