Abstract
While aiming to determine orientations and orders of fragmented contigs, scaffolding is an essential step of assembly pipelines and can make assembly results more complete. Most existing scaffolding tools adopt the scaffold graph approach. However, constructing an accurate scaffold graph is still a challenge task. Removing potential false relationships is a key to achieve a better scaffolding performance, while most scaffolding approaches neglect the impacts of uneven sequencing depth that may cause more sequencing errors, and finally result in many false relationships. In this paper, we present a new scaffolding method LSLS (Loose-Strict-Loose Scaffolding), which is based on path extension. LSLS uses different strategies to extend paths, which can be more adaptive to different sequencing depths. For the problem of multiple paths, we designed a score function, which is based on the distribution of read pairs, to evaluate the reliability of path candidates and extend them with the paths which have the highest score. Besides, LSLS contains a new gap estimation method, which can estimate gap sizes more precisely. The experiment results on the two standard datasets show that LSLS can get better performance.
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Li, M. et al. (2017). LSLS: A Novel Scaffolding Method Based on Path Extension. In: Huang, DS., Jo, KH., Figueroa-GarcÃa, J. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science(), vol 10362. Springer, Cham. https://doi.org/10.1007/978-3-319-63312-1_38
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DOI: https://doi.org/10.1007/978-3-319-63312-1_38
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