I have two questions for you. First, does limpa assume that all experimental samples have been normalized to technical/process blanks before they are entered into the limpa workflow? If not, is this a step I should be performing before using limpa?
Second, when using Spectronaut v20 for PTM analysis, the user is provided with the option to use input normalization and PTM site stoichiometry to improve the accuracy of their PTM analysis results. "stoichiometry...reflects the proportion of a given PTM site that carries specific PTM and its unmodified levels." Input normalization is "...a process that adjusts PTM site quantities using data from pre-enrichment samples". Both definitions are quoted from the source linked below. Aside from selecting a different column in the qty.column argument of the readSpectronaut() function, are there other changes or considerations that the user should make to the limpa workflow when selecting these options in their PTM analysis?
He left some comments regarding normalization. Here is the relevant quote:
The EList object produced by dpcQuant(), containing protein log-expression values, can be normalized by normalizeBetweenArrays(), but we find that normalization is not always necessary. Upstream peptide quantification tools like DIA-NN seem to already do some normalization, which sometimes seems to us to be sufficient.
source (To Dr. Smyth: I wanted to thank you and say that I have great respect your work, user support and the way you educate users like myself. )
The short answer is that limpa reads standard feature-level intensities from Spectronaut or other quantifications tools. limpa is designed to work on intensities, not on ratios of intensities or on proportions. There is no need to do any special or artificial normalizations. An example limpa analysis with Spectronaut output is provided on the limpa documentation page https://github.com/SmythLab/limpa/ .
I don't know what you mean by "technical/process blanks". I asked my proteomics expert colleagues and they haven't heard of such a concept either. There is no mention of blanks in the Spectronaut manuals.
If you are actually refering to control samples, then limpa will make any required comparisons to the control samples as part of the design matrix, same as would be done for any expression analysis. limpa expects to get control samples and treatment samples as separate columns.
You do not need to do any ad hoc normalizations yourself, and it would be wrong to do so.
Input normalization and PTM stochiometry are new features in Spectronaut and we are not familiar with them yet. However, looking at the BIOGNOSYS web page, I am worried that these normalizations will interfere with limpa's assumptions. limpa is designed to analyse intensities, not ratios of intensities, and certainly not proportions on an 0 < x < 1 scale. As a statistician, I would much prefer to get the PTM and protein abundances separately, so that I can relate one to the other as part of the statistical analysis. I don't want Spectronaut to take ratios before passing the data to me, because then I cannot infer whether the original intensities were large or small in the first place. Similarly with flyability ratios. I would want to get intensities for modified sites and their unmodified counterparts separately, not pre-normalized into proportions in some proprietry way by Spectronaut. What if one of the intensities was NA? What would sort of ratio or proportion would Spectronaut return then? I suspect we would lose information about what was detected and what was not.
Hi Emily,
He left some comments regarding normalization. Here is the relevant quote:
source (To Dr. Smyth: I wanted to thank you and say that I have great respect your work, user support and the way you educate users like myself. )
Take care, Jay