Relative and absolute intensity-based protein quantification across cell
lines, tissue atlases, and tumour datasets is increasingly available in
public datasets. These atlases enable researchers to explore fundamental
biological questions, such as protein existence, expression location,
quantity, and correlation with RNA expression. Most studies provide MS1
feature-based label-free quantitative (LFQ) datasets; however, growing
numbers of isobaric tandem mass tags (TMT) datasets remain unexplored.
Here, we compare traditional intensity-based absolute quantification
(iBAQ) proteome abundance ranking to an analogous method using reporter
ion proteome abundance ranking with data from an experiment where LFQ
and TMT were measured on the same samples. This new TMT method
substitutes reporter ion intensities for MS1 feature intensities in the
iBAQ framework. Additionally, we compared LFQ-iBAQ values to TMT-iBAQ
values from two independent large-scale tissue atlas datasets (one LFQ
and one TMT) using robust bottom-up proteomic identification,
normalisation, and quantitation workflows.