Accès ouvert déclaré 2023 preprint

Structural variation across 138,134 samples in the TOPMed consortium

Goo Jun, Adam C. English, Ginger Metcalf, Jianzhi Yang, Mark Chaisson, Nathan Pankratz, Vipin K. Menon, William Salerno, Olga Krasheninina, Albert V. Smith, John Lane, Thomas W. Blackwell, Hyun Min Kang, Sejal Salvi, Qingchang Meng, Hua Shen, Divya Pasham, Sravya Bhamidipati, Kavya Kottapalli, Donna K. Arnett, Allison E. Ashley‐Koch, Paul L. Auer, Kathleen M Beutel, Joshua C. Bis, John Blangero, Donald W. Bowden, Jennifer A. Brody, Brian E. Cade, Yii‐Der Ida Chen, Michael H. Cho, Joanne E. Curran, Myriam Fornage, Barry Frredman, Tasha E. Fingerlin, Bruce D. Gelb, Lifang Hou, Yi‐Jen Hung, John P. Kane, Robert C. Kaplan, Wonji Kim, Ruth J. F. Loos, Gregory M. Marcus, Rasika A. Mathias, Stephen T. McGarvey, Courtney G. Montgomery, Take Naseri, Michael Preuß, Patricia A. Peyser, Laura M. Raffield, Aakrosh Ratan, Susan Redline, Muagututi‘a Sefuiva Reupena, Jerome I. Rotter, Stephen S. Rich, Michiel Rienstra, Ingo Ruczinski, Vijay G. Sankaran, David A. Schwartz, Christine E. Seidman, Jonathan G. Seidman, Edwin K. Silverman, Jennifer A. Smith, Adrienne M. Stilp, Kent D. Taylor, Marilyn J. Telen, Scott T. Weiss, L. Keoki Williams, Baojun Wu, Lisa R. Yanek, Yingze Zhang, Jessica Lasky‐Su, Marie‐Claude Gingras, Susan K. Dutcher, Evan E. Eichler, Stacey Gabriel, Søren Germer, Ryan Kim, Karine A. Viaud Martinez, Deborah A. Nickerson, James Luo, Alex P. Reiner, Richard A. Gibbs, Eric Boerwinkle, Goncaol Abecasis, Fritz J. Sedlazeck

9Citations signalées, ce qui n’est pas une note de qualité

58Institutions déclarées

8Pays d’affiliation déclarés

Rattachement africain : us, gb, tw, dk, jm, ws, ee, nl. Niveau de preuve : code pays fourni par la source.

Résumé indisponible. Les résultats de l’étude ne doivent pas être déduits de son seul titre.

Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref: Structural variation across 138,134 samples in the TOPMed consortium
Date Crossref: 03/02/2023
Éditeur: Springer Science and Business Media LLC
Type: posted-content

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Les institutions déclarées

The University of Texas Health Science Center at Houston Baylor College of Medicine Baylor Genetics University of Southern California California Southern University University of Minnesota Regeneron (United States)University of Michigan University of Minnesota System University of Kentucky Duke University Duke Medical Center Medical College of Wisconsin University of Washington University College London The University of Texas Rio Grande Valley Wake Forest University Brigham and Women's Hospital Circadian (United States)UCLA Medical Center Harbor–UCLA Medical Center Brown Foundation National Jewish Health University of Colorado Denver Northwestern University Child Health and Development Institute Pediatrics and Genetics Icahn School of Medicine at Mount Sinai Tri-Service General Hospital Songshan Branch National Defense Medical Center Albert Einstein College of Medicine University of California, San Francisco Novo Nordisk Foundation Foundation Center Novo Nordisk Foundation Center for Basic Metabolic Research Johns Hopkins University Johns Hopkins Medicine Ministry of Health Oklahoma Medical Research Foundation National University of Samoa University of Pittsburgh University of North Carolina at Chapel Hill University of Virginia Wikimedia Eesti University Medical Center Groningen University of Groningen Boston Children's Hospital Boston Children's Museum University of Colorado System Harvard University Harvard University Press Genomics (United Kingdom)Henry Ford Health Broad Institute New York Genome Center Illumina (United States)National Heart, Lung, and Blood Institute Fred Hutch Cancer Center

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Gene expression and cancer classificationGenetic Associations and EpidemiologyRadiomics and Machine Learning in Medical Imaging

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