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De novo annotation of centromere with centroAnno

Junhai QiiD, Junchi Ma, Renmin HaniD, Zheng Han, Ting YuiD, Guojun Li

Abstract

Accurate centromere annotation is essential for elucidating chromosomal stability, gene regulation, and the complexities of genome architecture. However, existing methods are often constrained by their dependence on prior knowledge and their limited applicability across diverse genomic contexts. In this study, we present Centromere Annotator (centroAnno), a novel de novo algorithm tailored for the precise annotation of centromeres and tandem repeats directly within complex genomes, assemblies, centromeric sequences, or raw sequencing data. Through extensive evaluations on both simulated and real-world datasets, centroAnno consistently outperforms existing tools in annotation accuracy. Additionally, centroAnno significantly enhances efficiency, achieving annotation speeds 12 to 44 times faster than other methods when applied to human centromeric regions.

02 /Specification & Classification

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