Evidence map›Paper›PMID 36700103›Full record

ArticleBioinformatics advances2021

Aquila_stLFR: diploid genome assembly based structural variant calling package for stLFR linked-reads.

Yichen Henry Liu, Griffin L Grubbs, Lu Zhang, Xiaodong Fang, David L Dill, Arend Sidow, Xin Zhou

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Article in Bioinformatics advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. The Bioinformatic Applications of Hi-C and Linked Reads.Genomics, proteomics & bioinformatics · 2024
    Review
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  5. Article
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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yichen Henry LiuDepartment of Computer Science, Vanderbilt University, Nashville, TN 37235, USA.
Griffin L GrubbsDepartment of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Lu ZhangDepartment of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
Xiaodong FangBGI Tech, BGI Genomics, Shenzhen 518083, China.
David L DillDepartment of Computer Science, Stanford University, Stanford, CA 94305, USA.
Arend SidowDepartment of Pathology, Stanford University, Stanford, CA 94305, USA.
Xin ZhouDepartment of Computer Science, Vanderbilt University, Nashville, TN 37235, USA.ORCID https://orcid.org/0000-0003-4015-4787

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: Identifying structural variants (SVs) is critical in health and disease, however, detecting them remains a challenge. Several linked-read sequencing technologies, including 10X Genomics, TELL-Seq and single tube long fragment read (stLFR), have been recently developed as cost-effective approaches to reconstruct multi-megabase haplotypes (phase blocks) from sequence data of a single sample. These technologies provide an optimal sequencing platform to characterize SVs, though few computational algorithms can utilize them. Thus, we developed Aquila_stLFR, an approach that resolves SVs through haplotype-based assembly of stLFR linked-reads. Results: Aquila_stLFR first partitions long fragment reads into two haplotype-specific blocks with the assistance of the high-quality reference genome, by taking advantage of the potential phasing ability of the linked-read itself. Each haplotype is then assembled independently, to achieve a complete diploid assembly to finally reconstruct the genome-wide SVs. We benchmarked Aquila_stLFR on a well-studied sample, NA24385, and showed Aquila_stLFR can detect medium to large size deletions (50 bp-10 kb) with high sensitivity and medium-size insertions (50 bp-1 kb) with high specificity. Availability and implementation: Source code and documentation are available on https://github.com/maiziex/Aquila_stLFR. Supplementary information: Supplementary data are available at

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PMID36700103
PMCPMC9710574

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.