I have some shotgun data (MS spectra) that I analyzed in Proteome discoverer implementing the Minora node (which I understand is used to do label-free quantification). However, I have read so many papers with so many different methodologies that I no longer know how to process my results.
In some of them they mention the Minora node, but they use the results of the Proteome discoverer to process them after by other secondary softwares and obtain the quantification. Many others even use rna-seq tools (like limma). I don't understand this strategy, isn't that supposed to be Minora's advantage? The direct quantification?
Now I have my results with the abundances and the relative ratios between compared samples, with their respective p-values and I thought to choose my differential proteins from these columns of abundance ratios (fold change 1 for up-regulated and 0.66 for down-regulated). But after seeing so many papers I only ended up more confused. Could someone guide me or tell me if it is correct that I work directly on the results obtained with the Proteome discoverer?
Hello Hugo Hernández ,
you are right. You can select the differentially expressed proteins directly from the results you obtained from Proteome Discoverer. However, before I would suggest normalizing the abundances between the samples using total peptide amounts in the Minora node and filtering proteins to be present with high confidence in at least two replicates of a group. Then, you can define cutoff values for differentially expressed proteins for the log2 abundance ratio and the (adjusted) p-value. I would suggest a log2 abundance ratio of +/-1 and an adjusted p-value < 0.05.
Best regards,
Simon
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