Evidence map›Paper›PMID 37020281›Full record

ArticleBMC medical genomics2023

Test development, optimization and validation of a WGS pipeline for genetic disorders.

Ziying Yang, Xu Yang, Yan Sun, Yaoshen Wang, Lijie Song, Zhihong Qiao, Zhonghai Fang, Zhonghua Wang, Lipei Liu, Yunmei Chen and 9 more

Abstract read
In one paragraph

Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

19 authors.

Ziying Yang *College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
Xu Yang *Department of Paediatrics, Pu'er People's Hospital, Pu'er, 665000, China.
Yan Sun *BGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Yaoshen Wang *Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Lijie Song *Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Zhihong Qiao *Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Zhonghai FangTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Zhonghua WangTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Lipei LiuTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Yunmei ChenTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Saiying YanTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Xueqin GuoBGI-Wuhan Clinical Laboratories, BGI-Shenzhen, Wuhan, 430074, China.
Junqing ZhangTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Chunna FanTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Fengxia LiuTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Zhiyu PengBGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Huanhuan PengClinical Laboratory of BGI Health, BGI-Shenzhen, Shenzhen, 518083, China.
Jun SunTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China. sunjun@bgi.com.
Wei ChenPu'er People's Hospital, Pu'er, 665000, China. kwwgc@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith advances in massive parallel sequencing (MPS) technology, whole-genome sequencing (WGS) has gradually evolved into the first-tier diagnostic test for genetic disorders. However, deployment practice and pipeline testing for clinical WGS are lacking.

methodsIn this study, we introduced a whole WGS pipeline for genetic disorders, which included the entire process from obtaining a sample to clinical reporting. All samples that underwent WGS were constructed using polymerase chain reaction (PCR)-free library preparation protocols and sequenced on the MGISEQ-2000 platform. Bioinformatics pipelines were developed for the simultaneous detection of various types of variants, including single nucleotide variants (SNVs), insertions and deletions (indels), copy number variants (CNVs) and balanced rearrangements, mitochondrial (MT) variants, and other complex variants such as repeat expansion, pseudogenes and absence of heterozygosity (AOH). A semiautomatic pipeline was developed for the interpretation of potential SNVs and CNVs. Forty-five samples (including 14 positive commercially available samples, 23 laboratory-held positive cell lines and 8 clinical cases) with known variants were used to validate the whole pipeline.

resultsIn this study, a whole WGS pipeline for genetic disorders was developed and optimized. Forty-five samples with known variants (6 with SNVs and Indels, 3 with MT variants, 5 with aneuploidies, 1 with triploidy, 23 with CNVs, 5 with balanced rearrangements, 2 with repeat expansions, 1 with AOHs, and 1 with exon 7-8 deletion of SMN1 gene) validated the effectiveness of our pipeline.

conclusionsThis study has been piloted in test development, optimization, and validation of the WGS pipeline for genetic disorders. A set of best practices were recommended using our pipeline, along with a dataset of positive samples for benchmarking.

Indexed as

INDEL MutationBase SequenceWhole Genome SequencingBioinformatics pipelinesClinical diagnosisGenetic disordersWhole genome sequencing

Identifiers

PMID37020281
PMCPMC10077614

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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.