ftwkoopmans
commented
1 year ago Perhaps you should account for the technical replicates in the statistical model instead of averaging values in the dataset (prior to statistical comparison of your experimental conditions). You can add random variables to the DEqMS and MSqRob linear regression models using the 'random_variables' parameter in the setup_contrasts() function. Example; dataset = setup_contrasts(dataset, contrast_list = list(c("control","disease")), random_variables = "patient") (assuming that 'patient' is a column in your sample metadata & this "groups" your technical replicates / repeated measurements of the same individual). This would be the easiest solution, but I'm not 100% sure if that applies to your dataset, it kind of depends on your experimental design; please consult your lab's statistician.
If you want to go down the route of averaging the data between replicates; this is not a built-in MS-DAP feature. But here's an example of how you could do this;
1) usual MS-DAP workflow of preparing the input data; import dataset, fasta files and sample metadata
2) apply the filter_dataset() function to perform filtering & normalization
3) write some code that summarizes/collapses the dataset$peptides table (unfortunately, I don't have time to help you write this code atm)
4) apply the dea() function to perform statistics
DiQin2023
Hi, Thanks for the nice package! I have 2-3 technical replicates for each sample in my dataset, how can I make sure they are averaged before group comparison? Thanks!