Author summary Identifying and quantifying proteins in single cells gives researchers the ability to tackle complex biological problems that involve single cell heterogeneity, such as the treatment of solid tumors. Mass spectrometry analysis of peptides can identify their sequence from their masses and the masses of their fragment ion, but often times these pieces of evidence are insufficient for a confident peptide identification. This problem is exacerbated when analyzing lowly abundant samples such as single cells. To identify even peptides with weak mass spectra, DART-ID incorporates their retention time—the time when they elute from the liquid chromatography used to physically separate them. We present both a novel method of aligning the retention times of peptides across experiments, as well as a rigorous framework for using the estimated retention times to enhance peptide sequence identification. Incorporating the retention time as additional evidence leads to a substantial increase in the number of samples in which proteins are confidently identified and quantified.
slavovLab@galos_gann The point of peer review is constructive feedback, not highly-technical comments intended to confuse.
I raise this publicly because I think it's poisonous for the community. It's counterproductive. It's sad. It's pathetic.
slavovLab@galos_gann Yes, ideally they will be disregarded... though practically they can result in a rejection, and dealing with appeals may or may not be successful. In any case -- even without a rejection -- such comments waste time for the editors, for the authors, and for the reviewers ...
slavovLab-- Some reviewers of mass-spec data use 3-4 low-quality spectra (marked as low-quality by search engines and not used for further analysis) to evaluate & discredit the entire dataset of millions of high-quality spectra used for further analysis. 2/3
slavovLabHere is very telling difference between 2 omics communities:
-- Reviewers of next-gen sequencing data generally don't use 3-4 low-quality sequences from a fastaq file (or their underlying data) to evaluate & discredit the entire dataset of millions of high-quality sequences. 1/3