Evidence map›Paper›PMID 37870428›Full record

ArticleNucleic acids research2023

A high-resolution haplotype-resolved Reference panel constructed from the China Kadoorie Biobank Study.

Canqing Yu, Xianmei Lan, Ye Tao, Yu Guo, Dianjianyi Sun, Puyi Qian, Yuwen Zhou, Robin G Walters, Linxuan Li, Yunqing Zhu and 23 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2023. 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

33 authors.

Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.ORCID 0000-0002-0019-0014
Xianmei LanCollege of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0001-7240-3819
Ye TaoBGI Research, Shenzhen 518083, China.
Yu GuoNational Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China.
Dianjianyi SunDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Puyi QianChina National GeneBank, BGI, Shenzhen 518083, China.
Yuwen ZhouCollege of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
Robin G WaltersClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom.
Linxuan LiCollege of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
Yunqing ZhuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Jingyu ZengBGI Research, Shenzhen 518083, China.
Iona Y MillwoodClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom.
Ruidong GuoBGI Research, Shenzhen 518083, China.
Pei PeiCenter for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China.
Tao YangChina National GeneBank, BGI, Shenzhen 518083, China.
Huaidong DuClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom.ORCID 0000-0002-9814-0049
Fan YangChina National GeneBank, BGI, Shenzhen 518083, China.
Ling YangClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom.
Fangyi RenChina National GeneBank, BGI, Shenzhen 518083, China.
Yiping ChenClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom.
Fengzhen ChenChina National GeneBank, BGI, Shenzhen 518083, China.
Xiaosen JiangCollege of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
Zhiqiang YeChina National GeneBank, BGI, Shenzhen 518083, China.
Lanlan DaiChina National GeneBank, BGI, Shenzhen 518083, China.
Xiaofeng WeiChina National GeneBank, BGI, Shenzhen 518083, China.
Xun XuBGI Research, Shenzhen 518083, China.ORCID 0000-0002-5338-5173
Huanming YangBGI Research, Shenzhen 518083, China.
Jian WangBGI, Shenzhen 518083, China.
Zhengming ChenClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, United Kingdom.
Huanhuan ZhuBGI Research, Shenzhen 518083, China.
Jun LvCenter for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China.
Xin JinBGI Research, Shenzhen 518083, China.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.ORCID 0000-0001-5873-7089

Funding

Cancer Research UK 29186Medical Research Council MC_PC_14135Medical Research Council MC_UU_00017/1Wellcome TrustWellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

Precision medicine depends on high-accuracy individual-level genotype data. However, the whole-genome sequencing (WGS) is still not suitable for gigantic studies due to budget constraints. It is particularly important to construct highly accurate haplotype reference panel for genotype imputation. In this study, we used 10 000 samples with medium-depth WGS to construct a reference panel that we named the CKB reference panel. By imputing microarray datasets, it showed that the CKB panel outperformed compared panels in terms of both the number of well-imputed variants and imputation accuracy. In addition, we have completed the imputation of 100 706 microarrays with the CKB panel, and the after-imputed data is the hitherto largest whole genome data of the Chinese population. Furthermore, in the GWAS analysis of real phenotype height, the number of tested SNPs tripled and the number of significant SNPs doubled after imputation. Finally, we developed an online server for offering free genotype imputation service based on the CKB reference panel (https://db.cngb.org/imputation/). We believe that the CKB panel is of great value for imputing microarray or low-coverage genotype data of Chinese population, and potentially mixed populations. The imputation-completed 100 706 microarray data are enormous and precious resources of population genetic studies for complex traits and diseases.

Indexed as

Biological Specimen BanksGenomeChinaGenome-Wide Association StudyGenotypeHaplotypesHumansPolymorphism, Single Nucleotide

Identifiers

PMID37870428
PMCPMC10681741

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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.