In one paragraphArticle in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from itWhat 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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
74 authors.
Malvika TejuraDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0001-5356-1977 Yile ChenDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-4406-1166 Abbye E McEwenDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0001-7187-7975 Yuriy SverchkovDepartment of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA.ORCID 0000-0002-9851-8582 Florent LavalCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0001-7744-6199 Shawn FayerDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-1883-9069 Jeremy StoneBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-7565-2463 Nahum SmithBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0007-5494-7477 Silvia CasadeiBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-2619-5662 Ziyu R WangDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0000-4924-2463 Matthew W SnyderBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0001-7433-4343 Benjamin J CapodannoBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0007-1273-879X Pankhuri GuptaDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0002-5802-1296 Mariam BenazouzMolecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA.ORCID 0000-0001-8561-296X Sarah HeidlBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0000-7692-9391 Lara MuffleyDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-3035-3339 Estelle Y DaDepartment of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia.ORCID 0000-0002-9313-7860 Sabrina BestBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0008-6352-0106 Sally GrindstaffBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-0930-0520 David ReinhartBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0009-1975-4180 Leslie Rodriguez-SalasBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0008-0602-8035 Allyssa J VandiDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0001-6781-416X Cameron WenmanBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0001-0819-0326 Melinda K WheelockDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0002-9825-6276 Sriram PendyalaDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-3395-3417 Dan HolmesDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-0489-4043 Airi HosokaiBrotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.ORCID 0009-0008-5802-7130 Maxime TixhonCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0009-0004-4289-6842 Chloe RenoDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0009-0009-9332-0831 Kerstin Spirohn-FitzgeraldCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0002-2071-1606 Tanisha TeelucksinghDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-1151-8433 Georges CoppinCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0001-7647-3240 Luke LambourneCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0002-7001-7575 Marinella GebbiaDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-2550-2141 Atina G CotéDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-0340-9325 Warren van LoggerenbergDepartment of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.ORCID 0000-0002-4912-1044 Kirby M FawcettDepartment of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.ORCID 0009-0004-0729-5283 Jill M JohnsenDivision of Hematology and Oncology, Department of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-2279-2550 Andrew B StergachisDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-1299-3674 Frederick P RothDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-6628-649X Richard G JamesCenter for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, WA, USA.ORCID 0000-0002-2302-7367 IGVF Coding Variants Focus Group
Mikko TaipaleDonnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-3811-1761 Michael A CalderwoodCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.ORCID 0000-0001-6475-1418 Mark CravenDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0002-8917-7464 Vikas PejaverInstitute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID 0000-0002-1943-0284 Alan F RubinCollaborative Centre for Genomic Cancer Medicine, University of Melbourne, Melbourne, VIC, Australia.ORCID 0000-0003-1474-605X Douglas M FowlerDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0001-7614-1713 Lea M StaritaDepartment of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-2870-5099 Funding
Conduits: Mount Sinai Health System Translational Science HubUL1TR004419 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Rosalind J Wright · 2022 to 2026
$46.4MGenomic Analysis of Network Perturbations in Human DiseaseP50HG004233 · NHGRI · DANA-FARBER CANCER INST · PI VIDAL, MARC · 2007 to 2017
$31.6MSupport for the use and evaluation of large cloud-based genomic datasets.U24HG012012 · NHGRI · STANFORD UNIVERSITY · PI Mark Bender Gerstein, Benjamin Hitz · 2021 to 2026
$23.0MUniversity of Washington Mendelian Genomics Research Center (UW-MGRC)U01HG011744 · NHGRI · UNIVERSITY OF WASHINGTON · PI MICHAEL Joseph BAMSHAD, Evan Eichler · 2021 to 2026
$15.8MThe Center for Actionable Variant Analysis; measuring variant function at scaleUM1HG011969 · NHGRI · UNIVERSITY OF WASHINGTON · PI Douglas M Fowler, Lea Starita · 2021 to 2026
$9.9MMolecular phenotyping of ~100,000 coding variants across Mendelian disease genesUM1HG011989 · NHGRI · DANA-FARBER CANCER INST · PI Marc Vidal · 2021 to 2026
$9.9MMedical Genetics Training GrantT32GM007454 · NIGMS · UNIVERSITY OF WASHINGTON · PI Gail Pairitz Jarvik, Andrew Ben Stergachis · 1985 to 2026
$6.9MLinking Variants to Multi-scale Phenotypes via a Synthesis of Subnetwork Inference and Deep LearningU01HG012039 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI Mark W. Craven · 2021 to 2026
$3.5MSupporting IGVF by modeling genetics, function, and phenotype with machine learningU01HG012022 · NHGRI · NORTHEASTERN UNIVERSITY · PI Predrag Radivojac · 2021 to 2026
$3.4MAdvancing the implementation of variant-level functional data into clinical databases and clinical practiceR01HG013025 · NHGRI · UNIVERSITY OF WASHINGTON · PI Lea Starita, Andrew Ben Stergachis · 2023 to 2026
$3.1MCOVID and Translational Science supercomputer (CATS)S10OD030463 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2021 to 2021
$2.0MBig Omics Data Engine 2 SupercomputerS10OD026880 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2019 to 2019
$2.0MNCATS NIH HHS UL1 TR004419NHGRI NIH HHS P50 HG004233NHGRI NIH HHS R01 HG013025NHGRI NIH HHS R01 HG013350NHGRI NIH HHS U01 HG011744NHGRI NIH HHS U01 HG012022NHGRI NIH HHS U01 HG012039NHGRI NIH HHS U24 HG012012NHGRI NIH HHS UM1 HG011969NHGRI NIH HHS UM1 HG011989NHLBI NIH HHS R01 HL152066NIGMS NIH HHS T32 GM007454NIH HHS S10 OD026880NIH HHS S10 OD030463NIMH NIH HHS R21 MH128827NIMH NIH HHS R56 MH128365
6 · The paper itselfAbstract
Over 90% of missense variants across ~4,000 disease-associated genes are variants of uncertain significance (VUS). Experimental variant effect measurements provide critical evidence about pathogenicity and inform disease biology, but most variants lack data and clinical translation has been limited. The Impact of Genomic Variation on Function Consortium generated experimental data for 62,215 variants across ten genes using multiplexed assays and 1,407 variants across 163 genes using arrayed assays, curated 193,139 additional community-generated variant effect measurements across 30 additional genes, and developed automated calibration methods for translating experimental data and variant effect predictions into clinical evidence. To reduce current VUS, we developed a scalable workflow using only experimental and predictive evidence, enabling reclassification of 75% of the 16,115 VUS in these genes as pathogenic or benign with <1% error. To minimize future VUS, we analyzed >90,000 unobserved variants; 62% had enough evidence to be "preclassified" as pathogenic or benign. We validated our data, evidence and classifications using All of Us and created interactive resources to enable clinical use of the calibrated data. Thus, for 40 genes, representing 1% of the clinical genome, we resolve most existing VUS and future variants, illustrating how systematic use of scalable evidence can empower genomic medicine.
Identifiers
PMID41727046
PMCPMC12918978
What OpenQuestion holds
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