Literature DB >> 34648021

scMRMA: single cell multiresolution marker-based annotation.

Jia Li1,2, Quanhu Sheng1,2, Yu Shyr1,2, Qi Liu1,2.   

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.
© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2022        PMID: 34648021      PMCID: PMC8789072          DOI: 10.1093/nar/gkab931

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   19.160


  41 in total

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6.  Clonal replacement of tumor-specific T cells following PD-1 blockade.

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Journal:  Nat Med       Date:  2019-07-29       Impact factor: 53.440

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8.  CellO: comprehensive and hierarchical cell type classification of human cells with the Cell Ontology.

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9.  Evaluation of methods to assign cell type labels to cell clusters from single-cell RNA-sequencing data.

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  1 in total

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  1 in total

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