Solution to Statistical Challenges in Proteomics Is More Statistics, Not Less

Journal of Proteome Research

Volumn 14, Issue 10, 2015, Pages 4099-4103

  Serang, Oliver ^a,b   Käll, Lukas ^c  

^a FREIE UNIVERSITÄT BERLIN   (Germany)

^b LEIBNIZ INSTITUTE OF FRESHWATER ECOLOGY AND INLAND FISHERIES   (Germany)

^c ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

false discovery rate (FDR); human proteome; multiple testing; protein identification; simulation; statistics

Indexed keywords

PROTEIN;

DATA BASE; FALSE DISCOVERY RATE; GENETIC ASSOCIATION; MASS SPECTROMETRY; NULL HYPOTHESIS; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEOMICS; REVIEW; SIMULATION; ALGORITHM; ARTIFACT; COMPUTER PROGRAM; HUMAN; ISOLATION AND PURIFICATION; PROCEDURES; PROTEIN DATABASE; STATISTICS AND NUMERICAL DATA; TANDEM MASS SPECTROMETRY;

ALGORITHMS; ARTIFACTS; DATABASES, PROTEIN; HUMANS; PROTEINS; PROTEOMICS; SOFTWARE; TANDEM MASS SPECTROMETRY;

EID: 84942905791     PISSN: 15353893     EISSN: 15353907     Source Type: Journal    
DOI: 10.1021/acs.jproteome.5b00568     Document Type: Review

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