Evidence map›Paper›PMID 39769013›Full record

ArticleInternational journal of molecular sciences2024

Enhancing Clinical Applications by Evaluation of Sensitivity and Specificity in Whole Exome Sequencing.

Youngbeen Moon, Chung Hwan Hong, Young-Ho Kim, Jong-Kwang Kim, Seo-Hyeon Ye, Eun-Kyung Kang, Hye Won Choi, Hyeri Cho, Hana Choi, Dong-Eun Lee and 5 more

Abstract read
In one paragraph

Article in International journal of molecular sciences, 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

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

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

15 authors.

Youngbeen MoonBioinformatics Analysis Team, Research Core Center, Research Institute, National Cancer Center, Goyang 10408, Gyeonggi-do, Republic of Korea.
Chung Hwan HongCancer Molecular Biology Branch, Division of Cancer Biology, Research Institute, National Cancer Center, Goyang 10408, Gyeonggi-do, Republic of Korea.ORCID 0000-0002-2361-1635
Young-Ho KimDiagnostic and Therapeutics Technology Branch, Division of Technology Convergence, Research Institute, National Cancer Center, Goyang 10408, Gyeonggi-do, Republic of Korea.ORCID 0000-0002-6993-0906
Jong-Kwang KimBioinformatics Analysis Team, Research Core Center, Research Institute, National Cancer Center, Goyang 10408, Gyeonggi-do, Republic of Korea.ORCID 0000-0001-9290-0820
Seo-Hyeon YeCancer Molecular Biology Branch, Division of Cancer Biology, Research Institute, National Cancer Center, Goyang 10408, Gyeonggi-do, Republic of Korea.
Eun-Kyung KangCancer Molecular Biology Branch, Division of Cancer Biology, Research Institute, National Cancer Center, Goyang 10408, Gyeonggi-do, Republic of Korea.
Hye Won ChoiCancer Molecular Biology Branch, Division of Cancer Biology, Research Institute, National Cancer Center, Goyang 10408, Gyeonggi-do, Republic of Korea.
Hyeri ChoDiagnostic and Therapeutics Technology Branch, Division of Technology Convergence, Research Institute, National Cancer Center, Goyang 10408, Gyeonggi-do, Republic of Korea.
Hana ChoiDiagnostic and Therapeutics Technology Branch, Division of Technology Convergence, Research Institute, National Cancer Center, Goyang 10408, Gyeonggi-do, Republic of Korea.
Dong-Eun LeeBiostatistics Collaboration Team, Research Core Center, Research Institute, National Cancer Center, Goyang 10408, Gyeonggi-do, Republic of Korea.
Yongdoo ChoiDivision of Technology Convergence, National Cancer Center, 323 Ilsan-ro, Goyang 10408, Gyeonggi-do, Republic of Korea.
Tae-Min KimDepartment of Medical Informatics and Cancer Research Institute, College of Medicine, The Catholic University of Korea, Seoul 06591, Gyeonggi-do, Republic of Korea.
Seong Gu HeoDana Farber Cancer Institute, Boston, MA 02215, USA.
Namshik HanMilner Therapeutics Institute, University of Cambridge, Cambridge CB2 0AW, UK.
Kyeong-Man HongBioinformatics Analysis Team, Research Core Center, Research Institute, National Cancer Center, Goyang 10408, Gyeonggi-do, Republic of Korea.

Funding

National Cancer Center, Korea 2210700
6 · The paper itself

Abstract

The cost-effectiveness of whole exome sequencing (WES) remains controversial due to variant call variability, necessitating sensitivity and specificity evaluation. WES was performed by three companies (AA, BB, and CC) using reference standards composed of DNA from hydatidiform mole and individual blood at various ratios. Sensitivity was assessed by the detection rate of null-homozygote (N-H) alleles at expected variant allelic fractions, while false positive (FP) errors were counted for unexpected alleles. Sensitivity was approximately 20% for in-house results from BB and CC and around 5% for AA. Dynamic Read Analysis for GENomics (DRAGEN) analyses identified 1.34 to 1.71 times more variants, detecting over 96% of in-house variants, with sensitivity for common variants increasing to 5%. In-house FP errors varied significantly among companies (up to 13.97 times), while DRAGEN minimized this variation. Despite DRAGEN showing higher FP errors for BB and CC, the increased sensitivity highlights the importance of effective bioinformatic conditions. We also assessed the potential effects of target enrichment and proposed optimal cutoff values for the read depth and variant allele fraction in WES. Optimizing bioinformatic analysis based on sensitivity and specificity from reference standards can enhance variant detection and improve the clinical utility of WES.

Indexed as

Exome SequencingSensitivity and SpecificityAllelesComputational BiologyExomeFemaleHigh-Throughput Nucleotide SequencingHumansHydatidiform MolePregnancycancerfalse negative errorfalse positive errormutationquality controlreference standardWES

Identifiers

PMID39769013
PMCPMC11678496

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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.