Analyse multi-patients de données génomiques
Type de document :
Communication dans un congrès avec actes
URL permanente :
Titre :
Analyse multi-patients de données génomiques
Auteur(s) :
Grimonprez, Quentin [Auteur]
Celisse, Alain [Auteur]
Marot, Guillemette [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Celisse, Alain [Auteur]

Marot, Guillemette [Auteur]

MOdel for Data Analysis and Learning [MODAL]
Titre de la manifestation scientifique :
46e Journées de Statistique
Organisateur(s) de la manifestation scientifique :
Société Française de Statistique
Ville :
Rennes
Pays :
France
Date de début de la manifestation scientifique :
2014-06-02
Date de publication :
2014-06-02
Mot(s)-clé(s) :
Package
Genomic markers selection
Copy-number
Data normalization
SNP
Segmentation
Genomic markers selection
Copy-number
Data normalization
SNP
Segmentation
Discipline(s) HAL :
Statistiques [stat]
Résumé en anglais : [en]
MPAgenomics, standing for multi-patients analysis (MPA) of genomic markers, is an R-package devoted to: (i) efficient segmentation, and (ii) genomic marker selection from multi-patient copy number and SNP data profiles.It ...
Lire la suite >MPAgenomics, standing for multi-patients analysis (MPA) of genomic markers, is an R-package devoted to: (i) efficient segmentation, and (ii) genomic marker selection from multi-patient copy number and SNP data profiles.It provides wrappers from commonly used packages to facilitate their repeated (sometimes difficult) use, offering an easy-to-use pipeline for beginners in R. The segmentation of successive multiple profiles (finding losses and gains) is based on a new automatic choice of influential parameters since default ones were misleading in the original packages. Considering multiple profiles in the same time, MPAgenomics wraps efficient penalized regression methods to select relevant markers associated with a given response.Lire moins >
Lire la suite >MPAgenomics, standing for multi-patients analysis (MPA) of genomic markers, is an R-package devoted to: (i) efficient segmentation, and (ii) genomic marker selection from multi-patient copy number and SNP data profiles.It provides wrappers from commonly used packages to facilitate their repeated (sometimes difficult) use, offering an easy-to-use pipeline for beginners in R. The segmentation of successive multiple profiles (finding losses and gains) is based on a new automatic choice of influential parameters since default ones were misleading in the original packages. Considering multiple profiles in the same time, MPAgenomics wraps efficient penalized regression methods to select relevant markers associated with a given response.Lire moins >
Langue :
Anglais
Audience :
Nationale
Vulgarisation :
Non
Établissement(s) :
CHU Lille
CNRS
Université de Lille
CNRS
Université de Lille
Date de dépôt :
2020-06-08T14:10:38Z