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Nat Methods. 2014 Mar;11(3):301-4. doi: 10.1038/nmeth.2806. Epub 2014 Jan 19.

Targeted protein quantification using sparse reference labeling.

Author information

1
1] Department of Statistics, Purdue University, West Lafayette, Indiana, USA. [2].
2
1] Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland. [2].
3
1] Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland. [2] Competence Center for Systems Physiology and Metabolic Diseases, ETH Zurich, Zurich, Switzerland. [3] Faculty of Science, University of Zurich, Zurich, Switzerland.
4
1] Department of Statistics, Purdue University, West Lafayette, Indiana, USA. [2] Department of Computer Science, Purdue University, West Lafayette, Indiana, USA.

Abstract

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.

PMID:
24441934
DOI:
10.1038/nmeth.2806
[Indexed for MEDLINE]

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