Computer aided manual validation of mass spectrometry-based proteomic data
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Author(s)
Curran, Timothy G.
Bryson, Bryan D.
Reigelhaupt, Michael
Johnson, Hannah
White, Forest M.
Date Issued
March 2013
Journal
Methods
Publisher
Elsevier
Citation
Curran, Timothy G., Bryan D. Bryson, Michael Reigelhaupt, Hannah Johnson, and Forest M. White. “Computer Aided Manual Validation of Mass Spectrometry-Based Proteomic Data.” Methods 61, no. 3 (June 2013): 219–226.
Version
Author's final manuscript
Abstract
Advances in mass spectrometry-based proteomic technologies have increased the speed of analysis and the depth provided by a single analysis. Computational tools to evaluate the accuracy of peptide identifications from these high-throughput analyses have not kept pace with technological advances; currently the most common quality evaluation methods are based on statistical analysis of the likelihood of false positive identifications in large-scale data sets. While helpful, these calculations do not consider the accuracy of each identification, thus creating a precarious situation for biologists relying on the data to inform experimental design. Manual validation is the gold standard approach to confirm accuracy of database identifications, but is extremely time-intensive. To palliate the increasing time required to manually validate large proteomic datasets, we provide computer aided manual validation software (CAMV) to expedite the process. Relevant spectra are collected, catalogued, and pre-labeled, allowing users to efficiently judge the quality of each identification and summarize applicable quantitative information. CAMV significantly reduces the burden associated with manual validation and will hopefully encourage broader adoption of manual validation in mass spectrometry-based proteomics.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Mathematics
Koch Institute for Integrative Cancer Research at MIT
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DOI of Published Version
https://doi.org/10.1016/j.ymeth.2013.03.004
