Data-driven assessment of dimension reduction quality for single-cell omics data.
editorial · Level V
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- Record sourced from PubMed, PMID 35510193.
- Also identified by DOI 10.1016/j.patter.2022.100465 and PMC identifier 9058902.
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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 <i>Patterns</i>, Johnsona et al. develop a statistical approach to assist in selecting high-quality reduced representations to improve analyses and biological interpretations.