Detecting differential protein abundance by combining peptide level P-values
[1];
[2];
[3]
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Washington State Univ., Pullman, WA (United States)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Washington State Univ., Pullman, WA (United States
The majority of methods for detecting differentially abundant proteins between samples in label-free LC-MS bottom-up proteomics experiments rely on statistically testing inferred protein abundances derived from peptide ionization intensities or averaging peptide level statistics. Here in this paper, we statistically test peptide ionization intensities directly and combine the resulting dependent P-values using the Empirical Brown's Method (EBM), avoiding error introduced through the estimation of protein abundances or summarizing test statistics. We show that on a spike-in proteomics dataset, a peptide level approach using EBM outperforms differential abundance detection using a protein level approach and several analysis workflows, including MSstats. Additionally, we demonstrate the effectiveness of this approach by detecting enriched proteins from an activity-based protein profiling dataset.
- Research Organization:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- AC05-76RL01830; AC06-76RL01830
- OSTI ID:
- 1752963
- Report Number(s):
- PNNL-SA-144005
- Journal Information:
- Molecular Omics, Vol. 16, Issue 6; ISSN 2515-4184
- Publisher:
- Royal Society of ChemistryCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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