Numerical deconvolution of cDNA microarray signal: simulation study.
A computational model for simulation of the cDNA microarray experiments has been created. The simulation allows one to foresee the statistical properties of replicated experiments without actually performing them. We introduce a new concept, the so-called bio-weight, which allows for reconciliation between conflicting meanings of biological and statistical significance in microarray experiments. It is shown that, for a small sample size, the bio-weight is a more powerful criterion of the presence of a signal in microarray data as compared to the standard approach based on t test. Joint simulation of microarray and quantitative PCR data shows that the genes recovered by using the bio-weight have better chances to be confirmed by PCR than those obtained by the t test technique. We also employ extreme value considerations to derive plausible cutoff levels for hypothesis testing.
Rosenfeld
Simon
S
Biometry Research Group, Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, EPN 3136, 6130 Executive Boulevard, Rockville, MD 20892, USA. sr212a@nih.gov
Wang
Thomas
T
Kim
Young
Y
Milner
John
J
D045744:Cell Line, Tumor; D019295:Computational Biology / Q000379:methods; D018076:DNA, Complementary / Q000235:genetics; D006801:Humans; D008297:Male; D009363:Neoplasm Proteins / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D016133:Polymerase Chain Reaction / Q000379:methods*; D011471:Prostatic Neoplasms; D015203:Reproducibility of Results
D018076:DNA, Complementary; D009363:Neoplasm Proteins