Adam Gayoso

TL;DR: It is shown that Palantir outperforms existing algorithms in identifying cell lineages and recapitulating gene expression trends during differentiation, is generalizable to diverse tissue types, and is well-suited to resolving less-studied differentiating systems.

TL;DR: In this article, the authors present a framework for end-to-end joint analysis of CITE-seq data that probabilistically represents the data as a composite of biological and technical factors, including protein background and batch effects.

TL;DR: ScArches as mentioned in this paper uses transfer learning and parameter optimization to enable efficient, decentralized, iterative reference building and contextualization of new datasets with existing references without sharing raw data, which can facilitate collaborative projects by enabling iterative construction, updating, sharing and efficient use of reference atlas.