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Updated: Jul 21, 2025

ATAC-Seq Optimization for Cancer Epigenetics Research
Published on: June 30, 2022
AtacAnnoR: a reference-based annotation tool for single cell ATAC-seq data
Lejin Tian1, Yunxiao Xie1, Zhaobin Xie1
1State Key Laboratory of Genetic Engineering, Department of Computational Biology, School of Life Sciences, Fudan University, Shanghai, China.
Abstract:
Here, we present AtacAnnoR, a two-round annotation method for scATAC-seq data using well-annotated scRNA-seq data as reference. We evaluate AtacAnnoR's performance against six competing methods on 11 benchmark datasets. Our results show that AtacAnnoR achieves the highest mean accuracy and the highest mean balanced accuracy and performs particularly well when unpaired scRNA-seq data are used as the reference. Furthermore, AtacAnnoR implements a 'Combine and Discard' strategy to further improve annotation accuracy when annotations of multiple references are available. AtacAnnoR has been implemented in an R package and can be directly integrated into currently popular scATAC-seq analysis pipelines.
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