Sceptic: pseudotime analysis for time-series single-cell sequencing and imaging data.

Abstract

Several computational methods have been developed to construct single-cell pseudotime embeddings for extracting the temporal order of transcriptional cell states from time-series scRNA-seq datasets. However, existing methods suffer from low predictive accuracy, and this problem becomes even worse when we try to generalize to other data types such as scATAC-seq or microscopy images. To address this problem, we propose Sceptic, a support vector machine model for supervised pseudotime analysis. We demonstrate that Sceptic achieves significantly improved prediction power relative to state-of-the-art methods, and that Sceptic can be applied to a variety of single-cell data types, including single-nucleus image data.

Authors

Li G  •  Kim HJ  •  Pendyala S  •  Zhang R  •  Vert JP  •  Disteche CM  •  Deng X  •  Fowler DM  •  Noble WS

Link

https://www.ncbi.nlm.nih.gov/pubmed/40676652