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Long-read mapping to repetitive reference sequences using Winnowmap2

delete2022-04-01
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OA
AI
C
Chirag Jain *
A
Arang Rhie
N
Nancy F. Hansen
S
Sergey Koren
A
Adam M. Phillippy
DOI:10.1038/s41592-022-01457-8delete
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摘要

摘要

En 中文
Approximately 5-10% of the human genome remains inaccessible due to the presence of repetitive sequences such as segmental duplications and tandem repeat arrays. We show that existing long-read mappers often yield incorrect alignments and variant calls within long, near-identical repeats, as they remain vulnerable to allelic bias. In the presence of a nonreference allele within a repeat, a read sampled from that region could be mapped to an incorrect repeat copy. To address this limitation, we developed a new long-read mapping method, Winnowmap2, by using minimal confidently alignable substrings. Winnowmap2 computes each read mapping through a collection of confident subalignments. This approach is more tolerant of structural variation and more sensitive to paralog-specific variants within repeats. Our experiments highlight that Winnowmap2 successfully addresses the issue of allelic bias, enabling more accurate downstream variant calls in repetitive sequences.
Keyword:
COPY-NUMBER VARIATION
ALGORITHM
GRAPHS

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Nature Methods 封面图
Nature Methods
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32.1
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被引数:
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national institutes of health (nih) - usa
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indian institute of science (iisc) - bangalore
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nih national human genome research institute (nhgri)
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