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1. A genealogical interpretation of fixed and random effects models of complex traits

Author

Lee, Hanbin

Subjects
Quantitative Biology - Populations and Evolution, Quantitative Biology - Genomics
Abstract

In the analysis of complex traits, genetic effects are frequently modelled as either fixed or random effects. Such assumptions serve as a foundation of defining heritability and relatedness using genome-wide single nucleotide polymorphism (SNP) markers. In this work, I propose a genealogical framework connecting the two assumptions conditional on the ancestral recombination graph (ARG). It turns out that the reference time point in which the probability is defined determines whether the effect of a variant to behave as either a fixed or random effect. This lays a connection between the PC regression and linear mixed model (LMM) for genetic association study. The framework induces a genetic relatedness matrix (GRM) in which the elements are a function of the time to the recent common ancestor. Subsequently, a novel trait variance decomposition respect to the regions sharing a common genealogy is followed. The variance decomposition then provides a natural means to define heritability and a potential method for gene mapping., Comment: 8 pages

Published
2023

3. Disentangling Linkage and Population Structure in Association Mapping

Author

Lee, Hanbin and Lee, Moo Hyuk

Subjects
Quantitative Biology - Populations and Evolution
Abstract

Genome-wide association study (GWAS) tests single nucleotide polymorphism (SNP) markers across the genome to localize the underlying causal variant of a trait. Because causal variants are seldom observed directly, a surrogate model based on genotyped markers are widely considered. Although many methods estimating the parameters of the surrogate model have been proposed, the connection between the surrogate model and the true causal model is yet investigated. In this work, we establish the connection between the surrogate model and the true causal model. The connection shows that population structure is accounted in GWAS by modelling the variant of interest and not the trait. Such observation explains how environmental confounding can be partially corrected using genetic covariates and why the previously claimed connection between PC correction and linear mixed models is incorrect., Comment: 11 pages, 1 figure

Published
2023

4. Suffering from Vaccines or from Government? : Partisan Bias in COVID-19 Vaccine Adverse Events Coverage

Author

Kang, TaeYoung and Lee, Hanbin

Subjects
Computer Science - Computation and Language, Computer Science - Computers and Society, Computer Science - Social and Information Networks
Abstract

Vaccine adverse events have been presumed to be a relatively objective measure that is immune to political polarization. The real-world data, however, shows the correlation between presidential disapproval ratings and the subjective severity of adverse events. This paper investigates the partisan bias in COVID vaccine adverse events coverage with language models that can classify the topic of vaccine-related articles and the political disposition of news comments. Based on 90K news articles from 52 major newspaper companies, we found that conservative media are inclined to report adverse events more frequently than their liberal counterparts, while the coverage itself was statistically uncorrelated with the severity of real-world adverse events. The users who support the conservative opposing party were more likely to write the popular comments from 2.3K random sampled articles on news platforms. This research implies that bipartisanship can still play a significant role in forming public opinion on the COVID vaccine even after the majority of the population's vaccination, Comment: 5 pages, 5 figures, 2 tables

Published
2022

10. More Than 50 Percent Reduction in LDL Cholesterol in Patients With Target LDL <70 mg/dL After a Stroke

Author

Amarenco, Pierre, Lavallée, Philippa C., Kim, Jong S., Labreuche, Julien, Charles, Hugo, Giroud, Maurice, Lee, Byung-Chul, Mahagne, Marie-Hélène, Meseguer, Elena, Nighoghossian, Norbert, Steg, Philippe Gabriel, Vicaut, Éric, Bruckert, Eric, Kim, Jong S, Touboul, Pierre-Jean, Leys, Didier, Béjot, Yannick, Pico, Fernando, Touzé, Emmanuel, Ducrocq, Gregory, Abtan, Jérémy, Varenne, Olivier, Touboul, Pierre-Jean, Kemmel, Agnes, Syana, Fausta, Ledra, Manele, Nagasara, Tharani, Ledjeroud, Mervette, Samia, Bahous, Hadia, Hafirassou, Hazare, Benyoub, Jaghouni, Ikrame El, Yelles, Nessima, Zemouri, Sofia, Ladjeroud, Mervette, Kerai, Salim, In, YunJeong, Hobeanu, Cristina, Guidoux, Celine, Cabrejo, Lucie, Lapergue, Bertrand, Sabben, Candice, Gonzalez-Valcarcel, Jaime, Rigual, Ricardo, Sirimarco, Gaia, Martin-Bechet, Anna, Viedma, Elena, Avram, Ioan, Samson, Yves, Rosso, Charlotte, Crozier, Sophie, Leder, Sara, Léger, Anne, Deltour, Sandrine, Mutlu, Gurkan, Yger, Marion, Zavanone, Chiara, Baronnet, Flore, Pires, Christine, Lapergue, Bertrand, Wang, Adrien, Evrard, Serge, Tchikviladze, Maya, Bourdain, Frédéric, Lopez, Delphine, Pico, Fernando, de la Tour, Laetitia Bayon, Chadenat, Marie-Laure, Duong, Duc Long, Genty, Solène, Hirel, Catherine, Mutlu, Gurkan, Nifle, Chantal, Servan, Jérôme, Stanciu, Daniela, Sudacevschi, Veronica, Tir, Mélissa, Troussière, Anne-Cécile, Yeung, Jennifer, Zeghoudi, Anne-Céline, Tidafi-Bayou, Ikram, Lachaud, Sylvain, Cho, Tae-Hee, Mechtouff, Laura, Ritzenthaller, Thomas, Derex, Laurent, Albanesi, Carlo, Ong, Elodie, Benoit, Amandine, Berhoune, Nadia, Felix, Sandra, Esteban-Mader, Maud, Sibon, Igor, Kazadi, Annabelle, Rouanet, François, Renou, Pauline, Debruxelles, Sabrina, Poli, Mathilde, Sagnier, Sharmila, Mas, Jean-Louis, Domigo, Valérie, Lamy, Catherine, Bodiguel, Eric, Grimaud, Jérôme, Bohotin, Valentin, Obadia, Michael, Sabben, Candice, Morvan, Erwan, Rodier, Gilles, Vadot, Wilfried, Hénon, Hilde, Cordonnier, Charlotte, Dumont, Frédéric, Bodenant, Marie, Lucas, Christian, Moulin, Solène, Dequatre, Nelly, Alamowitch, Sonia, Muresan, Jean-Paul, Drouet, Thomas, Gallea, Magalie, Dalloz, Marie-Amélie, Delorme, Stephen, Yger, Marion, Béjot, Yannick, Loisel, Philippe, Bonnin, Carine, Bernigal, Virginie, Osseby, Guy Victor, Hervieu-BègueMarsac, Marie, Garnier, Pierre, Accassat, Sandrine, Epinat, Magali, Varvat, Jérôme, Marinescu, Doïna, Triquenot-Bagan, Aude, Ozkul- Wermester, Ozlem, Philippeau, Frédéric, Olaru, Angel, Vieillart, Anne, Lannuzel, Annie, Demoly, Alice, Wolff, Valérie, Diaconu, Mihaela, Bataillard, Marc, Montoro, Francisco Macian, Faugeras, Frédéric, Gimenez, Laeticia, Abdallah-Lebeau, Françoise, Timsit, Serge, Viakhireva-Dovganyuk, Irina, Tirel-Badets, Anne, Merrien, François-Mathias, Goas, Philippe, Rouhart, François, Jourdain, Aurore, Guillon, Benoit, Hérissson, Fanny, Sevin-Allouet, Mathieu, Nasr, Nathalie, Olivot, Jean-Marc, Lecluse, Alderic, Marc, Guillaume, Touzé, Emmanuel, de la Sayette, Vincent, Apoil, Marion, Lin, Li, Cogez, Julien, Guettier, Sophie, Godefroy, Olivier, Lamy, Chantal, Bugnicourt, Jean-Marc, Taurin, Grégory, Mérienne, Marc, Gere, Julien, Chessak, Anne-Marie, Habet, Tarik, Ferrier, Anna, Bourgois, Nathalie, Minier, Dominique, Caillier-Minier, Marie, Contégal- Callier, Fabienne, Vion, Philippe, Vaschalde, Yvan, Amrani, Mohammed El, Emilie, Zuber, Mathieu, Bruandet, Marie, Join- Lambert, Claire, Garcia, Pierre-Yves, Serre, Isabelle, Faucheux, Jean-Marc, Radji, Fatia, Leca-Radu, Elena, Debroucker, Thomas, Cumurcuc, Rodica, Cakmak, Serkan, Peysson, Stéphane, Ellie, Emmanuel, Bernady, Patricia, Moulin, Thierry, Montiel, Paola, Revenco, Eugeniu, Decavel, Pierre, Medeiros, Elisabeth, Bouveret, Myriam, Louchart, Pierre, Vaduva, Claudia, Couvreur, Grégory, Sartori, Eric, Carpentier, Alnajar, Levasseur, Michèle, Louchart, Pierre, Faucheux, Jean-Marc, Neau, Philippe, Vandamme, Xavier, Meresse, Isabelle, Stantescu, Bataillard, Marc, Ozsancak, Canan, Beauvais, Katell, Auzou, Pascal, Amevigbe, Joséphine, Vuillemet, Francis, Dugay-Arentz, Marie-Hélène, Carelli, Gabriela, Martinez, Mikel, Maillet-Vioud, Marcel, Escaillas, Jean-Pierre, Chapuis, Stéphane, Tardy, Jean, Manchon, Eric, Varnet, Olivier, Kim, Yong-Jae, Chang, Yoonkyung, Song, Tae-Jin, Kim, Jong Sung, Han, Jung-Hoon, Noh, Kyung Chul, Lee, Eun-Jae, Kang, Dong-Wha, Kwon, Sun Uck, Kwon, Boseoung, Park, Seongho, Lee, Dongwhane, Kwon, Hyuk Sung, Jeong, Daeun, Lee, MinHwan, Kim, Joonggoo, Lee, Hanbin, Nam, Hyo Jung, Lee, Sang Hun, Kim, Bum Joon, Cha, Jae-kwan, Kim, DaeHyun, Kim, Rae Young, Sohn, Sang Wuk, Shim, Dong-Hyun, Lee, Hyungjin, Nah, Hyun-Wook, Sung, Sang Min, Lee, Kyung Bok, Yoon Lee, Jeong, Yoon, Jee Eun, Kim, Eung-Gyu, Seo, Jung Hwa, Kim, Yong-Won, Hwang, Yangha, Park, Man Seok, Kim, Joon-Tae, Choi, Kang-Ho, Nam, Hyo Suk, Heo, Ji Hoe, Kim, Young Dae, Hwang, In Gun, Park, Hyung Jong, Kim, Kyoung Sub, Baek, Jang Hyun, Song, Dong Beom, Yoo, Joon Sang, Park, Jong-Moo, Kwon, Ohyun, Lee, Woong-Woo, Lee, Jung-Ju, Kang, Kyusik, Kim, Byung Kun, Lim, Jae-Sung, Oh, Mi Sun, Yu, Kyung-Ho, Hong, Bora, Jang, Mihoon, Jang, Seyoung, Jin, Jung Eun, Kim, Jei, Jeong, Hye Seon, Hong, Keun Sik, Park, Hong Kyun, Cho, Yong Jin, Bang, Oh Young, Seo, Woo-Keun, and Chung, Jongwon

Published
2023
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13. Glaucoma

Author

Lee, Richard M. H., Liu, Christopher, Lee, Hanbin, Liu, Christopher, editor, and Lee, Hanbin, editor

Published
2020
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17. Pseudobulk with proper offsets has the same statistical properties as generalized linear mixed models in single-cell case-control studies.

Author

Lee, Hanbin and Han, Buhm

Subjects
*GENE expression, *RNA sequencing, *CASE-control method, *MOTIVATION (Psychology), *COMPUTER software
Abstract

Motivation Generalized linear mixed models (GLMMs), such as the negative-binomial or Poisson linear mixed model, are widely applied to single-cell RNA sequencing data to compare transcript expression between different conditions determined at the subject level. However, the model is computationally intensive, and its relative statistical performance to pseudobulk approaches is poorly understood. Results We propose offset-pseudobulk as a lightweight alternative to GLMMs. We prove that a count-based pseudobulk equipped with a proper offset variable has the same statistical properties as GLMMs in terms of both point estimates and standard errors. We confirm our findings using simulations based on real data. Offset-pseudobulk is substantially faster (>×10) and numerically more stable than GLMMs. Availability and implementation Offset pseudobulk can be easily implemented in any generalized linear model software by tweaking a few options. The codes can be found at https://github.com/hanbin973/pseudobulk_is_mm. [ABSTRACT FROM AUTHOR]

Published
2024
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18. Outcomes of Descemet's membrane endothelial keratoplasty performed in combination with, before, or after cataract surgery in Fuchs' endothelial dystrophy: A review of the literature and meta-analysis

Author

Mukhija, Ritika, Henein, Christin, Lee, Hanbin, Phee, Jaewon, and Nanavaty, Mayank

Subjects
Visual acuity -- Analysis, Cornea -- Transplantation, Cataract -- Surgery, Health
Abstract

Byline: Ritika. Mukhija, Christin. Henein, Hanbin. Lee, Jaewon. Phee, Mayank. Nanavaty This review aimed to compare the outcomes of Descemet's membrane endothelial keratoplasty (DMEK) in combination with (category 1), before [...]

Published
2023

28. Benefit of Targeting a LDL (Low-Density Lipoprotein) Cholesterol <70 mg/dL During 5 Years After Ischemic Stroke

Author

Amarenco, Pierre, Kim, Jong S., Labreuche, Julien, Charles, Hugo, Giroud, Maurice, Lee, Byung-Chul, Mahagne, Marie-Hélène, Nighoghossian, Norbert, Gabriel Steg, Philippe, Vicaut, Éric, Bruckert, Eric, Touboul, Pierre-Jean, Leys, Didier, Béjot, Yannick, Lavallée, Philippa, Pico, Fernando, Touzé, Emmanuel, Ducrocq, Gregory, Abtan, Jérémy, Varenne, Olivier, Touboul, Pierre-Jean, Kemmel, Agnes, Syana, Fausta, Ledra, Manele, Nagasara, Tharani, Ledjeroud, Mervette, Samia, Bahous, Hadia, Hafirassou, Hazare, Benyoub, El Jaghouni, Ikrame, Yelles, Nessima, Zemouri, Sofia, Ladjeroud, Mervette, Kerai, Salim, In, Yun Jeong, Meseguer, Elena, Lavallée, Philippa C, Hobeanu, Cristina, Guidoux, Celine, Cabrejo, Lucie, Lapergue, Bertrand, Sabben, Candice, Gonzalez-Valcarcel, Jaime, Rigual, Ricardo, Sirimarco, Gaia, Martin-Bechet, Anna, Viedma, Elena, Avram, Ioan, Samson, Yves, Rosso, Charlotte, Crozier, Sophie, Leder, Sara, Léger, Anne, Deltour, Sandrine, Mutlu, Gurkan, Yger, Marion, Zavanone, Chiara, Baronnet, Flore, Pires, Christine, Lapergue, Bertrand, Wang, Adrien, Evrard, Serge, Tchikviladze, Maya, Bourdain, Frédéric, Lopez, Delphine, Pico, Fernando, de la Tour, Laetitia Bayon, Chadenat, Marie-Laure, Duong, Duc Long, Genty, Solène, Hirel, Catherine, Mutlu, Gurkan, Nifle, Chantal, Servan, Jérôme, Stanciu, Daniela, Sudacevschi, Veronica, Tir, Mélissa, Troussière, Anne-Cécile, Yeung, Jennifer, Zeghoudi, Anne-Céline, Tidafi-Bayou, Ikram, Lachaud, Sylvain, Cho, Tae-Hee, Mechtouff, Laura, Ritzenthaller, Thomas, Derex, Laurent, Albanesi, Carlo, Ong, Elodie, Benoit, Amandine, Berhoune, Nadia, Felix, Sandra, Esteban-Mader, Maud, Sibon, Igor, Kazadi, Annabelle, Rouanet, François, Renou, Pauline, Debruxelles, Sabrina, Poli, Mathilde, Sagnier, Sharmila, Mas, Jean-Louis, Domigo, Valérie, Lamy, Catherine, Bodiguel, Eric, Grimaud, Jérôme, Bohotin, Valentin, Obadia, Michael, Sabben, Candice, Morvan, Erwan, Rodier, Gilles, Vadot, Wilfried, Hénon, Hilde, Cordonnier, Charlotte, Dumont, Frédéric, Bodenant, Marie, Lucas, Christian, Moulin, Solène, Dequatre, Nelly, Alamowitch, Sonia, Muresan, Jean-Paul, Drouet, Thomas, Gallea, Magalie, Dalloz, Marie-Amélie, Delorme, Stephen, Yger, Marion, Béjot, Yannick, Loisel, Philippe, Bonnin, Carine, Bernigal, Virginie, Osseby, Guy Victor, Marsac, Marie Hervieu-Bègue, Garnier, Pierre, Accassat, Sandrine, Epinat, Magali, Varvat, Jérôme, Marinescu, Doïna, Triquenot-Bagan, Aude, Ozkul-Wermester, Ozlem, Philippeau, Frédéric, Olaru, Angel, Vieillart, Anne, Lannuzel, Annie, Demoly, Alice, Wolff, Valérie, Diaconu, Mihaela, Bataillard, Marc, Montoro, Francisco Macian, Faugeras, Frédéric, Gimenez, Laeticia, Abdallah-Lebeau, Françoise, Timsit, Serge, Viakhireva-Dovganyuk, Irina, Tirel-Badets, Anne, Merrien, François-Mathias, Goas, Philippe, Rouhart, François, Jourdain, Aurore, Guillon, Benoit, Hérissson, Fanny, Sevin-Allouet, Mathieu, Nasr, Nathalie, Olivot, Jean-Marc, Lecluse, Alderic, Marc, Guillaume, Touzé, Emmanuel, de la Sayette, Vincent, Apoil, Marion, Lin, Li, Cogez, Julien, Guettier, Sophie, Godefroy, Olivier, Lamy, Chantal, Bugnicourt, Jean-Marc, Taurin, Grégory, Mérienne, Marc, Gere, Julien, Chessak, Anne-Marie, Habet, Tarik, Ferrier, Anna, Bourgois, Nathalie, Minier, Dominique, Caillier-Minier, Marie, Contégal-Callier, Fabienne, Vion, Philippe, Vaschalde, Yvan, El Amrani, Emilie, Mohammed, Zuber, Mathieu, Bruandet, Marie, Join-Lambert, Claire, Garcia, Pierre-Yves, Serre, Isabelle, Faucheux, Jean-Marc, Radji, Fatia, Leca-Radu, Elena, Debroucker, Thomas, Cumurcuc, Rodica, Cakmak, Serkan, Peysson, Stéphane, Ellie, Emmanuel, Bernady, Patricia, Moulin, Thierry, Montiel, Paola, Revenco, Eugeniu, Decavel, Pierre, Medeiros, Elisabeth, Bouveret, Myriam, Louchart, Pierre, Vaduva, Claudia, Couvreur, Grégory, Sartori, Eric, Alnajar-Carpentier, Eric, Levasseur, Michèle, Louchart, Pierre, Neau, Jean-Philippe, Vandamme, Xavier, Meresse, Isabelle, Stantescu, Bataillard, Marc, Ozsancak, Canan, Beauvais, Katell, Auzou, Pascal, Amevigbe, Joséphine, Vuillemet, Francis, Dugay-Arentz, Marie-Hélène, Carelli, Gabriela, Martinez, Mikel, Maillet-Vioud, Marcel, Escaillas, Jean-Pierre, Chapuis, Stéphane, Tardy, Jean, Manchon, Eric, Varnet, Olivier, Kim, Yong-Jae, Chang, Yoonkyung, Song, Tae-Jin, Han, Jung-Hoon, Noh, Kyung Chul, Lee, Eun-Jae, Kang, Dong-Wha, Kwon, Sun Uck, Kwon, Boseoung, Park, Seongho, Lee, Dongwhane, Kwon, Hyuk Sung, Jeong, Daeun, Lee, MinHwan, Kim, Joonggoo, Lee, Hanbin, Nam, Hyo Jung, Lee, Sang Hun, Kim, Bum Joon, Cha, Jae-kwan, Kim, DaeHyun, Young Kim, Rae, Sohn, Sang Wuk, Shim, Dong-Hyun, Lee, Hyungjin, Nah, Hyun-Wook, Sung, Sang Min, Lee, Kyung Bok, Lee, Jeong Yoon, Yoon, Jee Eun, Kim, Eung-Gyu, Seo, Jung Hwa, Kim, Yong-Won, Hwang, Yangha, Park, Man Seok, Kim, Joon-Tae, Choi, Kang-Ho, Nam, Hyo Suk, Heo, Ji Hoe, Kim, Young Dae, Hwang, In Gun, Park, Hyung Jong, Kim, Kyoung Sub, Baek, Jang Hyun, Song, Dong Beom, Yoo, Joon Sang, Park, Jong-Moo, Kwon, Ohyun, Lee, Woong-Woo, Lee, Jung-Ju, Kang, Kyusik, Kim, Byung Kun, Lim, Jae-Sung, Oh, Mi Sun, Yu, Kyung-Ho, Hong, Bora, Jang, Mihoon, Jang, Seyoung, Jin, Jung Eun, Kim, Jei, Jeong, Hye Seon, Hong, Keun Sik, Park, Hong Kyun, Cho, Yong Jin, Bang, Oh Young, Seo, Woo-Keun, and Chung, Jongwon

Published
2020
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37. Economics of Food Attributes Linked to Farm Practices

Author

Lee, Hanbin and Lee, Hanbin

Abstract

This dissertation explores the economics of food attributes linked to production practices. I consider two distinct farm commodities: pork and carrots. The pork study models and simulates the economic consequences of prospective retail regulations that restrict farm practices used to produce pork products sold within the regulated jurisdiction. The carrot study estimates econometrically retail demand parameters for carrot attributes linked to farm production and processing practices. In the pork study, I analyze the controversial regulations on sales of pork products in California that were mandated by the voter-approved Proposition 12 (Prop 12). Prop 12 requires uncooked pork cuts sold in California must originate from hogs whose mother sows were housed as set forth in Prop 12 and accompanying regulations. As of August 2022, implementation of Prop 12 is on hold pending outcomes of state and federal legal challenges. In this dissertation, I develop a detailed, empirical economic simulation model of the implications of Prop 12 for quantities and prices of hogs and pork. Simulation results show that, using a range of values for applicable parameters, compliant farrowing operations will incur about 4% higher costs, pork processors and marketers also incur added costs, and California retail prices of covered cuts of pork will rise by about 7%. California consumers of covered cuts of pork lose about $260 million annually. Hog producers who comply with Prop 12 standards in order to supply the California market will, on average, receive greater profits. Market impacts are minimal for hog producers who choose not to comply with Prop 12 standards and for prices and quantities of pork sold outside California. The second part of this dissertation investigates consumer demand for carrot product attributes that are linked to two sets of production practices: organic farming and fresh-cut processing practices. The demand for food product attributes tied to production practices is

Published
2022

41. Formation of Hierarchical Pyramid-structured Si with Nanoholes by Using Thermally Dewetted Ag Thin Films

Author

Kim Hyo Jung and Lee Hanbin

Subjects
010302 applied physics, Morphology (linguistics), business.industry, General Physics and Astronomy, 02 engineering and technology, 021001 nanoscience & nanotechnology, 01 natural sciences, Isotropic etching, Contact angle, Nanopore, Etching (microfabrication), 0103 physical sciences, Optoelectronics, Wafer, Thin film, 0210 nano-technology, business, Pyramid (geometry)
Abstract

Si surface texturing generally requires an etching process to improve the anti-reflection and the self-cleaning properties of the surface. Among the various etching techniques for surface texturing, the wet etching method has been widely adopted as a relatively simple and inexpensive manufacturing method. In this study, we report the effects of hierarchical pyramid-structured Si with nanoholes formed using a chemical wet etching process with thermally dewetted Ag thin films. First, alkaline etching was performed on a Si wafer to fabricate micrometer-sized random pyramid structures. Then, Ag thin film was thermally grown on the pyramid-structured Si. Finally, nanopores were formed on the random pyramid structure via metal-assisted chemical etching. The final morphology of Si was a hierarchical random pyramid structure with nanoholes, exhibiting both anti-reflection and superhydrophobicity. The average reflectance decreased to ∼4%, and the contact angle increased to 170.5°, allowing these surfaces to be used in various wettability-controlled optoelectronic devices, such as Si solar cells for where light trapping and self-cleaning are essential.

Published
2020

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