Forest Fire Clustering for single-cell sequencing combines iterative label propagation with parallelized Monte Carlo simulations

In the era of single-cell sequencing, there is a growing need to extract insights from data with clustering methods. Here, we introduce Forest Fire Clustering, an efficient and interpretable method for cell-type discovery from single-cell data. Forest Fire Clustering makes minimal prior assumptions...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Zhanlin, Goldwasser, Jeremy, Tuckman, Philip, Liu, Jason, Zhang, Jing, Gerstein, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209427/
https://www.ncbi.nlm.nih.gov/pubmed/35725981
http://dx.doi.org/10.1038/s41467-022-31107-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209427/
https://www.ncbi.nlm.nih.gov/pubmed/35725981
http://dx.doi.org/10.1038/s41467-022-31107-8

Ejemplares similares