Signal localization: a new approach in signal discovery.
Biom J
; 59(1): 126-144, 2017 Jan.
Article
em En
| MEDLINE
| ID: mdl-27775844
ABSTRACT
A new approach for statistical association signal identification is developed in this paper. We consider a strategy for nonprecise signal identification by extending the well-known signal detection and signal identification methods applicable to the multiple testing problem. Collection of statistical instruments under the presented approach is much broader than under the traditional signal identification methods, allowing more efficient signal discovery. Further assessments of maximal value and average statistics in signal discovery are improved. While our method does not attempt to detect individual predictors, it instead detects sets of predictors that are jointly associated with the outcome. Therefore, an important application would be in genome wide association study (GWAS), where it can be used to detect genes which influence the phenotype but do not contain any individually significant single nucleotide polymorphism (SNP). We compare power of the signal identification method based on extremes of single p-values with the signal localization method based on average statistics for logarithms of p-values. A simulation analysis informs the application of signal localization using the average statistics for wide signals discovery in Gaussian white noise process. We apply average statistics and the localization method to GWAS to discover better gene influences of regulating loci in a Chinese cohort developed for risk of nasopharyngeal carcinoma (NPC).
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Estudo de Associação Genômica Ampla
/
Modelos Biológicos
Tipo de estudo:
Prognostic_studies
Limite:
Humans
País como assunto:
Asia
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article