المؤلفون: Abel Brodeur, Kevin Esterling, Jörg Ankel-Peters, Natália S. Bueno, Scott Desposato, Anna Dreber, Federica Genovese, Donald P. Green, Matthew Hepplewhite, Fernando Hoces de la Guardia, Magnus Johannesson, Andreas Kotsadam, Edward Miguel, Yamil R. Velez, Lauren Young

المصدر: Research & Politics, Vol 11 (2024)

مصطلحات موضوعية: Political science

الوصف: This article reviews and summarizes current reproduction and replication practices in political science. We first provide definitions for reproducibility and replicability. We then review data availability policies for 28 leading political science journals and present the results from a survey of editors about their willingness to publish comments and replications. We discuss new initiatives that seek to promote and generate high-quality reproductions and replications. Finally, we make the case for standards and practices that may help increase data availability, reproducibility, and replicability in political science.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2053-1680Test

الوصول الحر: https://doaj.org/article/fb8ea364602a43f2b75e6db1e131ea38Test

المؤلفون: Michael Gordon, Michael Bishop, Yiling Chen, Anna Dreber, Brandon Goldfedder, Felix Holzmeister, Magnus Johannesson, Yang Liu, Louisa Tran, Charles Twardy, Juntao Wang, Thomas Pfeiffer

المصدر: Royal Society Open Science, Vol 9, Iss 9 (2022)

مصطلحات موضوعية: preprinting, forecasting, science policy, Science

الوصف: Many publications on COVID-19 were released on preprint servers such as medRxiv and bioRxiv. It is unknown how reliable these preprints are, and which ones will eventually be published in scientific journals. In this study, we use crowdsourced human forecasts to predict publication outcomes and future citation counts for a sample of 400 preprints with high Altmetric score. Most of these preprints were published within 1 year of upload on a preprint server (70%), with a considerable fraction (45%) appearing in a high-impact journal with a journal impact factor of at least 10. On average, the preprints received 162 citations within the first year. We found that forecasters can predict if preprints will be published after 1 year and if the publishing journal has high impact. Forecasts are also informative with respect to Google Scholar citations within 1 year of upload on a preprint server. For both types of assessment, we found statistically significant positive correlations between forecasts and observed outcomes. While the forecasts can help to provide a preliminary assessment of preprints at a faster pace than traditional peer-review, it remains to be investigated if such an assessment is suited to identify methodological problems in preprints.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2054-5703Test

الوصول الحر: https://doaj.org/article/ba12a0eb04734f978ddace59d4850d81Test

المؤلفون: Balazs Aczel, Barnabas Szaszi, Gustav Nilsonne, Olmo R van den Akker, Casper J Albers, Marcel ALM van Assen, Jojanneke A Bastiaansen, Daniel Benjamin, Udo Boehm, Rotem Botvinik-Nezer, Laura F Bringmann, Niko A Busch, Emmanuel Caruyer, Andrea M Cataldo, Nelson Cowan, Andrew Delios, Noah NN van Dongen, Chris Donkin, Johnny B van Doorn, Anna Dreber, Gilles Dutilh, Gary F Egan, Morton Ann Gernsbacher, Rink Hoekstra, Sabine Hoffmann, Felix Holzmeister, Juergen Huber, Magnus Johannesson, Kai J Jonas, Alexander T Kindel, Michael Kirchler, Yoram K Kunkels, D Stephen Lindsay, Jean-Francois Mangin, Dora Matzke, Marcus R Munafò, Ben R Newell, Brian A Nosek, Russell A Poldrack, Don van Ravenzwaaij, Jörg Rieskamp, Matthew J Salganik, Alexandra Sarafoglou, Tom Schonberg, Martin Schweinsberg, David Shanks, Raphael Silberzahn, Daniel J Simons, Barbara A Spellman, Samuel St-Jean, Jeffrey J Starns, Eric Luis Uhlmann, Jelte Wicherts, Eric-Jan Wagenmakers

المصدر: eLife, Vol 10 (2021)

مصطلحات موضوعية: multi-analyst, metascience, statistical practice, science forum, expert consensus, analytical variability, Medicine, Science, Biology (General), QH301-705.5

الوصف: Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research.

وصف الملف: electronic resource

العلاقة: https://elifesciences.org/articles/72185Test; https://doaj.org/toc/2050-084XTest

الوصول الحر: https://doaj.org/article/2f33a9be099441798c65209457b94d1cTest

المؤلفون: David W Clark, Yukinori Okada, Kristjan H S Moore, Dan Mason, Nicola Pirastu, Ilaria Gandin, Hannele Mattsson, Catriona L K Barnes, Kuang Lin, Jing Hua Zhao, Patrick Deelen, Rebecca Rohde, Claudia Schurmann, Xiuqing Guo, Franco Giulianini, Weihua Zhang, Carolina Medina-Gomez, Robert Karlsson, Yanchun Bao, Traci M Bartz, Clemens Baumbach, Ginevra Biino, Matthew J Bixley, Marco Brumat, Jin-Fang Chai, Tanguy Corre, Diana L Cousminer, Annelot M Dekker, David A Eccles, Kristel R van Eijk, Christian Fuchsberger, He Gao, Marine Germain, Scott D Gordon, Hugoline G de Haan, Sarah E Harris, Edith Hofer, Alicia Huerta-Chagoya, Catherine Igartua, Iris E Jansen, Yucheng Jia, Tim Kacprowski, Torgny Karlsson, Marcus E Kleber, Shengchao Alfred Li, Ruifang Li-Gao, Anubha Mahajan, Koichi Matsuda, Karina Meidtner, Weihua Meng, May E Montasser, Peter J van der Most, Matthias Munz, Teresa Nutile, Teemu Palviainen, Gauri Prasad, Rashmi B Prasad, Tallapragada Divya Sri Priyanka, Federica Rizzi, Erika Salvi, Bishwa R Sapkota, Daniel Shriner, Line Skotte, Melissa C Smart, Albert Vernon Smith, Ashley van der Spek, Cassandra N Spracklen, Rona J Strawbridge, Salman M Tajuddin, Stella Trompet, Constance Turman, Niek Verweij, Clara Viberti, Lihua Wang, Helen R Warren, Robyn E Wootton, Lisa R Yanek, Jie Yao, Noha A Yousri, Wei Zhao, Adebowale A Adeyemo, Saima Afaq, Carlos Alberto Aguilar-Salinas, Masato Akiyama, Matthew L Albert, Matthew A Allison, Maris Alver, Tin Aung, Fereidoun Azizi, Amy R Bentley, Heiner Boeing, Eric Boerwinkle, Judith B Borja, Gert J de Borst, Erwin P Bottinger, Linda Broer, Harry Campbell, Stephen Chanock, Miao-Li Chee, Guanjie Chen, Yii-Der I Chen, Zhengming Chen, Yen-Feng Chiu, Massimiliano Cocca, Francis S Collins, Maria Pina Concas, Janie Corley, Giovanni Cugliari, Rob M van Dam, Anna Damulina, Maryam S Daneshpour, Felix R Day, Graciela E Delgado, Klodian Dhana, Alexander S F Doney, Marcus Dörr, Ayo P Doumatey, Nduna Dzimiri, S Sunna Ebenesersdóttir, Joshua Elliott, Paul Elliott, Ralf Ewert, Janine F Felix, Krista Fischer, Barry I Freedman, Giorgia Girotto, Anuj Goel, Martin Gögele, Mark O Goodarzi, Mariaelisa Graff, Einat Granot-Hershkovitz, Francine Grodstein, Simonetta Guarrera, Daniel F Gudbjartsson, Kamran Guity, Bjarni Gunnarsson, Yu Guo, Saskia P Hagenaars, Christopher A Haiman, Avner Halevy, Tamara B Harris, Mehdi Hedayati, David A van Heel, Makoto Hirata, Imo Höfer, Chao Agnes Hsiung, Jinyan Huang, Yi-Jen Hung, M Arfan Ikram, Anuradha Jagadeesan, Pekka Jousilahti, Yoichiro Kamatani, Masahiro Kanai, Nicola D Kerrison, Thorsten Kessler, Kay-Tee Khaw, Chiea Chuen Khor, Dominique P V de Kleijn, Woon-Puay Koh, Ivana Kolcic, Peter Kraft, Bernhard K Krämer, Zoltán Kutalik, Johanna Kuusisto, Claudia Langenberg, Lenore J Launer, Deborah A Lawlor, I-Te Lee, Wen-Jane Lee, Markus M Lerch, Liming Li, Jianjun Liu, Marie Loh, Stephanie J London, Stephanie Loomis, Yingchang Lu, Jian’an Luan, Reedik Mägi, Ani W Manichaikul, Paolo Manunta, Gísli Másson, Nana Matoba, Xue W Mei, Christa Meisinger, Thomas Meitinger, Massimo Mezzavilla, Lili Milani, Iona Y Millwood, Yukihide Momozawa, Amy Moore, Pierre-Emmanuel Morange, Hortensia Moreno-Macías, Trevor A Mori, Alanna C Morrison, Taulant Muka, Yoshinori Murakami, Alison D Murray, Renée de Mutsert, Josyf C Mychaleckyj, Mike A Nalls, Matthias Nauck, Matt J Neville, Ilja M Nolte, Ken K Ong, Lorena Orozco, Sandosh Padmanabhan, Gunnar Pálsson, James S Pankow, Cristian Pattaro, Alison Pattie, Ozren Polasek, Neil Poulter, Peter P Pramstaller, Lluis Quintana-Murci, Katri Räikkönen, Sarju Ralhan, Dabeeru C Rao, Wouter van Rheenen, Stephen S Rich, Paul M Ridker, Cornelius A Rietveld, Antonietta Robino, Frank J A van Rooij, Daniela Ruggiero, Yasaman Saba, Charumathi Sabanayagam, Maria Sabater-Lleal, Cinzia Felicita Sala, Veikko Salomaa, Kevin Sandow, Helena Schmidt, Laura J Scott, William R Scott, Bahareh Sedaghati-Khayat, Bengt Sennblad, Jessica van Setten, Peter J Sever, Wayne H-H Sheu, Yuan Shi, Smeeta Shrestha, Sharvari Rahul Shukla, Jon K Sigurdsson, Timo Tonis Sikka, Jai Rup Singh, Blair H Smith, Alena Stančáková, Alice Stanton, John M Starr, Lilja Stefansdottir, Leon Straker, Patrick Sulem, Gardar Sveinbjornsson, Morris A Swertz, Adele M Taylor, Kent D Taylor, Natalie Terzikhan, Yih-Chung Tham, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Annika Tillander, Russell P Tracy, Teresa Tusié-Luna, Ioanna Tzoulaki, Simona Vaccargiu, Jagadish Vangipurapu, Jan H Veldink, Veronique Vitart, Uwe Völker, Eero Vuoksimaa, Salma M Wakil, Melanie Waldenberger, Gurpreet S Wander, Ya Xing Wang, Nicholas J Wareham, Sarah Wild, Chittaranjan S Yajnik, Jian-Min Yuan, Lingyao Zeng, Liang Zhang, Jie Zhou, Najaf Amin, Folkert W Asselbergs, Stephan J L Bakker, Diane M Becker, Benjamin Lehne, David A Bennett, Leonard H van den Berg, Sonja I Berndt, Dwaipayan Bharadwaj, Lawrence F Bielak, Murielle Bochud, Mike Boehnke, Claude Bouchard, Jonathan P Bradfield, Jennifer A Brody, Archie Campbell, Shai Carmi, Mark J Caulfield, David Cesarini, John C Chambers, Giriraj Ratan Chandak, Ching-Yu Cheng, Marina Ciullo, Marilyn Cornelis, Daniele Cusi, George Davey Smith, Ian J Deary, Rajkumar Dorajoo, Cornelia M van Duijn, David Ellinghaus, Jeanette Erdmann, Johan G Eriksson, Evangelos Evangelou, Michele K Evans, Jessica D Faul, Bjarke Feenstra, Mary Feitosa, Sylvain Foisy, Andre Franke, Yechiel Friedlander, Paolo Gasparini, Christian Gieger, Clicerio Gonzalez, Philippe Goyette, Struan F A Grant, Lyn R Griffiths, Leif Groop, Vilmundur Gudnason, Ulf Gyllensten, Hakon Hakonarson, Anders Hamsten, Pim van der Harst, Chew-Kiat Heng, Andrew A Hicks, Hagit Hochner, Heikki Huikuri, Steven C Hunt, Vincent W V Jaddoe, Philip L De Jager, Magnus Johannesson, Åsa Johansson, Jost B Jonas, J Wouter Jukema, Juhani Junttila, Jaakko Kaprio, Sharon L. R. Kardia, Fredrik Karpe, Meena Kumari, Markku Laakso, Sander W van der Laan, Jari Lahti, Matthias Laudes, Rodney A Lea, Wolfgang Lieb, Thomas Lumley, Nicholas G Martin, Winfried März, Giuseppe Matullo, Mark I McCarthy, Sarah E Medland, Tony R Merriman, Andres Metspalu, Brian F Meyer, Karen L Mohlke, Grant W Montgomery, Dennis Mook-Kanamori, Patricia B Munroe, Kari E North, Dale R Nyholt, Jeffery R O’connell, Carole Ober, Albertine J Oldehinkel, Walter Palmas, Colin Palmer, Gerard G Pasterkamp, Etienne Patin, Craig E Pennell, Louis Perusse, Patricia A Peyser, Mario Pirastu, Tinca J. C. Polderman, David J Porteous, Danielle Posthuma, Bruce M Psaty, John D Rioux, Fernando Rivadeneira, Charles Rotimi, Jerome I Rotter, Igor Rudan, Hester M Den Ruijter, Dharambir K Sanghera, Naveed Sattar, Reinhold Schmidt, Matthias B Schulze, Heribert Schunkert, Robert A Scott, Alan R Shuldiner, Xueling Sim, Neil Small, Jennifer A Smith, Nona Sotoodehnia, E-Shyong Tai, Alexander Teumer, Nicholas J Timpson, Daniela Toniolo, David-Alexandre Tregouet, Tiinamaija Tuomi, Peter Vollenweider, Carol A Wang, David R Weir, John B Whitfield, Cisca Wijmenga, Tien-Yin Wong, John Wright, Jingyun Yang, Lei Yu, Babette S Zemel, Alan B Zonderman, Markus Perola, Patrik K. E. Magnusson, André G Uitterlinden, Jaspal S Kooner, Daniel I Chasman, Ruth J. F. Loos, Nora Franceschini, Lude Franke, Chris S Haley, Caroline Hayward, Robin G Walters, John R. B. Perry, Tōnu Esko, Agnar Helgason, Kari Stefansson, Peter K Joshi, Michiaki Kubo, James F Wilson

المصدر: Nature Communications, Vol 10, Iss 1, Pp 1-17 (2019)

مصطلحات موضوعية: Science

الوصف: Inbreeding depression has been observed in many different species, but in humans a systematic analysis has been difficult so far. Here, analysing more than 1.3 million individuals, the authors show that a genomic inbreeding coefficient (FROH) is associated with disadvantageous outcomes in 32 out of 100 traits tested.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2041-1723Test

الوصول الحر: https://doaj.org/article/701d2fda0b6343e98f5974339f0a8eb7Test

المؤلفون: Domenico Viganola, Grant Buckles, Yiling Chen, Pablo Diego-Rosell, Magnus Johannesson, Brian A. Nosek, Thomas Pfeiffer, Adam Siegel, Anna Dreber

المصدر: Royal Society Open Science, Vol 8, Iss 7 (2021)

مصطلحات موضوعية: prediction markets, peer beliefs, hypothesis, Science

الوصف: There is evidence that prediction markets are useful tools to aggregate information on researchers' beliefs about scientific results including the outcome of replications. In this study, we use prediction markets to forecast the results of novel experimental designs that test established theories. We set up prediction markets for hypotheses tested in the Defense Advanced Research Projects Agency's (DARPA) Next Generation Social Science (NGS2) programme. Researchers were invited to bet on whether 22 hypotheses would be supported or not. We define support as a test result in the same direction as hypothesized, with a Bayes factor of at least 10 (i.e. a likelihood of the observed data being consistent with the tested hypothesis that is at least 10 times greater compared with the null hypothesis). In addition to betting on this binary outcome, we asked participants to bet on the expected effect size (in Cohen's d) for each hypothesis. Our goal was to recruit at least 50 participants that signed up to participate in these markets. While this was the case, only 39 participants ended up actually trading. Participants also completed a survey on both the binary result and the effect size. We find that neither prediction markets nor surveys performed well in predicting outcomes for NGS2.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2054-5703Test

الوصول الحر: https://doaj.org/article/a0020a75602147c19d675c9474af04a3Test

المؤلفون: Michael Gordon, Domenico Viganola, Anna Dreber, Magnus Johannesson, Thomas Pfeiffer

المصدر: PLoS ONE, Vol 16, Iss 4, p e0248780 (2021)

مصطلحات موضوعية: Medicine, Science

الوصف: The reproducibility of published research has become an important topic in science policy. A number of large-scale replication projects have been conducted to gauge the overall reproducibility in specific academic fields. Here, we present an analysis of data from four studies which sought to forecast the outcomes of replication projects in the social and behavioural sciences, using human experts who participated in prediction markets and answered surveys. Because the number of findings replicated and predicted in each individual study was small, pooling the data offers an opportunity to evaluate hypotheses regarding the performance of prediction markets and surveys at a higher power. In total, peer beliefs were elicited for the replication outcomes of 103 published findings. We find there is information within the scientific community about the replicability of scientific findings, and that both surveys and prediction markets can be used to elicit and aggregate this information. Our results show prediction markets can determine the outcomes of direct replications with 73% accuracy (n = 103). Both the prediction market prices, and the average survey responses are correlated with outcomes (0.581 and 0.564 respectively, both p < .001). We also found a significant relationship between p-values of the original findings and replication outcomes. The dataset is made available through the R package "pooledmaRket" and can be used to further study community beliefs towards replications outcomes as elicited in the surveys and prediction markets.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/1932-6203Test

الوصول الحر: https://doaj.org/article/999f585048464807a021a167c9a6a6abTest

المؤلفون: Michael Gordon, Domenico Viganola, Michael Bishop, Yiling Chen, Anna Dreber, Brandon Goldfedder, Felix Holzmeister, Magnus Johannesson, Yang Liu, Charles Twardy, Juntao Wang, Thomas Pfeiffer

المصدر: Royal Society Open Science, Vol 7, Iss 7 (2020)

مصطلحات موضوعية: science policy, replication, forecasting, Science

الوصف: The Defense Advanced Research Projects Agency (DARPA) programme ‘Systematizing Confidence in Open Research and Evidence' (SCORE) aims to generate confidence scores for a large number of research claims from empirical studies in the social and behavioural sciences. The confidence scores will provide a quantitative assessment of how likely a claim will hold up in an independent replication. To create the scores, we follow earlier approaches and use prediction markets and surveys to forecast replication outcomes. Based on an initial set of forecasts for the overall replication rate in SCORE and its dependence on the academic discipline and the time of publication, we show that participants expect replication rates to increase over time. Moreover, they expect replication rates to differ between fields, with the highest replication rate in economics (average survey response 58%), and the lowest in psychology and in education (average survey response of 42% for both fields). These results reveal insights into the academic community's views of the replication crisis, including for research fields for which no large-scale replication studies have been undertaken yet.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2054-5703Test

الوصول الحر: https://doaj.org/article/3085a2213c4d46d7aa24aee94aec7e64Test

المؤلفون: M. C. Weinstein, Bernie O’Brien, John Hornberger, Joseph Jackson, Magnus Johannesson, Chris Mccabe, Bryan R. Luce, A. V. Pavlysh, A. S. Kolbin

المصدر: Качественная клиническая практика, Vol 0, Iss 2, Pp 19-28 (2018)

مصطلحات موضوعية: математическое моделирование, оценка технологий здравоохранения, принятие решений, валидация моделей, анализ чувствительности, mathematical modeling, health technology assessment, decision-making, model validation, sensitivity analysis, Medical technology, R855-855.5, Pharmacy and materia medica, RS1-441

الوصف: Principles of Good Practice for Decision Analytic Modeling in Health-Care Evaluation: Report of the ISPOR Task Force on Good Research Practices - Modeling Studies Abstract. Objectives: Mathematical modeling is used widely in economic evaluations of pharmaceuticals and other healthcare technologies. Users of models in government and the private sector need to be able to evaluate the quality of models according to scientific criteria of good practice. This report describes the consensus of a task force convened to provide modelers with guidelines for conducting and reporting modeling studies. Methods: The task force was appointed with the advice and consent of the Board of Directors of ISPOR. Members were experienced developers or users of models, worked in academia and industry, and came from several countries in North America and Europe. The task force met on three occasions, conducted frequent correspondence and exchanges of drafts by electronic mail, and solicited comments on three drafts from a core group of external reviewers and more broadly from the membership of ISPOR. Results: Criteria for assessing the quality of models fell into three areas: model structure, data used as inputs to models, and model validation. Several major themes cut across these areas. Models and their results should be represented as aids to decision making, not as statements of scientific fact; therefore, it is inappropriate to demand that models be validated prospectively before use. However, model assumptions regarding causal structure and parameter estimates should be continually assessed against data, and models should be revised accordingly. Structural assumptions and parameter estimates should be reported clearly and explicitly, and opportunities for users to appreciate the conditional relationship between inputs and outputs should be provided through sensitivity analyses. Conclusions: Model-based evaluations are a valuable resource for health-care decision makers. It is the responsibility of model developers to conduct modeling studies according to the best practicable standards of quality and to communicate results with adequate disclosure of assumptions and with the caveat that conclusions are conditional upon the assumptions and data on which the model is built.

وصف الملف: electronic resource

العلاقة: https://www.clinvest.ru/jour/article/view/14Test; https://doaj.org/toc/2588-0519Test; https://doaj.org/toc/2618-8473Test

الوصول الحر: https://doaj.org/article/e50c6ac6c1b74e5390ae2194e3779cb6Test

المؤلفون: Adam Altmejd, Anna Dreber, Eskil Forsell, Juergen Huber, Taisuke Imai, Magnus Johannesson, Michael Kirchler, Gideon Nave, Colin Camerer

المصدر: PLoS ONE, Vol 14, Iss 12, p e0225826 (2019)

مصطلحات موضوعية: Medicine, Science

الوصف: We measure how accurately replication of experimental results can be predicted by black-box statistical models. With data from four large-scale replication projects in experimental psychology and economics, and techniques from machine learning, we train predictive models and study which variables drive predictable replication. The models predicts binary replication with a cross-validated accuracy rate of 70% (AUC of 0.77) and estimates of relative effect sizes with a Spearman ρ of 0.38. The accuracy level is similar to market-aggregated beliefs of peer scientists [1, 2]. The predictive power is validated in a pre-registered out of sample test of the outcome of [3], where 71% (AUC of 0.73) of replications are predicted correctly and effect size correlations amount to ρ = 0.25. Basic features such as the sample and effect sizes in original papers, and whether reported effects are single-variable main effects or two-variable interactions, are predictive of successful replication. The models presented in this paper are simple tools to produce cheap, prognostic replicability metrics. These models could be useful in institutionalizing the process of evaluation of new findings and guiding resources to those direct replications that are likely to be most informative.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/1932-6203Test

الوصول الحر: https://doaj.org/article/8bd9cacff3e64798b9387e61ea2df3c2Test

المؤلفون: Ronald de Vlaming, Aysu Okbay, Cornelius A Rietveld, Magnus Johannesson, Patrik K E Magnusson, André G Uitterlinden, Frank J A van Rooij, Albert Hofman, Patrick J F Groenen, A Roy Thurik, Philipp D Koellinger

المصدر: PLoS Genetics, Vol 13, Iss 1, p e1006495 (2017)

مصطلحات موضوعية: Genetics, QH426-470

الوصف: Large-scale genome-wide association results are typically obtained from a fixed-effects meta-analysis of GWAS summary statistics from multiple studies spanning different regions and/or time periods. This approach averages the estimated effects of genetic variants across studies. In case genetic effects are heterogeneous across studies, the statistical power of a GWAS and the predictive accuracy of polygenic scores are attenuated, contributing to the so-called 'missing heritability'. Here, we describe the online Meta-GWAS Accuracy and Power (MetaGAP) calculator (available at www.devlaming.eu) which quantifies this attenuation based on a novel multi-study framework. By means of simulation studies, we show that under a wide range of genetic architectures, the statistical power and predictive accuracy provided by this calculator are accurate. We compare the predictions from the MetaGAP calculator with actual results obtained in the GWAS literature. Specifically, we use genomic-relatedness-matrix restricted maximum likelihood to estimate the SNP heritability and cross-study genetic correlation of height, BMI, years of education, and self-rated health in three large samples. These estimates are used as input parameters for the MetaGAP calculator. Results from the calculator suggest that cross-study heterogeneity has led to attenuation of statistical power and predictive accuracy in recent large-scale GWAS efforts on these traits (e.g., for years of education, we estimate a relative loss of 51-62% in the number of genome-wide significant loci and a relative loss in polygenic score R2 of 36-38%). Hence, cross-study heterogeneity contributes to the missing heritability.

وصف الملف: electronic resource

العلاقة: http://europepmc.org/articles/PMC5240919?pdf=renderTest; https://doaj.org/toc/1553-7390Test; https://doaj.org/toc/1553-7404Test

الوصول الحر: https://doaj.org/article/39f9049b84b84185a20acd38803b72daTest