Background: Selected and multiple reaction monitoring involves monitoring a multiplexed assay of proteotypic peptides and associated transitions in mass spectrometry runs. To describe peptide and associated transitions as stable, quantifiable, and reproducible representatives of proteins of interest, experimental and analytical validation is required. However, inadequate and disparate analytical tools and validation methods predispose assay performance measures to errors and inconsistencies. Results: Implemented as a freely available, open-source tool in the platform independent Java programing language, MRMPlus computes analytical measures as recommended recently by the Clinical Proteomics Tumor Analysis Consortium Assay Development Working Group for "Tier 2" assays - that is, non-clinical assays sufficient enough to measure changes due to both biological and experimental perturbations. Computed measures include; limit of detection, lower limit of quantification, linearity, carry-over, partial validation of specificity, and upper limit of quantification. Conclusions: MRMPlus streamlines assay development analytical workflow and therefore minimizes error predisposition. MRMPlus may also be used for performance estimation for targeted assays not described by the Assay Development Working Group. MRMPlus' source codes and compiled binaries can be freely downloaded from https://bitbucket.org/paiyetan/mrmplusguiand https://bitbucket.org/paiyetan/mrmplusgui/downloadsrespectively.
Bibliographical noteFunding Information:
The authors acknowledge all the members of the Center for Biomarker Discovery and Translation, Johns Hopkins Medical Institution; and members of the Assay Development Working Group (ADWG) of the National Cancer Institute (NCI) Clinical Proteomics Tumor Analysis Consortium (CPTAC). MRMPlus’ development was supported by the National Institutes of Health, National Cancer Institute, Clinical Proteomic Tumor Analysis Consortium (CPTAC, U24CA160036) ; the Early Detection Research Network (EDRN, U01CA152813); and the National Heart, Lung, and Blood Institute, Programs of Excellence in Glycosciences (PEG, P01HL107153). The authors also acknowledge the help of Jeffrey Whiteaker, Ph.D., of the Fred Hutchinson Cancer Research Center in Seattle, Washington, with deriving comparable performance results on PanoramaWeb.
© 2015 Aiyetan et al.