Sphetcher: Spherical Thresholding Improves Sketching of Single-Cell Transcriptomic Heterogeneity.

ABSTRACT: The massive size of single-cell RNA sequencing datasets often exceeds the capability of current computational analysis methods to solve routine tasks such as detection of cell types. Recently, geometric sketching was introduced as an alternative to uniform subsampling. It selects a subset of cells (the sketch) that evenly cover the transcriptomic space occupied by the original dataset, to accelerate downstream analyses and highlight rare cell types. Here, we propose algorithm Sphetcher that makes use of the thresholding technique to efficiently pick representative cells within spheres (as opposed to the typically used equal-sized boxes) that cover the entire transcriptomic space. We show that the spherical sketch computed by Sphetcher constitutes a more accurate representation of the origi

SUBMITTER: Do VH 

PROVIDER: S-EPMC7235285 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature