Kerfdr: A semi-parametric kernel-based approach to local false discovery rate estimation

BMC Bioinformatics

Volumn 10, Issue , 2009, Pages

  Guedj, Mickael ^a,d   Robin, Stephane ^b,d   Celisse, Alain ^b,d   Nuel, Gregory ^a,c,d  

^a UNIVERSITÉ D EVRY VAL D ESSONNE   (France)

^b AGROPARISTECH   (France)

^c UNIVERSITÉ PARIS DESCARTES   (France)

^d Statistics for Systems Biology Group   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ALTERNATIVE HYPOTHESIS; FALSE DISCOVERY RATE; GENOME-WIDE ASSOCIATION STUDIES; KERNEL BASED APPROACH; LOCAL FALSE DISCOVERY RATES; MONTE-CARLO SIMULATIONS; STATISTICAL HYPOTHESIS; TRUNCATED DISTRIBUTIONS;

GENE EXPRESSION; INTELLIGENT SYSTEMS;

STATISTICAL TESTS;

ALGORITHM; ARTICLE; COMPUTER SIMULATION; CONTROLLED STUDY; DNA SEQUENCE; FALSE DISCOVERY RATE; GENE EXPRESSION; GENETIC ASSOCIATION; HIGH THROUGHPUT SCREENING; INTERMETHOD COMPARISON; KERNEL METHOD; MONTE CARLO METHOD; PARAMETRIC TEST; STATISTICAL ANALYSIS; STATISTICAL DISTRIBUTION; BIOLOGY; COMPUTER PROGRAM; GENE EXPRESSION PROFILING; INTERNET; LABORATORY DIAGNOSIS; METHODOLOGY; STATISTICAL MODEL;

COMPUTATIONAL BIOLOGY; FALSE POSITIVE REACTIONS; GENE EXPRESSION PROFILING; GENOME-WIDE ASSOCIATION STUDY; INTERNET; MODELS, STATISTICAL; SOFTWARE;

EID: 65549134384     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-10-84     Document Type: Article

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