Robust group fused lasso for multisample copy number variation detection under uncertainty.
IET Syst Biol
; 10(6): 229-236, 2016 Dec.
Article
em En
| MEDLINE
| ID: mdl-27879477
ABSTRACT
One of the most important needs in the post-genome era is providing the researchers with reliable and efficient computational tools to extract and analyse this huge amount of biological data, in which DNA copy number variation (CNV) is a vitally important one. Array-based comparative genomic hybridisation (aCGH) is a common approach in order to detect CNVs. Most of methods for this purpose were proposed for one-dimensional profiles. However, slightly this focus has moved from one- to multi-dimensional signals. In addition, since contamination of these profiles with noise is always an issue, it is highly important to have a robust method for analysing multi-sample aCGH profiles. In this study, the authors propose robust group fused lasso which utilises the robust group total variations. Instead of l2,1 norm, the l1 - l2 M-estimator is used which is more robust in dealing with non-Gaussian noise and high corruption. More importantly, Correntropy (Welsch M-estimator) is also applied for fitting error. Extensive experiments indicate that the proposed method outperforms the state-of-the art algorithms and techniques under a wide range of scenarios with diverse noises.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Hibridização Genômica Comparativa
/
Variações do Número de Cópias de DNA
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Female
/
Humans
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article