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Efficient iterative Hi-C scaffolder based on N-best neighbors

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Guan, Dengfeng 
McCarthy, Shane A. 
Ning, Zemin 
Wang, Guohua 
Wang, Yadong 


Abstract: Background: Efficient and effective genome scaffolding tools are still in high demand for generating reference-quality assemblies. While long read data itself is unlikely to create a chromosome-scale assembly for most eukaryotic species, the inexpensive Hi-C sequencing technology, capable of capturing the chromosomal profile of a genome, is now widely used to complete the task. However, the existing Hi-C based scaffolding tools either require a priori chromosome number as input, or lack the ability to build highly continuous scaffolds. Results: We design and develop a novel Hi-C based scaffolding tool, pin_hic, which takes advantage of contact information from Hi-C reads to construct a scaffolding graph iteratively based on N-best neighbors of contigs. Subsequent to scaffolding, it identifies potential misjoins and breaks them to keep the scaffolding accuracy. Through our tests on three long read based de novo assemblies from three different species, we demonstrate that pin_hic is more efficient than current standard state-of-art tools, and it can generate much more continuous scaffolds, while achieving a higher or comparable accuracy. Conclusions: Pin_hic is an efficient Hi-C based scaffolding tool, which can be useful for building chromosome-scale assemblies. As many sequencing projects have been launched in the recent years, we believe pin_hic has potential to be applied in these projects and makes a meaningful contribution.



Software, Hi-C, Scaffolding

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BMC Bioinformatics

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BioMed Central
National Natural Science Foundation of China (2017YFC0907503, 2018YFC0910504, 2017YFC1201201)
Wellcome Trust (WT207492)