Evidence map›Paper›PMID 40918065›Full record

ArticleNAR genomics and bioinformatics2025

A systematic analysis of contemporary whole exome sequencing capture kits to optimise high-coverage capture of CCDS regions.

Fernando Vázquez López, James J Ashton, Guo Cheng, Sarah Ennis

Abstract readComparative Study
In one paragraph

Article in NAR genomics and bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

4 authors.

Fernando Vázquez LópezDepartment of Human Genetics and Genomic Medicine, University of Southampton, Southampton, SO16 6YD, UK.ORCID https://orcid.org/0009-0007-2974-9292
James J AshtonDepartment of Human Genetics and Genomic Medicine, University of Southampton, Southampton, SO16 6YD, UK.
Guo ChengDepartment of Human Genetics and Genomic Medicine, University of Southampton, Southampton, SO16 6YD, UK.
Sarah EnnisDepartment of Human Genetics and Genomic Medicine, University of Southampton, Southampton, SO16 6YD, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole exome sequencing (WES) is a well-established tool for clinical diagnostics, is more cost-effective and faster to analyse than whole genome sequencing and has been implemented to uplift diagnostic rates in human disease. However, challenges remain to achieve comprehensive and uniform coverage of targets, and high sensitivity and specificity. Differences in genomic target regions and exome capture mechanism between kits may lead to differences in overall coverage uniformity and capture efficiency. Here, we analyse the efficiency of a range of off-the-shelf exome sequencing (ES) kits in capturing their reported targets and the consensus coding sequence (CCDS) regions. Our results show Twist Custom Exome, Twist Human Comprehensive Exome, and Roche KAPA HyperExome V1 perform particularly well at capturing their target regions at 10X and 20X coverage and achieve the highest capture efficiency of CCDS regions upon read downsampling. This was the case despite both Twist kits targeting less than 37Mb in the genome. Our analysis highlights the impact of kit target design on capture efficiency in WES, with kit target size and uniformity of coverage impacting the capture efficiency of CCDS regions. This benchmark will help researchers to make an informed decision based on their needs.

Indexed as

Consensus SequenceExome SequencingReagent Kits, DiagnosticExomeGenome, HumanHumansReagent Kits, Diagnostic

Identifiers

PMID40918065
PMCPMC12408908

What OpenQuestion holds

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LicenceCC BY
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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.