Evidence map›Paper›PMID 33849535›Full record

ArticleBMC medical genomics2021

Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders.

Yan Sun, Fengxia Liu, Chunna Fan, Yaoshen Wang, Lijie Song, Zhonghai Fang, Rui Han, Zhonghua Wang, Xiaodan Wang, Ziying Yang and 10 more

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
6.8field-weighted citation impact, top 3% 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

23 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

20 authors at 2 institutions in 1 country.

Yan Sun *BGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Fengxia Liu *Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Chunna Fan *Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Yaoshen Wang *Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Lijie SongTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Zhonghai FangTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Rui HanTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Zhonghua WangTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Xiaodan WangTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Ziying YangTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Zhenpeng XuBGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Jiguang PengBGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Chaonan ShiTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Hongyun ZhangBGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Wei DongBGI-Beijing Clinical Laboratories, BGI-Shenzhen, Beijing, 101300, China.
Hui HuangBGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Yun LiBGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Yanqun LeTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China.
Jun SunTianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, 300308, China. sunjun@bgi.com.
Zhiyu PengBGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China. pengzhiyu@bgi.com.ORCID 0000-0003-2349-750X
BGI Group (China) · CNTianjin Medical University · CN

Funding

Beijing Municipal Science & Technology Commission Z181100001918013Special Foundation for High-level Talents of Guangdong 2016TX03R171
6 · The paper itself

Abstract

backgroundDue to its reduced cost and incomparable advantages, WGS is likely to lead to changes in clinical diagnosis of rare and undiagnosed diseases. However, the sensitivity and breadth of coverage of clinical WGS as a diagnostic test for genetic disorders has not been fully evaluated.

methodsHere, the performance of WGS in NA12878, the YH cell line, and the Chinese trios were measured by assessing their sensitivity, PPV, depth and breadth of coverage using MGISEQ-2000. We also compared the performance of WES and WGS using NA12878. The sensitivity and PPV were tested using the family-based trio design for the Chinese trios. We further developed a systematic WGS pipeline for the analysis of 8 clinical cases.

resultsIn general, the sensitivity and PPV for SNV/indel detection increased with mean depth and reached a plateau at an ~ 40X mean depth using down-sampling samples of NA12878. With a mean depth of 40X, the sensitivity of homozygous and heterozygous SNPs of NA12878 was > 99.25% and > 99.50%, respectively, and the PPV was 99.97% and 98.96%. Homozygous and heterozygous indels showed lower sensitivity and PPV. The sensitivity and PPV were still not 100% even with a mean depth of ~ 150X. We also observed a substantial variation in the sensitivity of CNV detection across different tools, especially in CNVs with a size less than 1 kb. In general, the breadth of coverage for disease-associated genes and CNVs increased with mean depth. The sensitivity and coverage of WGS (~ 40X) was better than WES (~ 120X). Among the Chinese trios with an ~ 40X mean depth, the sensitivity among offspring was > 99.48% and > 96.36% for SNP and indel detection, and the PPVs were 99.86% and 97.93%. All 12 previously validated variants in the 8 clinical cases were successfully detected using our WGS pipeline.

conclusionsThe current standard of a mean depth of 40X may be sufficient for SNV/indel detection and identification of most CNVs. It would be advisable for clinical scientists to determine the range of sensitivity and PPV for different classes of variants for a particular WGS pipeline, which would be useful when interpreting and delivering clinical reports.

Indexed as

Genetic Diseases, InbornDiagnostic Tests, RoutineFemaleGenetic TestingGenome, HumanHumansINDEL MutationMalePolymorphism, Single NucleotideSensitivity and SpecificityWhole Genome SequencingClinical diagnosisCNVDP and breadth of coverageSensitivity and PPVWGS

Identifiers

PMID33849535
PMCPMC8045368
OpenAlexW3153630498

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.