Evidence map›Paper›PMID 33662625›Full record

ArticleGenomics, proteomics & bioinformatics2022

Robust Benchmark Structural Variant Calls of An Asian Using State-of-the-art Long-read Sequencing Technologies.

Xiao Du, Lili Li, Fan Liang, Sanyang Liu, Wenxin Zhang, Shuai Sun, Yuhui Sun, Fei Fan, Linying Wang, Xinming Liang and 11 more

Abstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Xiao DuBGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China; State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen 518083, China.
Lili LiNational Institutes for food and drug Control (NIFDC), Beijing 10050, China.
Fan LiangGrandOmics Biosciences, Beijing 102200, China.
Sanyang LiuAnnoroad Gene Technology (Beijing) Co., Ltd., Beijing 102200, China.
Wenxin ZhangNational Institutes for food and drug Control (NIFDC), Beijing 10050, China.
Shuai SunBGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China; State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen 518083, China.
Yuhui SunBGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China.
Fei FanBGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China.
Linying WangBGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China.
Xinming LiangMGI, BGI-Shenzhen, Shenzhen 518083, China.
Weijin QiuMGI, BGI-Shenzhen, Shenzhen 518083, China.
Guangyi FanBGI-Qingdao, BGI-Shenzhen, Qingdao 266555, China; State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen 518083, China.
Ou WangBGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China.
Weifei YangAnnoroad Gene Technology (Beijing) Co., Ltd., Beijing 102200, China.
Jiezhong ZhangAnnoroad Gene Technology (Beijing) Co., Ltd., Beijing 102200, China.
Yuhui XiaoGrandOmics Biosciences, Beijing 102200, China.
Yang WangGrandOmics Biosciences, Beijing 102200, China.
Depeng WangGrandOmics Biosciences, Beijing 102200, China. Electronic address: wangdp@grandomics.com.
Shoufang QuNational Institutes for food and drug Control (NIFDC), Beijing 10050, China. Electronic address: qushoufang@nifdc.org.cn.
Fang ChenBGI-Shenzhen, Shenzhen 518083, China; MGI, BGI-Shenzhen, Shenzhen 518083, China. Electronic address: fangchen@genomics.cn.
Jie HuangNational Institutes for food and drug Control (NIFDC), Beijing 10050, China. Electronic address: jhuang5522@nifdc.org.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The importance of structural variants (SVs) for human phenotypes and diseases is now recognized. Although a variety of SV detection platforms and strategies that vary in sensitivity and specificity have been developed, few benchmarking procedures are available to confidently assess their performances in biological and clinical research. To facilitate the validation and application of these SV detection approaches, we established an Asian reference material by characterizing the genome of an Epstein-Barr virus (EBV)-immortalized B lymphocyte line along with identified benchmark regions and high-confidence SV calls. We established a high-confidence SV callset with 8938 SVs by integrating four alignment-based SV callers, including 109× Pacific Biosciences (PacBio) continuous long reads (CLRs), 22× PacBio circular consensus sequencing (CCS) reads, 104× Oxford Nanopore Technologies (ONT) long reads, and 114× Bionano optical mapping platform, and one de novo assembly-based SV caller using CCS reads. A total of 544 randomly selected SVs were validated by PCR amplification and Sanger sequencing, demonstrating the robustness of our SV calls. Combining trio-binning-based haplotype assemblies, we established an SV benchmark for identifying false negatives and false positives by constructing the continuous high-confidence regions (CHCRs), which covered 1.46 gigabase pairs (Gb) and 6882 SVs supported by at least one diploid haplotype assembly. Establishing high-confidence SV calls for a benchmark sample that has been characterized by multiple technologies provides a valuable resource for investigating SVs in human biology, disease, and clinical research.

Indexed as

BenchmarkingEpstein-Barr Virus InfectionsAsian PeopleHaplotypesHerpesvirus 4, HumanHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNAAsian benchmarkHaplotype-resolvedReference materialSanger validationStructural variation

Identifiers

PMID33662625
PMCPMC9510867

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Registered trials

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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.