The Impact of Normalization Methods on RNA-Seq Data Analysis

BioMed Research International

Volumn 2015, Issue , 2015, Pages

  Zyprych Walczak, J ^a   Szabelska, A ^a   Handschuh, L ^b,c   Gorczak K ^a   Klamecka, K ^a   Figlerowicz, M ^b   Siatkowski, I ^a  

^a POZNA UNIVERSITY OF LIFE SCIENCES   (Poland)

^b INSTITUTE OF BIOORGANIC CHEMISTRY   (Poland)

^c POZNAN UNIVERSITY OF MEDICAL SCIENCES   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

TRANSCRIPTOME;

ARTICLE; BAYESIAN LEARNING; CONTROLLED STUDY; DATA ANALYSIS; DATA PROCESSING; DISCRIMINANT ANALYSIS; GENE EXPRESSION; GENE EXPRESSION ASSAY; HIGH THROUGHPUT SEQUENCING; HOUSEKEEPING GENE; HUMAN; HUMAN CELL; MEASUREMENT ACCURACY; RANDOM FOREST; RNA SEQUENCE; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; WORKFLOW; ALGORITHM; BIOLOGICAL MODEL; GENE EXPRESSION PROFILING; NORMAL DISTRIBUTION; PROCEDURES; SEQUENCE ANALYSIS; STANDARDS;

ALGORITHMS; GENE EXPRESSION PROFILING; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; MODELS, GENETIC; NORMAL DISTRIBUTION; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS, RNA;

EID: 84934326250     PISSN: 23146133     EISSN: 23146141     Source Type: Journal    
DOI: 10.1155/2015/621690     Document Type: Article

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