Evidence map›Paper›PMID 40701146›Full record

ReviewAmerican journal of human genetics2025

Implementing a training resource for large-scale genomic data analysis in the All of Us Researcher Workbench.

Jasmine Baker, Erik Stricker, Julie Coleman, Shamika Ketkar, Taotao Tan, Ashley M Butler, LaTerrica Williams, Latanya Hammonds-Odie, Debra Murray, Brendan Lee and 2 more

Abstract readReview
In one paragraph

Review in American journal of human genetics, 2025. 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. TheJournal of clinical and translational science · 2026
    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

12 authors.

Jasmine BakerDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Erik StrickerDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Julie ColemanDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Shamika KetkarDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Taotao TanDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX, USA.
Ashley M ButlerDepartment of Pediatrics, Baylor College of Medicine, Houston, TX, USA.
LaTerrica WilliamsDepartment of Pediatrics, Baylor College of Medicine, Houston, TX, USA.
Latanya Hammonds-OdieDepartment of Biological Sciences, Georgia Gwinnett College, Lawrenceville, GA, USA.
Debra MurrayDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Brendan LeeDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Kim C WorleyDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Elizabeth G AtkinsonDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA. Electronic address: elizabeth.atkinson@bcm.edu.

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
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
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
Illinois Precision Medicine Consortium OT2OD026557 · OD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI AHSAN, HABIBUL, ARGOS, MARIA · 2018 to 2023
$60.5M
The New England Precision Medicine Consortium of the All of Us Research ProgramOT2OD026553 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI CLARK, CHERYL RENEE, KARLSON, ELIZABETH W · 2018 to 2023
$58.8M
NHGRI NIH HHS R01 HG012869NIH 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 OD031932NIH HHS U24 OD023121NIH HHS U24 OD023163NIH HHS U24 OD023176NIH HHS U2C OD023196
6 · The paper itself

Abstract

A lack of representation in genomic research and limited access to computational training create barriers for many researchers seeking to analyze large-scale genetic datasets. The All of Us Research Program provides an unprecedented opportunity to address these gaps by offering genomic data from a broad range of participants, but its impact depends on equipping researchers with the necessary skills to use it effectively. The All of Us Biomedical Researcher (BR) Scholars Program at Baylor College of Medicine aims to break down these barriers by providing early-career researchers with hands-on training in computational genomics through the All of Us Evenings with Genetics Research Program. The year-long program begins with the faculty summit, an in-person computational boot camp that introduces scholars to foundational skills for using the All of Us dataset via a cloud-based research environment. The genomics tutorials focus on genome-wide association studies (GWASs), utilizing Jupyter Notebooks and the Hail computing framework to provide an accessible and scalable approach to large-scale data analysis. Scholars engage in hands-on exercises covering data preparation, quality control, association testing, and result interpretation. By the end of the summit, participants will have successfully conducted a GWAS, visualized key findings, and gained confidence in computational resource management. This initiative expands access to genomic research by equipping early-career researchers from a variety of backgrounds with the tools and knowledge to analyze All of Us data. By lowering barriers to entry and promoting the study of representative populations, the program fosters innovation in precision medicine and advances equity in genomic research.

Indexed as

Biomedical ResearchComputational BiologyGenomicsResearch PersonnelData AnalysisGenome-Wide Association StudyHumansUnited Statesbiomedical researchcontinuing educationcurriculumeducationgenomegenome-wide association studygenomicshealthhealth equitymedical informaticsresearchresearch personnel

Identifiers

PMID40701146
PMCPMC12320718

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.