Evidence map›Paper›PMID 38281971›Full record

ArticleNature communications2024

Utility of long-read sequencing for All of Us.

M Mahmoud, Y Huang, K Garimella, P A Audano, W Wan, N Prasad, R E Handsaker, S Hall, A Pionzio, M C Schatz and 4 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
97citing papers in PubMed, 1 pooled it
47.9field-weighted citation impact, top 1% 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

97 citing papers in PubMed, 1 synthesis or guideline pooled it, 94 citations in OpenAlex.

  1. Pooled it
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  10. Population-scale detection of methylation outliers from long-read genome sequencing.medRxiv : the preprint server for health sciences · 2026
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37 more citing papers are in PubMed but not listed here.

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

14 authors at 7 institutions in 1 country.

M MahmoudHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0002-2553-4231
Y HuangData Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA.
K GarimellaData Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA.
P A AudanoThe Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA.ORCID 0000-0002-5187-0415
W WanData Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA.
N PrasadDiscovery Life Sciences, Huntsville, AL, 35806, USA.
R E HandsakerDepartment of Genetics, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-3128-3547
S HallDiscovery Life Sciences, Huntsville, AL, 35806, USA.
A PionzioDiscovery Life Sciences, Huntsville, AL, 35806, USA.
M C SchatzDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-4118-4446
M E TalkowskiProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA.ORCID 0000-0003-2889-0992
E E EichlerDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.ORCID 0000-0002-8246-4014
S E LevyHudsonAlpha Institute for Biotechnology, Huntsville, AL, 35806, USA.ORCID 0000-0002-1369-5740
F J SedlazeckHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA. fritz.sedlazeck@bcm.edu.ORCID 0000-0001-6040-2691
Broad Institute · USLife Sciences Discovery Fund · USBaylor College of Medicine · USHoward Hughes Medical Institute · USHudsonAlpha Institute for Biotechnology · USJackson Laboratory · USJohns Hopkins University · US

Funding

Technology to Empower Changes in Health (TECH) Network Participant Technologies CenterU24OD023176 · OD · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2016 to 2022
$204.7M
Precision Medicine Initiative Cohort Program BiobankU24OD023121 · OD · MAYO CLINIC ROCHESTER · PI CEKANOVA, MARIA, CICEK, MINE · 2016 to 2024
$185.5M
The Baylor-Hopkins Clinical Genomics Center for All of UsOT2OD002751 · OD · BAYLOR COLLEGE OF MEDICINE · PI BOERWINKLE, ERIC A., DOHENY, KIMBERLY F · 2018 to 2023
$152.8M
Enhancing All of Us Data Resources for Nutrition Precision Health: the All of Us Data and Research CenterU2COD023196 · OD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GLAZER, DAVID, HARRIS, PAUL A. · 2016 to 2022
$143.7M
Adaptive Platform for Personalized EngagementU24OD023163 · OD · VIGNET, INC. · PI JAIN, PRADUMAN · 2017 to 2020
$102.6M
University of Arizona-Banner Health All of Us Research Program OT2OD026549 · OD · UNIVERSITY OF ARIZONA · PI MORENO, FRANCISCO A, REIMAN, ERIC MICHAEL · 2018 to 2023
$78.9M
California Precision Medicine Research Program ConsortiumOT2OD026552 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANTON-CULVER, HODA A, OHNO-MACHADO, LUCILA · 2018 to 2023
$73.4M
All of Us PennsylvaniaOT2OD026554 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E, VISWESWARAN, SHYAM · 2018 to 2023
$72.1M
New York City Consortium for Precision MedicineOT2OD026556 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BIER, LOUISE E, GHARAVI, ALI G · 2018 to 2023
$67.3M
Northwest Genomics Center for All of UsOT2OD002748 · OD · UNIVERSITY OF WASHINGTON · PI EICHLER, EVAN, JARVIK, GAIL PAIRITZ · 2018 to 2023
$65.4M
SouthEast Enrollment Center (SEEC) OT2OD026551 · OD · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CARRASQUILLO, OLVEEN, COLON, VIVIAN · 2018 to 2023
$62.8M
Southern All of Us NetworkOT2OD026548 · OD · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI FOUAD, MONA N., KORF, BRUCE R · 2018 to 2023
$60.5M
NIH HHS OT2 OD002748NIH HHS OT2 OD002751NIH HHS OT2 OD023205NIH HHS OT2 OD023206NIH HHS OT2 OD025276NIH HHS OT2 OD025277NIH HHS OT2 OD025315NIH HHS OT2 OD025337NIH HHS OT2 OD026548NIH HHS OT2 OD026549NIH HHS OT2 OD026550NIH HHS OT2 OD026551NIH HHS OT2 OD026552NIH HHS OT2 OD026553NIH HHS OT2 OD026554NIH HHS OT2 OD026555NIH HHS OT2 OD026556NIH HHS OT2 OD026557NIH HHS OT2 OD027070NIH HHS OT2 OD038122NIH HHS U24 OD023121NIH HHS U24 OD023163NIH HHS U24 OD023176NIH HHS U2C OD023196
6 · The paper itself

Abstract

The All of Us (AoU) initiative aims to sequence the genomes of over one million Americans from diverse ethnic backgrounds to improve personalized medical care. In a recent technical pilot, we compare the performance of traditional short-read sequencing with long-read sequencing in a small cohort of samples from the HapMap project and two AoU control samples representing eight datasets. Our analysis reveals substantial differences in the ability of these technologies to accurately sequence complex medically relevant genes, particularly in terms of gene coverage and pathogenic variant identification. We also consider the advantages and challenges of using low coverage sequencing to increase sample numbers in large cohort analysis. Our results show that HiFi reads produce the most accurate results for both small and large variants. Further, we present a cloud-based pipeline to optimize SNV, indel and SV calling at scale for long-reads analysis. These results lead to widespread improvements across AoU.

Indexed as

High-Throughput Nucleotide SequencingPopulation HealthGenome, HumanHumansINDEL MutationSequence Analysis, DNA

Identifiers

PMID38281971
PMCPMC10822842
OpenAlexW4391320440

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.