An Optimal Test with Maximum Average Power While Controlling FDR with Application to RNA-Seq Data

Biometrics

Volumn 69, Issue 3, 2013, Pages 594-605

  Si, Yaqing ^a   Liu, Peng ^a  

^a Iowa State University   (United States)

Author keywords

Empirical Bayes; FDR control; Gene expression; Maximum average power; RNA seq

Indexed keywords

GENE EXPRESSION; STATISTICAL TESTS;

AVERAGE POWER; EMPIRICAL BAYES; EXPRESSION LEVELS; FALSE DISCOVERY RATE; FALSE DISCOVERY RATE CONTROL; GENES EXPRESSION; MAXIMUM AVERAGE POWER; RATE CONTROLS; RNA-SEQ; RNA-SEQ DATUM;

RNA;

BIOMETRY; DATA SET; DISEASE TREATMENT; GENE EXPRESSION; HYPOTHESIS TESTING; OPTIMIZATION; RNA;

ZEA MAYS;

ARTICLE; BAYES THEOREM; BINOMIAL DISTRIBUTION; BIOMETRY; COMPUTER SIMULATION; EMPIRICAL BAYES; FDR CONTROL; GENE EXPRESSION; HIGH THROUGHPUT SEQUENCING; HUMAN; MAXIMUM AVERAGE POWER; METHODOLOGY; POISSON DISTRIBUTION; RNA-SEQ; SEQUENCE ANALYSIS; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICS;

EMPIRICAL BAYES; FDR CONTROL; GENE EXPRESSION; MAXIMUM AVERAGE POWER; RNA-SEQ;

BAYES THEOREM; BINOMIAL DISTRIBUTION; BIOMETRY; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; GENE EXPRESSION; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; MODELS, STATISTICAL; POISSON DISTRIBUTION; SEQUENCE ANALYSIS, RNA;

EID: 84892598640     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/biom.12036     Document Type: Article

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