Statistical properties of the quantile normalization method for density curve alignment
ABSTRACT: The article investigates the large sample properties of the quantile normalization method by Bolstad et al. (2003) [4] which has become one of the most popular methods to align density curves in microarray data analysis. We prove consistency of this method which is viewed as a particular c...
- Autores:
-
Gallón Gómez, Santiago Alejandro
Loubes, Jean Michel
Maza, Elie
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2013
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/7347
- Acceso en línea:
- http://hdl.handle.net/10495/7347
- Palabra clave:
- Wasserstein distance
Curve registration
Manifold registration
Microarray data analysis
Normalization
Order statistics
Structural expectation
- Rights
- openAccess
- License
- Atribución 2.5
| Summary: | ABSTRACT: The article investigates the large sample properties of the quantile normalization method by Bolstad et al. (2003) [4] which has become one of the most popular methods to align density curves in microarray data analysis. We prove consistency of this method which is viewed as a particular case of the structural expectation procedure for curve alignment, which corresponds to a notion of barycenter of measures in the Wasserstein space. Moreover, we show that, this method fails in some case of mixtures, and we propose a new methodology to cope with this issue. |
|---|