Cargando…
FR-Match: robust matching of cell type clusters from single cell RNA sequencing data using the Friedman–Rafsky non-parametric test
Single cell/nucleus RNA sequencing (scRNAseq) is emerging as an essential tool to unravel the phenotypic heterogeneity of cells in complex biological systems. While computational methods for scRNAseq cell type clustering have advanced, the ability to integrate datasets to identify common and novel c...
Autores principales: | Zhang, Yun, Aevermann, Brian D, Bakken, Trygve E, Miller, Jeremy A, Hodge, Rebecca D, Lein, Ed S, Scheuermann, Richard H |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8294536/ https://www.ncbi.nlm.nih.gov/pubmed/33249453 http://dx.doi.org/10.1093/bib/bbaa339 |
Ejemplares similares
-
Cell type matching in single-cell RNA-sequencing data using FR-Match
por: Zhang, Yun, et al.
Publicado: (2022) -
Matching single cells across modalities with contrastive learning and optimal transport
por: Gossi, Federico, et al.
Publicado: (2023) -
Mapping cell populations in flow cytometry data for cross‐sample comparison using the Friedman–Rafsky test statistic as a distance measure
por: Hsiao, Chiaowen, et al.
Publicado: (2015) -
Qmatey: an automated pipeline for fast exact matching-based alignment and strain-level taxonomic binning and profiling of metagenomes
por: Adams, Alison K, et al.
Publicado: (2023) -
Robust discovery of gene regulatory networks from single-cell gene expression data by Causal Inference Using Composition of Transactions
por: Shojaee, Abbas, et al.
Publicado: (2023)