Molecular mechanisms reconstruction from single-cell multi-omics data with HuMMuS.
Bioinformatics
; 40(5)2024 May 02.
Article
en En
| MEDLINE
| ID: mdl-38460192
ABSTRACT
MOTIVATION The molecular identity of a cell results from a complex interplay between heterogeneous molecular layers. Recent advances in single-cell sequencing technologies have opened the possibility to measure such molecular layers of regulation. RESULTS:
Here, we present HuMMuS, a new method for inferring regulatory mechanisms from single-cell multi-omics data. Differently from the state-of-the-art, HuMMuS captures cooperation between biological macromolecules and can easily include additional layers of molecular regulation. We benchmarked HuMMuS with respect to the state-of-the-art on both paired and unpaired multi-omics datasets. Our results proved the improvements provided by HuMMuS in terms of transcription factor (TF) targets, TF binding motifs and regulatory regions prediction. Finally, once applied to snmC-seq, scATAC-seq and scRNA-seq data from mouse brain cortex, HuMMuS enabled to accurately cluster scRNA profiles and to identify potential driver TFs. AVAILABILITY AND IMPLEMENTATION HuMMuS is available at https//github.com/cantinilab/HuMMuS.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Factores de Transcripción
/
Análisis de la Célula Individual
Límite:
Animals
/
Humans
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Francia