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Technology Description	A tool, PIPER, has been developed that uses protein expression data to improve protein identification fidelity in proteomics experiments using mass spectrometry
Category	Software
PRC	Caprion Proteomics Inc.
PubMed ID	18062667
Author	Paul Kearney, Heather Butler, Kevin Eng, and Patrice Hugo
Publication Description	The authors evaluate the hypothesis that tryptic peptides originating from the same protein have similar expression profiles across samples. Evidence supporting this hypothesis is provided. The approach is integrated into a protein identification tool, PIPER (Protein Identification and Peptide Expression Resolver), that reduces erroneous protein identifications below 5%. PIPER’s utility is illustrated by application to a 72-sample biomarker discovery study where it is demonstrated that false positive protein identifications can be reduced below 5%. The authors recommend that PIPER methodology be incorporated into proteomic studies where both protein expression and identification data are collected.
Methodology	PIPER correlates expression data with peptide data produced by LC-MS in order to estimate the false discovery rate and to identify differentially expressed genes.