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Updated: Feb 26, 2026
Genome-wide Purification of Extrachromosomal Circular DNA from Eukaryotic Cells
Published on: April 4, 2016
Análisis comparativo de herramientas de eccDNA y circRNA muestra una mayor precisión de la combinación de
Aitor Zabala1, Alex M Ascensión1, Iñigo Prada-Luengo2,3
1Group of Neuroimmunology, Biogipuzkoa Health Research Institute, San Sebastián, Spain.
Introduction:
Circular nucleic acids such as extrachromosomal circular DNA (eccDNA) and circular RNA (circRNA) are increasingly recognized for their biological relevance and potential as biomarkers in disease contexts. Despite their growing importance, their detection remains challenging due to tool-specific biases, limited validation frameworks, and high variability in performance across datasets.
Methods:
We benchmarked 10 circle detection tools across diverse conditions using both simulated and biological datasets. Our evaluation included classical performance metrics and a novel internal measure of read distribution symmetry (ΔCJ) to assess circle prediction confidence. We explored the impact of sequencing protocols, filtering strategies, and combined tool consensus.
Results:
We found that detection accuracy was highly influenced by sequencing depth, alignment algorithm, and experimental enrichment protocols. ΔCJ proved effective in flagging potential false positive circles, showing improved accuracy of Intersect (circles detected by all tools) and Rosette (circles detected by ≥2 tools) combinations.
Discussion:
This study offers a broad evaluation of circular detection tools, suggesting that the combination of ≥ 3 tools is necessary for a correct prediction. These insights will inform future experimental design and data analysis pipelines in both experimental and clinical settings.
