RT Journal Article
T1 A Bayesian decision procedure for testing multiple hypotheses in DNA microarray experiments
A1 Gómez Villegas, Miguel Ángel
A1 Salazar Mendoza, Isabel
A1 Sanz San Miguel, Luis
AB DNA microarray experiments require the use of multiple hypothesis testing procedures because thousands of hypotheses are simultaneously tested. We deal with this problem from a Bayesian decision theory perspective. We propose a decision criterion based on an estimation of the number of false null hypotheses (FNH), taking as an error measure the proportion of the posterior expected number of false positives with respect to the estimated number of true null hypotheses. The methodology is applied to a Gaussian model when testing bilateral hypotheses. The procedure is illustrated with both simulated and real data examples and the results are compared to those obtained by the Bayes rule when an additive loss function is considered for each joint action and the generalized loss 0-1 function for each individual action. Our procedure significantly reduced the percentage of false negatives whereas the percentage of false positives remains at an acceptable level.
PB De Gruyter
SN 2194-6302
YR 2014
FD 2014-02
LK https://hdl.handle.net/20.500.14352/33504
UL https://hdl.handle.net/20.500.14352/33504
NO Gómez Villegas, M. A., Salazar Mendoza, I. & Sanz San Miguel, L. «A Bayesian decision procedure for testing multiple hypotheses in DNA microarray experiments». Statistical Applications in Genetics and Molecular Biology, vol. 13, n.o 1, enero de 2014. DOI.org (Crossref), https://doi.org/10.1515/sagmb-2012-0076.
DS Docta Complutense
RD 1 oct 2024