A framework for quantifiable local and global structure preservation in single-cell dimensionality reduction
David Novak,
Cyril de Bodt,
Pierre Lambert
et al.
Abstract:Dimensionality reduction techniques are essential in current single-cell ‘omics approaches, offering biologists a first glimpse of the structure present in their data. These methods are most often used to visualise high-dimensional and noisy input datasets, but are also frequently applied for downstream structure learning. By design, every dimensionality reduction technique preserves some characteristics of the original, high-dimensional data, while discarding others. We introduceViScore, a framework for valid… Show more
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