Abstract
Whole genome sequencing enabled the exploration of genomic structural variants (SVs). However, there is still a lack of software in this field to integrate SVs and functional element database. Here, we propose SVHot, an automated software that detect and annotate SV hotspots. In terms of SV’s hotspot detection, we applies segmentation algorithms to hotspot detection. This work improves the hotspot detection capabilities. In terms of hotspot analysis, we proposes a hotspot annotation algorithm based on cancer types to overcome the shortcomings of existing interval annotation software. Then we develop an annotation database which conclude data of 31 cancer types. SVHots is an integrative software to detect and annotate SVs’ hotspot.
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Acknowledgement
This work was supported by the National Natural Science Foundation of China (Grant No. 41877305, 41705097).
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Lv, X., Liu, S., Jiang, S. (2022). Design and Implementation of Cancer Structural Variants Hotspot Detection and Annotation Software. In: Li, X. (eds) Advances in Intelligent Automation and Soft Computing. IASC 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 80. Springer, Cham. https://doi.org/10.1007/978-3-030-81007-8_67
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DOI: https://doi.org/10.1007/978-3-030-81007-8_67
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