Evidence map›Paper›PMID 38326393›Full record

ArticleNPJ genomic medicine2024

A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome.

Claude Bhérer, Robert Eveleigh, Katerina Trajanoska, Janick St-Cyr, Antoine Paccard, Praveen Nadukkalam Ravindran, Elizabeth Caron, Nimara Bader Asbah, Peyton McClelland, Clare Wei and 11 more

Abstract read
In one paragraph

Article in NPJ genomic medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 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

21 authors.

Claude BhérerDepartment of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montréal, Québec, Canada.ORCID http://orcid.org/0000-0002-2744-7246
Robert EveleighVictor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montréal, Québec, Canada.
Katerina TrajanoskaDepartment of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montréal, Québec, Canada.ORCID http://orcid.org/0000-0002-3792-4296
Janick St-CyrVictor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montréal, Québec, Canada.
Antoine PaccardVictor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montréal, Québec, Canada.
Praveen Nadukkalam RavindranVictor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montréal, Québec, Canada.
Elizabeth CaronVictor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montréal, Québec, Canada.
Nimara Bader AsbahDepartment of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montréal, Québec, Canada.
Peyton McClellandDepartment of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montréal, Québec, Canada.ORCID http://orcid.org/0009-0009-7671-8506
Clare WeiVictor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montréal, Québec, Canada.ORCID http://orcid.org/0009-0002-8739-4892
Iris BaumgartnerDivision of Angiology, Swiss Cardiovascular Center, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Marc SchindewolfDivision of Angiology, Swiss Cardiovascular Center, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Yvonne DöringDivision of Angiology, Swiss Cardiovascular Center, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Danielle PerleyVictor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montréal, Québec, Canada.
François LefebvreVictor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montréal, Québec, Canada.
Pierre LepageVictor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montréal, Québec, Canada.
Mathieu BourgeyMila - Quebec AI Institute, Montréal, Québec, Canada.ORCID http://orcid.org/0000-0002-8432-834X
Guillaume BourqueDepartment of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montréal, Québec, Canada.ORCID http://orcid.org/0000-0002-3933-9656
Jiannis RagoussisDepartment of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montréal, Québec, Canada.ORCID http://orcid.org/0000-0002-8515-0934
Vincent MooserDepartment of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montréal, Québec, Canada.
Daniel TaliunDepartment of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montréal, Québec, Canada. daniel.taliun@mcgill.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole genome sequencing (WGS) at high-depth (30X) allows the accurate discovery of variants in the coding and non-coding DNA regions and helps elucidate the genetic underpinnings of human health and diseases. Yet, due to the prohibitive cost of high-depth WGS, most large-scale genetic association studies use genotyping arrays or high-depth whole exome sequencing (WES). Here we propose a cost-effective method which we call "Whole Exome Genome Sequencing" (WEGS), that combines low-depth WGS and high-depth WES with up to 8 samples pooled and sequenced simultaneously (multiplexed). We experimentally assess the performance of WEGS with four different depth of coverage and sample multiplexing configurations. We show that the optimal WEGS configurations are 1.7-2.0 times cheaper than standard WES (no-plexing), 1.8-2.1 times cheaper than high-depth WGS, reach similar recall and precision rates in detecting coding variants as WES, and capture more population-specific variants in the rest of the genome that are difficult to recover when using genotype imputation methods. We apply WEGS to 862 patients with peripheral artery disease and show that it directly assesses more known disease-associated variants than a typical genotyping array and thousands of non-imputable variants per disease-associated locus.

Identifiers

PMID38326393
PMCPMC10850497

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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.