scMRMA: single cell multiresolution marker-based annotation

Jia Li, Quanhu Sheng, Yu Shyr, Qi Liu

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Single-cell RNA sequencing has become a powerful tool for identifying and characterizing cellular heterogeneity. One essential step to understanding cellular heterogeneity is determining cell identities. The widely used strategy predicts identities by projecting cells or cell clusters unidirectionally against a reference to find the best match. Here, we develop a bidirectional method, scMRMA, where a hierarchical reference guides iterative clustering and deep annotation with enhanced resolutions. Taking full advantage of the reference, scMRMA greatly improves the annotation accuracy. scMRMA achieved better performance than existing methods in four benchmark datasets and successfully revealed the expansion of CD8 T cell populations in squamous cell carcinoma after anti-PD-1 treatment.

Original languageEnglish
Pages (from-to)E7
JournalNucleic acids research
Volume50
Issue number2
DOIs
Publication statusPublished - 2022 Jan 25

All Science Journal Classification (ASJC) codes

  • Genetics

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