Title :

Analyse multi-patients de données génomiques

Author(s) :

Grimonprez, Quentin [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Celisse, Alain [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
MOdel for Data Analysis and Learning [MODAL]
Marot, Guillemette [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]

Conference title :

46e Journées de Statistique

Conference organizers(s) :

SFDS

City :

Rennes

Country :

France

Start date of the conference :

2014-06-02

Publication date :

2014

English keyword(s) :

segmentation
SNP
data normalization
copy-number
genomic markers selection
package

HAL domain(s) :

Statistiques [stat]
Sciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]

English abstract : [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 ...
Show more >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.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Nationale

Popular science :

Non

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL