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Inferring compound heterozygosity from large-scale exome sequencing data
Michael H. Guo, Laurent C. Francioli, Sarah L. Stenton, Julia K. Goodrich, Nicholas A. Watts, Moriel Singer‐Berk, Emily Groopman, Philip W. Darnowsky, Matthew Solomonson, Samantha Baxter, María T. Abreu, Carlos A. Aguilar‐Salinas, Tariq Ahmad, Christine M. Albert, Jessica Alföldi, Diego Ardissino, Irina M. Armean, Gil Atzmon, Eric Banks, John Barnard, Laurent Beaugerie, Emelia J. Benjamin, David Benjamin, Louis Bergelson, Michael Boehnke, Lori L. Bonnycastle, Erwin P. Böttinger, Donald W. Bowden, Matthew J. Bown, Steven R. Brant, Sarah E. Calvo, Hannia Campos, John C. Chambers, Juliana C.N. Chan, Katherine R. Chao, Sinéad B. Chapman, Daniel I. Chasman, Siwei Chen, Rex L. Chisholm, Judy H. Cho, Rajiv Chowdhury, Mina K. Chung, Wendy K. Chung, Kristian Cibulskis, Bruce M. Cohen, Ryan L. Collins, Kristen M. Connolly, Adolfo Correa, Miguel Covarrubias, Beryl B. Cummings, Dana Dabelea, John Danesh, Dawood Darbar, Joshua C. Denny, Stacey Donnelly, Ravindranath Duggirala, Josée Dupuis, Patrick T. Ellinor, Roberto Elosúa, James Emery, Eleina England, Jeanette Erdmann, Tõnu Esko, Emily Evangelista, Yossi Farjoun, Diane Fatkin, Steven Ferriera, José C. Florez, André Franke, Martti Färkkilâ, Stacey Gabriel, Kiran Garimella, Laura D. Gauthier, Jeff Gentry, Gad Getz, David C. Glahn, Benjamin Gläser, Stephen J. Glatt, David B. Goldstein, Clicerio González, Leif Groop, Sanna Gudmundsson, Namrata Gupta, Andrea Haessly, Christopher A. Haiman, Ira M. Hall, Craig L. Hanis, Matthew Harms, Mikko Hiltunen, Matti Holi, Christina M. Hultman, Chaim Jalas, Thibault Jeandet, Mikko Kallela, Diane Kaplan, Jaakko Kaprio, Sekar Kathiresan, Eimear E. Kenny, Bong-Jo Kim, Young Jin Kim, George Kirov, Zan Koenig, 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, Christopher Llanwarne, Ruth J. F. Loos, Steven A. Lubitz, Teresa Tusie Luna, Ronald C.W., Gregory M. Marcus, Jaume Marrugat, Alicia R. Martin, 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, Ruchi Munshi, Aliya Naheed, Saman Nazarian, Peter M. Nilsson, Sam Novod, Anne O’Donnell‐Luria, Michael O‘Donovan, Yukinori Okada, Döst Öngür, Lorena Orozco, Michael J. Owen, Aarno Palotie, Kyong Soo Park, Carlos N. Pato, Nikelle Petrillo, William Phu, Timothy Poterba, Ann E. Pulver, Dan Rader, Nazneen Rahman, Alex P. Reiner, Anne M. Remes, Dan Rhodes, Stephen S. Rich, John D. Rioux, Samuli Ripatti, David Roazen, Dan M. Roden, Jerome I. Rotter, Valentín Ruano-Rubio, Nareh Sahakian, Danish Saleheen, Veikko Salomaa, Andrea Saltzman, Nilesh J. Samani, Jeremiah M. Scharf, Molly Schleicher, Heribert Schunkert, Sebastian Schönherr, Eleanor G. Seaby, Cotton Seed, Svati H. Shah, Megan Shand, M. Benjamin Shoemaker, Tai E. Shyong, Edwin K. Silverman, Pamela Sklar, J. G. Smith, Jonathan T. 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, Michael E. Talkowski, Yekaterina Tarasova, Kent D. Taylor, Yik Ying Teo, Kathleen Tibbetts, Charlotte Tolonen, Ming T. Tsuang, Dan Turner, Teresa Tusié‐Luna, Erkki Vartiainen, Marquis P. Vawter, Christopher Vittal, Gordon Wade, Arcturus Wang, Qingbo S. Wang, James S. Ware, Hugh Watkins, Rinse K. Weersma, Ben Weisburd, Maija Wessman, Nicola Whiffin, Michael W. Wilson, James G. Wilson, Ramnik J. Xavier, Mary T. Yohannes, Grace Tiao, Benjamin M. Neale, Joel N. Hirschhorn, Heidi L. Rehm, Mark J. Daly, Konrad J. Karczewski, Daniel G. MacArthur, Kaitlin E. Samocha
Bibliographic record
VenueNature Genetics · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsUniversité de MontréalMcGill Genome CentreMontreal Heart InstituteUniversity of Ottawa
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesEisaiNational Human Genome Research InstituteGlaxoSmithKlineBiogenAstellas PharmaWellcome TrustU.S. Department of Health and Human Services
KeywordsBiologyGeneticsExome sequencingExomeCompound heterozygosityGeneComputational biologyLoss of heterozygosityMendelian inheritance1000 Genomes ProjectContext (archaeology)GenomeWhole genome sequencingGenotypeAlleleMutationSingle-nucleotide polymorphism
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.712
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 head0.024
GPT teacher head0.285
Teacher spread0.261 · 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 teacher head, not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Citations35
Published2023
Admission routes1
Has abstractno