Journal
NATURE METHODS
Volume 11, Issue 3, Pages 301-U272Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/nmeth.2806
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Funding
- LiverX program of the Swiss Initiative for Systems Biology (SystemsX)
- European Research Council (ERC) [233226]
- Swiss National Science Foundation [31-147086]
- US National Science Foundation CAREER award [DBI-1054826]
- Direct For Biological Sciences
- Div Of Biological Infrastructure [1054826] Funding Source: National Science Foundation
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Targeted proteomics is a method of choice for accurate and high-throughput quantification of predefined sets of proteins. Many workflows use isotope-labeled reference peptides for every target protein, which is time consuming and costly. We report a statistical approach for quantifying full protein panels with a reduced set of reference peptides. This label-sparse approach achieves accurate quantification while reducing experimental cost and time. It is implemented in the software tool SparseQuant.
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