Evidence map›Paper›PMID 39378130›Full record

ArticleGenomics, proteomics & bioinformatics2024

Enhancing Variant Calling in Whole-exome Sequencing Data Using Population-matched Reference Genomes.

Shuming Guo, Zhuo Huang, Yanming Zhang, Yukun He, Xiangju Chen, Wenjuan Wang, Lansheng Li, Yu Kang, Zhancheng Gao, Jun Yu and 2 more

Abstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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

12 authors.

Shuming GuoLinfen Clinical Medicine Research Center, LinFen Central Hospital, LinFen 041000, China.ORCID 0009-0001-7931-3725
Zhuo HuangChina National Center for Bioinformation, Beijing 100101, China.ORCID 0009-0005-1023-1560
Yanming ZhangLinfen Clinical Medicine Research Center, LinFen Central Hospital, LinFen 041000, China.ORCID 0009-0007-1480-1756
Yukun HeDepartment of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing 100044, China.ORCID 0000-0002-4164-2478
Xiangju ChenLinfen Clinical Medicine Research Center, LinFen Central Hospital, LinFen 041000, China.ORCID 0009-0005-7059-6350
Wenjuan WangLinfen Clinical Medicine Research Center, LinFen Central Hospital, LinFen 041000, China.ORCID 0009-0003-0444-379X
Lansheng LiLinfen Clinical Medicine Research Center, LinFen Central Hospital, LinFen 041000, China.ORCID 0009-0004-0689-8752
Yu KangChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0001-5196-0376
Zhancheng GaoDepartment of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing 100044, China.ORCID 0000-0001-7415-1416
Jun YuUniversity of Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0001-7599-2700
Zhenglin DuChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0003-2147-3475
Yanan ChuChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0002-9349-4307

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole-exome sequencing (WES) data are frequently used for cancer diagnosis and genome-wide association studies (GWAS), based on high-coverage read mapping, informative variant calling, and high-quality reference genomes. The center position of the currently used genome assembly, GRCh38, is now challenged by two newly published telomere-to-telomere (T2T) genomes, T2T-CHM13 and T2T-YAO, and it becomes urgent to have a comparative study to test population specificity using the three reference genomes based on real case WES data. Here, we report our analysis along this line for 19 tumor samples collected from Chinese patients. The primary comparison of the exon regions among the three references reveals that the sequences in up to ∼ 1% of target regions in T2T-YAO are widely diversified from GRCh38 and may lead to off-target in sequence capture. However, T2T-YAO still outperforms GRCh38 by obtaining 7.41% of more mapped reads. Due to more reliable read-mapping and closer phylogenetic relationship with the samples than GRCh38, T2T-YAO reduces half of variant calls of clinical significance which are mostly benign, while maintaining sensitivity in identifying pathogenic variants. T2T-YAO also outperforms T2T-CHM13 in reducing calls of Chinese-specific variants. Our findings highlight the critical need for employing population-specific reference genomes in genomic analysis to ensure accurate variant analysis and the significant benefits of tailoring these approaches to the unique genetic background of each ethnic group.

Indexed as

Exome SequencingGenome, HumanGenetic VariationHumansNeoplasmsPopulation-specific reference genomeT2T-YAOTumorVariant callingWhole-exome sequencing

Identifiers

PMID39378130
PMCPMC11687947

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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.