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. Author manuscript; available in PMC: 2022 Apr 3.
Published in final edited form as: J Proteome Res. 2022 Feb 27;21(4):891–898. doi: 10.1021/acs.jproteome.1c00894

Figure 3. The effect size on the protein level is minimized for proteins with greater numbers of peptides.

Figure 3.

An isobaric-labeled dataset associated with the Clinical Proteomics Tumor Analysis Consortium (CPTAC),(41) consists of 181,389 peptides mapped to 10,495 unique protein identifiers; proteins ranged from having 1 to 563 peptides associated with them. The a) log2 fold-change and b) log10 p-value is based on a comparison of tumor residual disease. The second dataset is label free and smaller, based on a Calu-3 cell culture experiment, also publicly available (MSV000079152).(42) This dataset has 15,953 unique protein identifiers, with proteins represented by 1 to 311 peptides. In this dataset the a) log2 fold-change and b) log10 p-value is based on a Middle East Respiratory Syndrome (MERS) infection to a sham control. Protein sum-based quantification sums all peptide measures per protein coding gene. For b) and d) the red line indicates the significance cutoff corresponding to p=0.05, with significantly different proteins falling below the line. Figures are truncated to 50 for ease of visualization.