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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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Abstract

Abstract

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.
Keywords:
COPY-NUMBER VARIATION
ALGORITHM
GRAPHS

Journal

Nature Methods cover
Nature Methods
IF:
32.1
Papers:
7.2K
Citations:
12.7W

Organization

N
national institutes of health (nih) - usa
Scholars:
10.3W
Papers: 8.2W
Citations: 111
I
indian institute of science (iisc) - bangalore
Scholars:
1.4W
Papers: 1.4W
Citations: 11
N
nih national human genome research institute (nhgri)
Scholars:
2.8K
Papers: 1.9K
Citations: 3
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Cited Papers

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