Statistical elimination of spectral features with large between-run variation enhances quantitative protein-level conclusions in experiments with data-independent spectral acquisition

BMC Bioinformatics

Meeting Abstract

Hannes Röst¹  Yansheng Liu¹  Ruedi Aebersold²  Olga Vitek³  Lin-Yang Cheng⁴  Ching-Yun Chang⁴ 

[1] Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093, Zurich, Switzerland;Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093, Zurich, Switzerland;Faculty of Science, University of Zurich, 8057, Zurich, Switzerland;Department of Computer Science, Purdue University, West Lafayette, IN, USA;Department of Statistics, Purdue University, West Lafayette, IN, USA;

关键词: Feature Selection;    False Discovery Rate;    Spectral Feature;    Protein Abundance;    Select Reaction Monitoring;   

DOI  :  10.1186/1471-2105-16-S2-A4

来源: Springer

【 授权许可】

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© Cheng et al; licensee BioMed Central Ltd. 2015