PT  - JOURNAL ARTICLE
AU  - Chari, Tara
AU  - Banerjee, Joeyta
AU  - Pachter, Lior
TI  - The Specious Art of Single-Cell Genomics
AID  - 10.1101/2021.08.25.457696
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.08.25.457696
4099  - http://biorxiv.org/content/early/2021/08/26/2021.08.25.457696.short
4100  - http://biorxiv.org/content/early/2021/08/26/2021.08.25.457696.full
AB  - Dimensionality reduction is standard practice for filtering noise and identifying relevant dimensions in large-scale data analyses. In biology, single-cell expression studies almost always begin with reduction to two or three dimensions to produce ‘all-in-one’ visuals of the data that are amenable to the human eye, and these are subsequently used for qualitative and quantitative analysis of cell relationships. However, there is little theoretical support for this practice. We examine the theoretical and practical implications of low-dimensional embedding of single-cell data, and find extensive distortions incurred on the global and local properties of biological patterns relative to the high-dimensional, ambient space. In lieu of this, we propose semi-supervised dimension reduction to higher dimension, and show that such targeted reduction guided by the metadata associated with single-cell experiments provides useful latent space representations for hypothesis-driven biological discovery.Competing Interest StatementThe authors have declared no competing interest.