Global rank-invariant set normalization (GRSN) to reduce systematic distortions in microarray data

BMC Bioinformatics

Volumn 9, Issue , 2008, Pages

  Pelz, Carl R ^a   Kulesz Martin, Molly ^a,b   Bagby, Grover ^a   Sears, Rosalie C ^a  

^a OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

^b OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL SAMPLES; DATA INTERPRETATION; INTENSITY-DEPENDENT; MICROARRAY EXPERIMENTS; MICROARRAY TECHNOLOGIES; NON-LINEAR VARIATION; PATHWAY IDENTIFICATION; REFERENCE POINTS;

GENE EXPRESSION; ITERATIVE METHODS; PROBES;

DATA HANDLING;

ANALYSIS OF VARIANCE; ARTICLE; ARTIFACT; BIOLOGICAL MODEL; BIOLOGY; COMPUTER SIMULATION; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETIC DATABASE; METHODOLOGY; REPRODUCIBILITY; SIGNAL TRANSDUCTION; STATISTICAL ANALYSIS;

ANALYSIS OF VARIANCE; ARTIFACTS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; DATABASES, GENETIC; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; MODELS, GENETIC; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REPRODUCIBILITY OF RESULTS; SIGNAL TRANSDUCTION;

EID: 60849121405     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-9-520     Document Type: Article

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