Evidence map›Paper›PMID 38636510›Full record

ArticleAmerican journal of human genetics2024

MagicalRsq-X: A cross-cohort transferable genotype imputation quality metric.

Quan Sun, Yingxi Yang, Jonathan D Rosen, Jiawen Chen, Xihao Li, Wyliena Guan, Min-Zhi Jiang, Jia Wen, Rhonda G Pace, Scott M Blackman and 17 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of human genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
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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

27 authors.

Quan SunDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Yingxi YangDepartment of Statistics and Data Science, Yale University, New Haven, CT 06520, USA.
Jonathan D RosenDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Jiawen ChenDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Xihao LiDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Wyliena GuanDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Min-Zhi JiangDepartment of Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Jia WenDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Rhonda G PaceMarsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Scott M BlackmanDivision of Pediatric Endocrinology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Michael J BamshadDepartment of Pediatrics, University of Washington, Seattle, WA 98105, USA; Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
Ronald L GibsonDepartment of Pediatrics, University of Washington, Seattle, WA 98105, USA.
Garry R CuttingDepartment of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Wanda K O'NealMarsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Michael R KnowlesMarsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Charles KooperbergDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA.
Alexander P ReinerDepartment of Epidemiology, University of Washington, Seattle, WA 98195, USA.
Laura M RaffieldDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
April P CarsonDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35249, USA.
Stephen S RichCenter for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.
Jerome I RotterThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA.
Ruth J F LoosThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA; Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.
Eimear KennyThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA.
Byron C JaegerWake Forest School of Medicine, Department of Biostatistics and Data Science, Wake Forest University, Winston-Salem, NC 27109, USA.
Yuan-I MinDepartment of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA.
Christian FuchsbergerInstitute for Biomedicine, Eurac Research (affiliated with the University of Lübeck), Bolzano, Italy. Electronic address: cfuchsberger@eurac.edu.
Yun LiDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. Electronic address: yunli@med.unc.edu.

Funding

Back Pain Consortium (BACPAC) Research Program Data Integration, Algorithm Development and Operations Management CenterU24AR076730 · NIAMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ANSTROM, KEVIN J, IVANOVA, ANASTASIA · 2019 to 2024
$60.0M
Biostatstics for Research in Environmental HealthT32ES007018 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Stephanie Engel, Rebecca Fry · 1985 to 2026
$31.3M
CHARGE Consortium: Omics Discovery for CVD and Aging PhenotypesR01HL105756 · NHLBI · UNIVERSITY OF WASHINGTON · PI Bruce M Psaty, NICHOLAS L SMITH · 2011 to 2026
$9.5M
Next generation functional genomics of hematology traitsR01HL146500 · NHLBI · UNIVERSITY OF WASHINGTON · PI ALEXANDER P REINER · 2020 to 2026
$5.7M
Polygenic risk scores for cardiometabolic disorders: the role of blood cells immune response and evolutionary adaptationU01HG011720 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Yun Li, ALEXANDER P REINER · 2021 to 2026
$5.4M
A Trans-Nordic Study of Extreme Major DepressionR01MH123724 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI PATRICK F SULLIVAN, Lu Yi · 2020 to 2026
$4.7M
NHGRI NIH HHS U01 HG011720NHLBI NIH HHS R01 HL146500NIAMS NIH HHS U24 AR076730NIEHS NIH HHS T32 ES007018NIMH NIH HHS R01 MH123724
6 · The paper itself

Abstract

Since genotype imputation was introduced, researchers have been relying on the estimated imputation quality from imputation software to perform post-imputation quality control (QC). However, this quality estimate (denoted as Rsq) performs less well for lower-frequency variants. We recently published MagicalRsq, a machine-learning-based imputation quality calibration, which leverages additional typed markers from the same cohort and outperforms Rsq as a QC metric. In this work, we extended the original MagicalRsq to allow cross-cohort model training and named the new model MagicalRsq-X. We removed the cohort-specific estimated minor allele frequency and included linkage disequilibrium scores and recombination rates as additional features. Leveraging whole-genome sequencing data from TOPMed, specifically participants in the BioMe, JHS, WHI, and MESA studies, we performed comprehensive cross-cohort evaluations for predominantly European and African ancestral individuals based on their inferred global ancestry with the 1000 Genomes and Human Genome Diversity Project data as reference. Our results suggest MagicalRsq-X outperforms Rsq in almost every setting, with 7.3%-14.4% improvement in squared Pearson correlation with true R

Indexed as

Gene FrequencyGenotypePolymorphism, Single NucleotideSoftwareCohort StudiesGenome, HumanGenome-Wide Association StudyHumansLinkage DisequilibriumMachine LearningQuality ControlWhole Genome Sequencingcross-cohortgenome-wide association studiesgenotype imputationimputation qualitymachine learningquality controlrare variantsvariant filteringwhole-genome sequencing

Identifiers

PMID38636510
PMCPMC11080605

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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.