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- W4366998824 abstract "Abstract Deletions and tandem duplications are two major classes of structural variations. They frequently occur in highly repetitive regions, where existing methods fail to detect most of them. We previously introduced SurVIndel, an algorithm that tackled this issue by employing novel statistical methods and had improved sensitivity in repetitive regions. However, its precision was low. Here, we introduce SurVIndel2, an algorithm that uses a novel type of evidence (which we called hidden split reads) and also borrows and adapts the statistical approach of its predecessor. By combining these two approaches, SurVIndel2 is both more sensitive and more precise than any other method we tested." @default.
- W4366998824 created "2023-04-27" @default.
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- W4366998824 date "2023-04-25" @default.
- W4366998824 modified "2023-09-23" @default.
- W4366998824 title "SurVIndel2: improving local CNVs calling from next-generation sequencing using novel hidden information" @default.
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- W4366998824 doi "https://doi.org/10.1101/2023.04.23.538018" @default.
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