Record W3166466898 · doi:10.1038/s41467-021-23655-2

Variant-specific inflation factors for assessing population stratification at the phenotypic variance level

2021· article· en· W3166466898 on OpenAlexaff

Tamar Sofer, Xiuwen Zheng, Cecelia Laurie, Stephanie M. Gogarten, Jennifer A. Brody, Matthew P. Conomos, Joshua C. Bis, Timothy A. Thornton, Adam A. Szpiro, Jeffrey R. O’Connell, Ethan M. Lange, Yan Gao, L. Adrienne Cupples, Bruce M. Psaty, Namiko Abe, Gonçalo R. Abecasis, François Aguet, Christine M. Albert, Laura Almasy, Álvaro Alonso, Seth A. Ament, Peter Anderson, Pramod Anugu, Deborah Applebaum‐Bowden, Kristin Ardlie, Dan Arking, Donna K. Arnett, Allison E. Ashley‐Koch, Stella Aslibekyan, Tim Assimes, Paul L. Auer, Dimitrios Avramopoulos, Najib Ayas, Adithya Balasubramanian, John Barnard, Kathleen C. Barnes, R. Graham Barr, Emily Barron‐Casella, Lucas Barwick, Terri Beaty, Gerald J. Beck, Diane M. Becker, Lewis C. Becker, Rebecca Beer, Amber L. Beitelshees, Emelia J. Benjamin, Takis Benos, Marcos Bezerra, Larry Bielak, Thomas W. Blackwell, John Blangero, Eric Boerwinkle, Donald W. Bowden, Russell P. Bowler, Ulrich Broeckel, Jai Broome, Deborah Brown, Karen Bunting, Esteban G. Burchard, Carlos D. Bustamante, Erin Buth, Brian E. Cade, Jonathan Cardwell, Vincent J. Carey, Julie Carrier, Cara L. Carty, Richard Casaburi, Juan P. Romero, James F. Casella, Peter J. Castaldi, Mark Chaffin, Christy Chang, Yi‐Cheng Chang, Daniel I. Chasman, Sameer Chavan, Bo-Juen Chen, Wei‐Min Chen, Yii‐Der Ida Chen, Michael H. Cho, Seung Hoan Choi, Lee‐Ming Chuang, Mina K. Chung, Ren‐Hua Chung, Clary B. Clish, Suzy Comhair, Elaine Cornell, Adolfo Correa, Carolyn Crandall, James D. Crapo, Joanne E. Curran, Jeffrey L. Curtis, Brian Custer, Coleen Damcott, Dawood Darbar, Sean P. David, Colleen Davis, Michelle Daya, Mariza de Andrade, Lisa de las Fuentes, Paul S. de Vries, Michael R. DeBaun, Ranjan Deka, Dawn L. DeMeo, Scott E. Devine, Huyen Dinh, HarshaVardhan Doddapaneni, Qing Duan, Shannon Dugan‐Perez, Ravi Duggirala, Jon Peter Durda, Susan K. Dutcher, Charles B. Eaton, Lynette Ekunwe, Adel Boueiz, Patrick T. Ellinor, Leslie S. Emery, Serpil C. Erzurum, Charles R. Farber, Jesse Farek, Tasha E. Fingerlin, Matthew Flickinger, Myriam Fornage, Nora Franceschini, Chris Frazar, Mao Fu, Stephanie M. Fullerton, Lucinda A. Fulton, Stacey Gabriel, Weiniu Gan, Shanshan Gao, Margery Gass, Heather Geiger, Bruce D. Gelb, Mark W. Geraci, Søren Germer, Robert E. Gerszten, Auyon Ghosh, Richard A. Gibbs, Chris Gignoux, Mark T. Gladwin, David C. Glahn, Da‐Wei Gong, Harald H.H. Göring, Sharon Graw, Kathryn J. Gray, Daniel Grine, Colin Gross, C. Charles Gu, Yue Guan, Xiuqing Guo, Namrata Gupta, David M. Haas, Jeff Haessler, Michael E. Hall, Yi Han, Patrick J. Hanly, Daniel Harris, Nicola L. Hawley, Jiang He, Ben Heavner, Susan R. Heckbert, Ryan D. Hernandez, David Herrington, Craig P. Hersh, Bertha Hidalgo, James E. Hixson, Brian D. Hobbs, John S. Hokanson, Elliott Hong, Karin F. Hoth, Chao A. Hsiung, Jianhong Hu, Yi‐Jen Hung, Haley Huston, Chii Min Hwu, Marguerite R. Irvin, Rebecca D. Jackson, Deepti Jain, Cashell E. Jaquish, Jill M. Johnsen, Andrew D. Johnson, Craig Johnson, Rich Johnston, Kimberly Marie Jones, Hyun Min Kang, Robert C. Kaplan, Sharon Kardia, Shannon Kelly, Eimear Kenny, Michael Kessler, Alyna Khan, Ziad Khan, Wonji Kim, John Kimoff, Gregory L. Kinney, Barbara A. Konkle, Charles Kooperberg, Holly Kramer, Christoph Lange, Leslie Lange, Cathy C. Laurie, Meryl S. LeBoff, Sandra Lee, Wen‐Jane Lee, Jonathon LeFaive, David Levine, Dan Levy, Joshua P. Lewis, Xiaohui Li, Yun Li, Henry J. Lin, Honghuang Lin, Xihong Lin, Simin Liu, Ching‐Ti Liu, Yu Liu, Ruth J. F. Loos, Steven Lubitz, Kathryn L. Lunetta, James Luo, Ulysses J. Magalang, Michael C. Mahaney, Barry J. Make, Ani Manichaikul, Alisa K. Manning, JoAnn E. Manson, Lisa W. Martin, Melissa Marton, Susan Mathai, Rasika A. Mathias, Susanne May, Patrick F. McArdle, Merry‐Lynn McDonald, Sean McFarland, Stephen T. McGarvey, Daniel McGoldrick, Caitlin McHugh, Becky McNeil, Hao Mei, James B. Meigs, Vipin K. Menon, Luisa Mestroni, Ginger Metcalf, Deborah A. Meyers, Emmanuel Mignot, Julie Mikulla, Yuan‐I Min, Mollie Minear, Ryan L. Minster, Braxton D. Mitchell, Matt Moll, Zeineen Momin, May E. Montasser, Courtney G. Montgomery, Donna M. Muzny, Josyf C. Mychaleckyj, Girish N. Nadkarni, Rakhi P. Naik, Take Naseri, Pradeep Natarajan, Sergeï Nekhai, Sarah C. Nelson, Bonnie Neltner, Caitlin Nessner, Deborah A. Nickerson, Osuji Nkechinyere, Kari E. North, Jeff O’Connell, Tim O’Connor, Heather M. Ochs‐Balcom, Geoffrey Okwuonu, Allan I Pack, David T. Paik, James S. Pankow, George Papanicolaou, Gina M. Peloso, Juan M. Peralta, Marco Pérez, James A. Perry, Ulrike Peters, Patricia A. Peyser, Lawrence S. Phillips, Jacob Pleiness, Toni I. Pollin, Wendy S. Post, Julia Powers Becker, Meher Preethi Boorgula, Michael Preuß, Pankaj Qasba, Dandi Qiao, Zhaohui Qin, Nicholas Rafaels, Laura M. Raffield, Mahitha Rajendran, Ramachandran S. Vasan, D. C. Rao, Laura J. Rasmussen‐Torvik, Aakrosh Ratan, Susan Redline, Robert D. Reed, Catherine Reeves, Elizabeth A. Regan, Alex P. Reiner, Muagututi‘a Sefuiva Reupena, Kenneth Rice, Stephen S. Rich, Rébecca Robillard, Nicolas Robine, Dan M. Roden, Carolina Roselli, Jerome I. Rotter, Ingo Ruczinski, Alexi Runnels, Pamela Russell, Sarah Ruuska, Kathleen A. Ryan, Éster Cerdeira Sabino, Danish Saleheen, Shabnam Salimi, Sejal Salvi, Steven L. Salzberg, Kevin Sandow, Vijay G. Sankaran, Jireh Santibanez, Karen Schwander, David A. Schwartz, Frank C. Sciurba, Christine E. Seidman, Jonathan G. Seidman, Frédéric Sériès, Vivien Sheehan, Stephanie L. Sherman, Amol C. Shetty, Aniket Shetty, Wayne Hui-Heng Sheu, M. Benjamin Shoemaker, B. Silver, Edwin K. Silverman, Robert Skomro, Albert V. Smith, Jennifer A. Smith, J. G. Smith, Nicholas L. Smith, Tanja Smith, Sylvia Smoller, Beverly Snively, M Snyder, Nona Sotoodehnia, Adrienne M. Stilp, Garrett Storm, Elizabeth A. Streeten, Jessica Lasky‐Su, Jody Sylvia, Daniel Taliun, Hua Tang, Margaret A. Taub, Kent D. Taylor, Matthew R. Taylor, Simeon I. Taylor, Marilyn J. Telen, Machiko Threlkeld, Lesley F. Tinker, David Tirschwell, Sarah A. Tishkoff, Hemant K. Tiwari, Catherine Tong, Russell Tracy, Michael Y. Tsai, Dhananjay Vaidya, David Van Den Berg, Peter VandeHaar, Scott Vrieze, Tarik Walker, Robert L. Wallace, Avram Walts, Fei Fei Wang, Heming Wang, Jiongming Wang, Karol E. Watson, Jennifer Watt, Daniel E. Weeks, Joshua Weinstock, Bruce S. Weir, Scott T. Weiss, Lu‐Chen Weng, Jennifer Wessel, Cristen J. Willer, Kayleen Williams, Lawrence K. Williams, Carla G. Wilson, James G. Wilson, Lara Winterkorn, Quenna Wong, Joseph C. Wu, Huichun Xu, Lisa R. Yanek, Ivana V. Yang, Ketian Yu, Seyedeh M. Zekavat, Yingze Zhang, Snow Xueyan Zhao, Wei Zhao, Xiaofeng Zhu, Michael C. Zody, Sebastian Zoellner

Bibliographic record

VenueNature Communications · 2021

Typearticle

Languageen

FieldBiochemistry, Genetics and Molecular Biology

TopicGenetic Associations and Epidemiology

Canadian institutionsUniversity of SaskatchewanUniversité LavalUniversity of OttawaMcGill UniversityUniversity of CalgaryProvidence Health Care

FundersNational Institute of Environmental Health SciencesNational Heart, Lung, and Blood InstituteNational Institute on AgingU.S. Department of Health and Human ServicesNational Institutes of HealthNational Human Genome Research Institute

KeywordsPopulation stratificationFalse positive paradoxVariance (accounting)Genetic associationSample size determinationStatisticsGenome-wide association studyBiostatisticsBiologyComputational biologyReplicateComputer scienceData miningGeneticsMathematicsSingle-nucleotide polymorphismMedicineEpidemiologyGenotypeInternal medicine

DOI10.1038/s41467-021-23655-2

Abstract

fetched live from OpenAlex

In modern Whole Genome Sequencing (WGS) epidemiological studies, participant-level data from multiple studies are often pooled and results are obtained from a single analysis. We consider the impact of differential phenotype variances by study, which we term 'variance stratification'. Unaccounted for, variance stratification can lead to both decreased statistical power, and increased false positives rates, depending on how allele frequencies, sample sizes, and phenotypic variances vary across the studies that are pooled. We develop a procedure to compute variant-specific inflation factors, and show how it can be used for diagnosis of genetic association analyses on pooled individual level data from multiple studies. We describe a WGS-appropriate analysis approach, implemented in freely-available software, which allows study-specific variances and thereby improves performance in practice. We illustrate the variance stratification problem, its solutions, and the proposed diagnostic procedure, in simulations and in data from the Trans-Omics for Precision Medicine Whole Genome Sequencing Program (TOPMed), used in association tests for hemoglobin concentrations and BMI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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)0.019

metaresearch head score (Gemma)0.112

Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated

Candidate categoriesMetaresearch

Consensus categoriesnone

DomainCandidate signal: Methods · Consensus signal: none

Study designCandidate signal: Simulation or modeling · Consensus signal: none

GenreCandidate signal: Methods · Consensus signal: Methods

Teacher disagreement score0.981

Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

Category	Codex	Gemma
Metaresearch	0.019	0.112
Meta-epidemiology (narrow)	0.001	0.001
Meta-epidemiology (broad)	0.001	0.003
Bibliometrics	0.003	0.003
Science and technology studies	0.001	0.001
Scholarly communication	0.001	0.001
Open science	0.001	0.002
Research integrity	0.002	0.002
Insufficient payload (model declined to judge)	0.004	0.001

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 head0.063

GPT teacher head0.340

Teacher spread0.277 · how far apart the two teachers sit on this one work

Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Metaresearch

Study designSimulation or modeling

DomainMethods

GenreMethods

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

Citations21

Published2021

Admission routes1

Has abstractyes

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