A comparison of statistical methods for detecting differentially expressed genes from RNA-seq data

American Journal of Botany

Volumn 99, Issue 2, 2012, Pages 248-256

  Kvam, Vanessa M ^a   Liu, Peng ^a   Yaqing, Si ^a  

^a E005A Lagomarcino Hall   (United States)

Author keywords

Bayseq; DEseq; Edger; False discovery rate; RNA seq; Statistical test; Two stage Poisson model

Indexed keywords

PLANT RNA;

ADVANCED TECHNOLOGY; BAYESIAN ANALYSIS; GENE EXPRESSION; GENOMICS; SOFTWARE;

ARTICLE; BIOLOGICAL MODEL; BIOLOGY; COMPARATIVE STUDY; COMPUTER PROGRAM; COMPUTER SIMULATION; GENE EXPRESSION REGULATION; GENETICS; METHODOLOGY; NUCLEIC ACID DATABASE; NUCLEOTIDE SEQUENCE; PLANT GENE; POISSON DISTRIBUTION; RECEIVER OPERATING CHARACTERISTIC; REPRODUCIBILITY; SEQUENCE ANALYSIS;

BASE SEQUENCE; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATABASES, NUCLEIC ACID; GENE EXPRESSION REGULATION, PLANT; GENES, PLANT; MODELS, GENETIC; POISSON DISTRIBUTION; REPRODUCIBILITY OF RESULTS; RNA, PLANT; ROC CURVE; SEQUENCE ANALYSIS, RNA; SOFTWARE;

EID: 84858606519     PISSN: 00029122     EISSN: None     Source Type: Journal    
DOI: 10.3732/ajb.1100340     Document Type: Article

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