Machine Learning Algorithms Reveals Country-Specific Metagenomic Taxa from American Gut Project Data.
Stud Health Technol Inform
; 281: 382-386, 2021 May 27.
Article
em En
| MEDLINE
| ID: mdl-34042770
ABSTRACT
In recent years, microbiota has become an increasingly relevant factor for the understanding and potential treatment of diseases. In this work, based on the data reported by the largest study of microbioma in the world, a classification model has been developed based on Machine Learning (ML) capable of predicting the country of origin (United Kingdom vs United States) according to metagenomic data. The data were used for the training of a glmnet algorithm and a Random Forest algorithm. Both algorithms obtained similar results (0.698 and 0.672 in AUC, respectively). Furthermore, thanks to the application of a multivariate feature selection algorithm, eleven metagenomic genres highly correlated with the country of origin were obtained. An in-depth study of the variables used in each model is shown in the present work.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Metagenômica
/
Aprendizado de Máquina
Tipo de estudo:
Incidence_studies
/
Prognostic_studies
País/Região como assunto:
America do norte
/
Europa
Idioma:
En
Revista:
Stud Health Technol Inform
Assunto da revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Espanha