Data-driven assessment of dimension reduction quality for single-cell omics data.
Patterns (N Y)
; 3(3): 100465, 2022 Mar 11.
Article
in En
| MEDLINE
| ID: mdl-35510193
ABSTRACT
Dimension reduction (DR) techniques have become synonymous with single-cell omics data due to their ability to generate attractive visualizations and enable analyses of high-dimensional data. In this issue of Patterns, Johnsona et al. develop a statistical approach to assist in selecting high-quality reduced representations to improve analyses and biological interpretations.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Patterns (N Y)
Year:
2022
Document type:
Article
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