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. Author manuscript; available in PMC: 2024 Mar 19.
Published in final edited form as: J Proteome Res. 2023 Oct 20;22(11):3427–3438. doi: 10.1021/acs.jproteome.3c00205

Table 2.

Data Set Characteristicsa

Identifier Peptides Runs % Missing Quantification Software Experiment Type Citation
PXD016079 32999 31 45 MaxQuant, MBR DDA, LFQ 32
PXD006109 38124 20 17 MaxQuant, MBR DDA (BoxCar) 33
PXD014525 17208 36 92 MaxQuant DDA, LFQ 34
PXD034525 40346 10 13 EncyclopeDIA, Skyline DIA 35
PXD014815 24204 42 29 EncyclopeDIA, Skyline DIA 36
PXD013792 2224 12 72 MaxQuant DDA, LFQ 37
PXD014156 697 20 55 MaxQuant DDA, LFQ 38
PXD006348 10362 24 72 MaxQuant DDA, LFQ 39
PXD011961 23415 23 46 MaxQuant, MBR DDA, LFQ 40
CPTAC-S047 40000 30 54 Philosopher DDA, TMT 41
CPTAC-S051 40000 30 41 Spectrum Mill DDA, TMT 42
PXD007683 38921 11 0 Custom pipeline DDA, TMT 43
a

Description of the proteomics data sets used in this study. The two CPTAC data sets were downsampled by randomly selecting 40,000 peptides and 30 runs each. “MBR” stands for “match between runs,” “LFQ” for “label-free quantification,”, and “TMT” for “tandem mass tag.” References for quantification software: MaxQuant,44 EncyclopeDIA,45 Skyline,46 Philosopher.47.