Cargando…
Robust and efficient single-cell Hi-C clustering with approximate k-nearest neighbor graphs
MOTIVATION: Hi-C technology provides insights into the 3D organization of the chromatin, and the single-cell Hi-C method enables researchers to gain knowledge about the chromatin state in individual cell levels. Single-cell Hi-C interaction matrices are high dimensional and very sparse. To cluster t...
Autores principales: | Wolff, Joachim, Backofen, Rolf, Grüning, Björn |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9502147/ https://www.ncbi.nlm.nih.gov/pubmed/34021764 http://dx.doi.org/10.1093/bioinformatics/btab394 |
Ejemplares similares
-
Loop detection using Hi-C data with HiCExplorer
por: Wolff, Joachim, et al.
Publicado: (2022) -
Single-cell and Spatial Transcriptomics Clustering with an Optimized Adaptive K-Nearest Neighbor Graph
por: Li, Jia, et al.
Publicado: (2023) -
Scool: a new data storage format for single-cell Hi-C data
por: Wolff, Joachim, et al.
Publicado: (2021) -
Scool: a new data storage format for single-cell Hi-C data
por: Wolff, Joachim, et al.
Publicado: (2020) -
Accumulative Quantization for Approximate Nearest Neighbor Search
por: Ai, Liefu, et al.
Publicado: (2022)