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A genomic mutational constraint map using variation in 76,156 human genomes
Siwei Chen, Laurent C. Francioli, Julia K. Goodrich, Ryan L. Collins, Masahiro Kanai, Qingbo S. Wang, Jessica Alföldi, Nicholas A. Watts, Christopher Vittal, Laura D. Gauthier, Timothy Poterba, Michael W. Wilson, Yekaterina Tarasova, William Phu, Riley Grant, Mary T. Yohannes, Zan Koenig, Yossi Farjoun, Eric Banks, Stacey Donnelly, Stacey Gabriel, Namrata Gupta, Steven Ferriera, Charlotte Tolonen, Sam Novod, Louis Bergelson, David Roazen, Valentín Ruano-Rubio, Miguel Covarrubias, Christopher Llanwarne, Nikelle Petrillo, Gordon Wade, Thibault Jeandet, Ruchi Munshi, Kathleen Tibbetts, María T. Abreu, Carlos A. Aguilar‐Salinas, Tariq Ahmad, Christine M. Albert, Diego Ardissino, Irina M. Armean, Elizabeth G. Atkinson, Gil Atzmon, John Barnard, Samantha Baxter, Laurent Beaugerie, Emelia J. Benjamin, David Benjamin, Michael Boehnke, Lori L. Bonnycastle, Erwin P. Böttinger, Donald W. Bowden, Matthew J. Bown, Harrison Brand, Steven R. Brant, Ted Brookings, Sam Bryant, Sarah E. Calvo, Hannia Campos, John C. Chambers, Juliana C.N. Chan, Katherine R. Chao, Sinéad B. Chapman, Daniel I. Chasman, Rex L. Chisholm, Judy H. Cho, Rajiv Chowdhury, Mina K. Chung, Wendy K. Chung, Kristian Cibulskis, Bruce M. Cohen, Kristen M. Connolly, Adolfo Correa, Beryl B. Cummings, Dana Dabelea, John Danesh, Dawood Darbar, Phil Darnowsky, Joshua C. Denny, Ravindranath Duggirala, Josée Dupuis, Patrick T. Ellinor, Roberto Elosúa, James Emery, Eleina England, Jeanette Erdmann, Tõnu Esko, Emily Evangelista, Diane Fatkin, José C. Florez, André Franke, Jack Fu, Martti Färkkilâ, Kiran Garimella, Jeff Gentry, Gad Getz, David C. Glahn, Benjamin Gläser, Stephen J. Glatt, David B. Goldstein, Clicerio González, Leif Groop, Sanna Gudmundsson, Andrea Haessly, Christopher A. Haiman, Ira M. Hall, Craig L. Hanis, Matthew Harms, Mikko Hiltunen, Matti Holi, Christina M. Hultman, Chaim Jalas, Mikko Kallela, Diane Kaplan, Jaakko Kaprio, Sekar Kathiresan, Eimear E. Kenny, Bong‐Jo Kim, Young Jin Kim, Daniel A. King, George Kirov, Jaspal S. Kooner, Seppo Koskinen, Harlan M. Krumholz, Subra Kugathasan, Soo Heon Kwak, Markku Laakso, Nicole J. Lake, Trevyn Langsford, Kristen M. Laricchia, Terho Lehtimäki, Monkol Lek, Emily Lipscomb, Ruth J. F. Loos, Wenhan Lu, Steven A. Lubitz, Teresa Tusie Luna, Ronald C.W., Gregory M. Marcus, Jaume Marrugat, Kari M. Mattila, Steven A. McCarroll, Mark I. McCarthy, Jacob L. McCauley, Dermot McGovern, Ruth McPherson, James B. Meigs, Olle Melander, Andres Metspalu, Deborah A. Meyers, Eric Vallabh Minikel, Braxton D. Mitchell, Vamsi K. Mootha, Aliya Naheed, Saman Nazarian, Peter M. Nilsson, Michael O‘Donovan, Yukinori Okada, Döst Öngür, Lorena Orozco, Michael J. Owen, Aarno Palotie, Kyong Soo Park, Carlos N. Pato, Ann E. Pulver, Dan Rader, Nazneen Rahman, Alex P. Reiner, Anne M. Remes, Dan Rhodes, Stephen S. Rich, John D. Rioux, Samuli Ripatti, Dan M. Roden, Jerome I. Rotter, Nareh Sahakian, Danish Saleheen, Veikko Salomaa, Andrea Saltzman, Nilesh J. Samani, Kaitlin E. Samocha, Alba Sanchis-Juan, Jeremiah M. Scharf, Molly Schleicher, Heribert Schunkert, Sebastian Schönherr, Eleanor G. Seaby, Svati H. Shah, Megan Shand, Ted Sharpe, M. Benjamin Shoemaker, Tai E. Shyong, Edwin K. Silverman, Moriel Singer‐Berk, Pamela Sklar, Jonathan T. Smith, J. G. Smith, Hilkka Soininen, Harry Sokol, Rachel G. Son, José Soto, Tim D. Spector, Christine Stevens, Nathan O. Stitziel, Patrick F. Sullivan, Jaana Suvisaari, E Shyong Tai, Kent D. Taylor, Yik Ying Teo, Ming T. Tsuang, Dan Turner, Teresa Tusié‐Luna, Erkki Vartiainen, Marquis P. Vawter, Lily Wang, Arcturus Wang, James S. Ware, Hugh Watkins, Rinse K. Weersma, Ben Weisburd, Maija Wessman, Nicola Whiffin, James G. Wilson, Ramnik J. Xavier, Anne O’Donnell‐Luria, Matthew Solomonson, Cotton Seed, Alicia R. Martin, Michael E. Talkowski, Heidi L. Rehm, Mark J. Daly, Grace Tiao, Benjamin M. Neale, Daniel G. MacArthur, Konrad J. Karczewski
Bibliographic record
VenueNature · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsUniversité de MontréalMontreal Heart InstituteUniversity of OttawaMcGill University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Diabetes and Digestive and Kidney DiseasesNational Human Genome Research InstituteNational Institute of Mental HealthNational Institutes of HealthWellcome Trust
KeywordsVariation (astronomy)GenomeConstraint (computer-aided design)Human genomeBiologyComputational biologyGeneticsGenomicsEvolutionary biologyHuman genetic variationStructural variationGeneMathematicsPhysics
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.011
GPT teacher head0.261
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations1,330
Published2023
Admission routes1
Has abstractno