Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis.

ABSTRACT: Reference-based cell-type annotation can significantly reduce time and effort in single-cell analysis by transferring labels from a previously-annotated dataset to a new dataset. However, label transfer by end-to-end computational methods is challenging due to the entanglement of technical (e.g., from different sequencing batches or techniques) and biological (e.g., from different cellular microenvironments) variations, only the first of which must be removed. To address this issue, we propose Polyphony, an interactive transfer learning (ITL) framework, to complement biologists' knowledge with advanced computational methods. Polyphony is motivated and guided by domain experts' needs for a controllable, interactive, and algorithm-assisted annotation process, identified through interviews wi

SUBMITTER: Cheng F 

PROVIDER: S-EPMC10039961 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature