MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data.
Genome Biol
; 21(1): 111, 2020 05 11.
Article
en En
| MEDLINE
| ID: mdl-32393329
ABSTRACT
Technological advances have enabled the profiling of multiple molecular layers at single-cell resolution, assaying cells from multiple samples or conditions. Consequently, there is a growing need for computational strategies to analyze data from complex experimental designs that include multiple data modalities and multiple groups of samples. We present Multi-Omics Factor Analysis v2 (MOFA+), a statistical framework for the comprehensive and scalable integration of single-cell multi-modal data. MOFA+ reconstructs a low-dimensional representation of the data using computationally efficient variational inference and supports flexible sparsity constraints, allowing to jointly model variation across multiple sample groups and data modalities.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Análisis Factorial
/
Análisis de la Célula Individual
Tipo de estudio:
Prognostic_studies
Límite:
Animals
Idioma:
En
Revista:
Genome Biol
Asunto de la revista:
BIOLOGIA MOLECULAR
/
GENETICA
Año:
2020
Tipo del documento:
Article
País de afiliación:
Reino Unido