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J Proteome Res. 2019 Jan 4;18(1):535-541. doi: 10.1021/acs.jproteome.8b00113. Epub 2018 Nov 2.

apQuant: Accurate Label-Free Quantification by Quality Filtering.

Author information

1
Research Institute of Molecular Pathology (IMP) , Vienna Biocenter (VBC) , Campus-Vienna-Biocenter 1 , 1030 Vienna , Austria.
2
Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA) , Vienna Biocenter (VBC) , Dr. Bohr-Gasse 3 , 1030 Vienna , Austria.
3
Gregor Mendel Institute of Molecular Plant Biology (GMI) , Vienna Biocenter (VBC) , Dr. Bohr-Gasse 3 , 1030 Vienna , Austria.

Abstract

Label-free quantification of shotgun proteomics data is a frequently used strategy, offering high dynamic range, sensitivity, and the ability to compare a high number of samples without additional labeling effort. Here, we present a bioinformatics approach that significantly improves label-free quantification results. We employ Percolator to assess the quality of quantified peptides. This allows to extract accurate and reliable quantitative results based on false discovery rate. Benchmarking our approach on previously published public data shows that it considerably outperforms currently available algorithms. apQuant is available free of charge as a node for Proteome Discoverer.

KEYWORDS:

computational proteomics; data analysis pipeline; label-free quantification; mass spectrometry; quantitative proteomics

PMID:
30351950
DOI:
10.1021/acs.jproteome.8b00113
[Indexed for MEDLINE]

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