A stochastic downhill search algorithm for estimating the local false discovery rate.
IEEE/ACM Trans Comput Biol Bioinform
; 1(3): 98-108, 2004.
Article
em En
| MEDLINE
| ID: mdl-17048385
ABSTRACT
Screening for differential gene expression in microarray studies leads to difficult large-scale multiple testing problems. The local false discovery rate is a statistical concept for quantifying uncertainty in multiple testing. In this paper, we introduce a novel estimator for the local false discovery rate that is based on an algorithm which splits all genes into two groups, representing induced and noninduced genes, respectively. Starting from the full set of genes, we successively exclude genes until the gene-wise p-values of the remaining genes look like a typical sample from a uniform distribution. In comparison to other methods, our algorithm performs compatibly in detecting the shape of the local false discovery rate and has a smaller bias with respect to estimating the overall percentage of noninduced genes. Our algorithm is implemented in the Bioconductor compatible R package TWILIGHT version 1.0.1, which is available from http//compdiag.molgen.mpg.de/software or from the Bioconductor project at http//www.bioconductor.org.
Buscar no Google
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Modelos Estatísticos
/
Perfilação da Expressão Gênica
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
ACM Trans Comput Biol Bioinform
Assunto da revista:
BIOLOGIA
/
INFORMATICA MEDICA
Ano de publicação:
2004
Tipo de documento:
Article
País de afiliação:
Alemanha