Comparative analysis of methodologies for detecting extrachromosomal circular DNA

Extrachromosomal circular DNA (eccDNA) is crucial in oncogene amplification, gene transcription regulation, and intratumor heterogeneity. While various analysis pipelines and experimental methods have been developed for eccDNA identification, their detection efficiencies have not been systematically assessed. To address this, we evaluate the performance of 7 analysis pipelines using seven simulated datasets, in terms of accuracy, identity, duplication rate, and computational resource consumption. We also compare the eccDNA detection efficiency of 7 experimental methods through twenty-one real sequencing datasets. Here, we show that Circle-Map and Circle_finder (bwa-mem-samblaster) outperform the other short-read pipelines. However, Circle_finder (bwa-mem-samblaster) exhibits notable redundancy in its outcomes. CReSIL is the most effective pipeline for eccDNA detection in long-read sequencing data at depths higher than 10X. Moreover, long-read sequencing-based Circle-Seq shows superior efficiency in detecting copy number-amplified eccDNA over 10 kb in length. These results offer valuable insights for researchers in choosing the suitable methods for eccDNA research.

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Publication Details

Journal
Nature Communications
Published
2024-10-24
DOI
https://doi.org/10.1038/s41467-024-53496-8
Citations
20
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
5.70

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article

Comparative analysis of methodologies for detecting extrachromosomal circular DNA

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20 citations
Nature Communications
Cancer Genomics and Diagnostics
5.70
article

Comparative analysis of methodologies for detecting extrachromosomal circular DNA

Xiaolian Gao, Meifang Tang, Kun Qu, Chuang Guo, Shouzhen Li, Chen Jiang, Songwen Luo, Jingwen Fang, Ke Liu, Yanbing Hou, Nianping Liu
article en
20 citations

Abstract

Extrachromosomal circular DNA (eccDNA) is crucial in oncogene amplification, gene transcription regulation, and intratumor heterogeneity. While various analysis pipelines and experimental methods have been developed for eccDNA identification, their detection efficiencies have not been systematically assessed. To address this, we evaluate the performance of 7 analysis pipelines using seven simulated datasets, in terms of accuracy, identity, duplication rate, and computational resource consumption. We also compare the eccDNA detection efficiency of 7 experimental methods through twenty-one real sequencing datasets. Here, we show that Circle-Map and Circle_finder (bwa-mem-samblaster) outperform the other short-read pipelines. However, Circle_finder (bwa-mem-samblaster) exhibits notable redundancy in its outcomes. CReSIL is the most effective pipeline for eccDNA detection in long-read sequencing data at depths higher than 10X. Moreover, long-read sequencing-based Circle-Seq shows superior efficiency in detecting copy number-amplified eccDNA over 10 kb in length. These results offer valuable insights for researchers in choosing the suitable methods for eccDNA research.

Nature CommunicationsVol. 15(1)
University of Science and Technology of China (CN), Bengbu Medical College (CN), Suzhou University of Science and Technology (CN), National Science Centre (PL), The First People's Hospital of Xiaoshan District, Hangzhou (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, University of Science and Technology of China, National Institutes of Health, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 3%
Cancer Genomics and Diagnostics
5.70
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