Evidence map›Paper›PMID 36968613›Full record

ArticlePrecision clinical medicine2023

CAS Array: design and assessment of a genotyping array for Chinese biobanking.

Zijian Tian, Fei Chen, Jing Wang, Benrui Wu, Jian Shao, Ziqing Liu, Li Zheng, You Wang, Tao Xu, Kaixin Zhou

Open access · diamondFull text read
In one paragraph

Article in Precision clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
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

10 citing papers in PubMed, 14 citations in OpenAlex.

  1. Novel immune-related susceptibility loci associated with pediatric steroid-sensitive nephrotic syndrome identified by a transethnic genome-wide association study.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2026
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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

10 authors at 3 institutions in 1 country.

Zijian TianNational Laboratory of Biomacromolecules, Institute of Biophysics Chinese Academy of Sciences, Beijing 100101, China.ORCID https://orcid.org/0000-0002-2182-5381
Fei ChenCollege of Life Sciences, University of the Chinese Academy of Sciences, Beijing 10140, China.
Jing WangCollege of Life Sciences, University of the Chinese Academy of Sciences, Beijing 10140, China.
Benrui WuNational Laboratory of Biomacromolecules, Institute of Biophysics Chinese Academy of Sciences, Beijing 100101, China.
Jian ShaoDepartment of Mathematics and Interdisciplinary, Guangzhou Laboratory, Guangzhou 510005, China.
Ziqing LiuCollege of Life Sciences, University of the Chinese Academy of Sciences, Beijing 10140, China.
Li ZhengNational Laboratory of Biomacromolecules, Institute of Biophysics Chinese Academy of Sciences, Beijing 100101, China.
You WangNational Laboratory of Biomacromolecules, Institute of Biophysics Chinese Academy of Sciences, Beijing 100101, China.
Tao XuNational Laboratory of Biomacromolecules, Institute of Biophysics Chinese Academy of Sciences, Beijing 100101, China.
Kaixin ZhouCollege of Life Sciences, University of the Chinese Academy of Sciences, Beijing 10140, China.
Chinese Academy of Sciences · CNUniversity of Chinese Academy of Sciences · CNGuangzhou Experimental Station · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chronic diseases are becoming a critical challenge to the aging Chinese population. Biobanks with extensive genomic and environmental data offer opportunities to elucidate the complex gene-environment interactions underlying their aetiology. Genome-wide genotyping array remains an efficient approach for large-scale genomic data collection. However, most commercial arrays have reduced performance for biobanking in the Chinese population. Materials and methods: Deep whole-genome sequencing data from 2 641 Chinese individuals were used as a reference to develop the CAS array, a custom-designed genotyping array for precision medicine. Evaluation of the array was performed by comparing data from 384 individuals assayed both by the array and whole-genome sequencing. Validation of its mitochondrial copy number estimating capacity was conducted by examining its association with established covariates among 10 162 Chinese elderly. Results: The CAS Array adopts the proven Axiom technology and is restricted to 652 429 single-nucleotide polymorphism (SNP) markers. Its call rate of 99.79% and concordance rate of 99.89% are both higher than for commercial arrays. Its imputation-based genome coverage reached 98.3% for common SNPs and 63.0% for low-frequency SNPs, both comparable to commercial arrays with larger SNP capacity. After validating its mitochondrial copy number estimates, we developed a publicly available software tool to facilitate the array utility. Conclusion: Based on recent advances in genomic science, we designed and implemented a high-throughput and low-cost genotyping array. It is more cost-effective than commercial arrays for large-scale Chinese biobanking.

Indexed as

chronic diseasegenotypingmitochondrial copy numberprecision medicinesingle-nucleotide polymorphism (SNP)SNP array

Identifiers

PMID36968613
PMCPMC10031742
OpenAlexW4321605014

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.