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808 results on '"Bourque, Guillaume"'

1. The Canadian VirusSeq Data Portal & Duotang: open resources for SARS-CoV-2 viral sequences and genomic epidemiology

Author

Gill, Erin E., Jia, Baofeng, Murall, Carmen Lia, Poujol, Raphaël, Anwar, Muhammad Zohaib, John, Nithu Sara, Richardsson, Justin, Hobb, Ashley, Olabode, Abayomi S., Lepsa, Alexandru, Duggan, Ana T., Tyler, Andrea D., N'Guessan, Arnaud, Kachru, Atul, Chan, Brandon, Yoshida, Catherine, Yung, Christina K., Bujold, David, Andric, Dusan, Su, Edmund, Griffiths, Emma J., Van Domselaar, Gary, Jolly, Gordon W., Ward, Heather K. E., Feher, Henrich, Baker, Jared, Simpson, Jared T., Uddin, Jaser, Ragoussis, Jiannis, Eubank, Jon, Fritz, Jörg H., Gálvez, José Héctor, Fang, Karen, Cullion, Kim, Rivera, Leonardo, Xiang, Linda, Croxen, Matthew A., Shiell, Mitchell, Prystajecky, Natalie, Quirion, Pierre-Olivier, Bajari, Rosita, Rich, Samantha, Mubareka, Samira, Moreira, Sandrine, Cain, Scott, Sutcliffe, Steven G., Kraemer, Susanne A., Joly, Yann, Alturmessov, Yelizar, consortium, CPHLN, consortium, CanCOGeN, Academic, VirusSeq Data Portal, network, Health, Fiume, Marc, Snutch, Terrance P., Bell, Cindy, Lopez-Correa, Catalina, Hussin, Julie G., Joy, Jeffrey B., Colijn, Caroline, Gordon, Paul M. K., Hsiao, William W. L., Poon, Art F. Y., Knox, Natalie C., Courtot, Mélanie, Stein, Lincoln, Otto, Sarah P., Bourque, Guillaume, Shapiro, B. Jesse, and Brinkman, Fiona S. L.

Subjects
Quantitative Biology - Genomics
Abstract

The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform public health response. Millions of SARS-CoV-2 genome sequences have been deposited in global public repositories. The Canadian COVID-19 Genomics Network (CanCOGeN - VirusSeq), a consortium tasked with coordinating expanded sequencing of SARS-CoV-2 genomes across Canada early in the pandemic, created the Canadian VirusSeq Data Portal, with associated data pipelines and procedures, to support these efforts. The goal of VirusSeq was to allow open access to Canadian SARS-CoV-2 genomic sequences and enhanced, standardized contextual data that were unavailable in other repositories and that meet FAIR standards (Findable, Accessible, Interoperable and Reusable). The Portal data submission pipeline contains data quality checking procedures and appropriate acknowledgement of data generators that encourages collaboration. Here we also highlight Duotang, a web platform that presents genomic epidemiology and modeling analyses on circulating and emerging SARS-CoV-2 variants in Canada. Duotang presents dynamic changes in variant composition of SARS-CoV-2 in Canada and by province, estimates variant growth, and displays complementary interactive visualizations, with a text overview of the current situation. The VirusSeq Data Portal and Duotang resources, alongside additional analyses and resources computed from the Portal (COVID-MVP, CoVizu), are all open-source and freely available. Together, they provide an updated picture of SARS-CoV-2 evolution to spur scientific discussions, inform public discourse, and support communication with and within public health authorities. They also serve as a framework for other jurisdictions interested in open, collaborative sequence data sharing and analyses.

Published
2024

2. A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome

Author

Bhérer, Claude, Eveleigh, Robert, Trajanoska, Katerina, St-Cyr, Janick, Paccard, Antoine, Nadukkalam Ravindran, Praveen, Caron, Elizabeth, Bader Asbah, Nimara, McClelland, Peyton, Wei, Clare, Baumgartner, Iris, Schindewolf, Marc, Döring, Yvonne, Perley, Danielle, Lefebvre, François, Lepage, Pierre, Bourgey, Mathieu, Bourque, Guillaume, Ragoussis, Jiannis, Mooser, Vincent, and Taliun, Daniel

Published
2024
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4. Epigenetic variation impacts individual differences in the transcriptional response to influenza infection

Author

Aracena, Katherine A., Lin, Yen-Lung, Luo, Kaixuan, Pacis, Alain, Gona, Saideep, Mu, Zepeng, Yotova, Vania, Sindeaux, Renata, Pramatarova, Albena, Simon, Marie-Michelle, Chen, Xun, Groza, Cristian, Lougheed, David, Gregoire, Romain, Brownlee, David, Boye, Carly, Pique-Regi, Roger, Li, Yang, He, Xin, Bujold, David, Pastinen, Tomi, Bourque, Guillaume, and Barreiro, Luis B.

Published
2024
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5. RNAget: an API to securely retrieve RNA quantifications.

Author

Upchurch, Sean, Palumbo, Emilio, Adams, Jeremy, Bujold, David, Bourque, Guillaume, Nedzel, Jared, Graham, Keenan, Kagda, Meenakshi, Assis, Pedro, Hitz, Benjamin, Righi, Emilio, Guigó, Roderic, and Wold, Barbara

Subjects
RNA, Software, Genomics, Genome, Sequence Analysis, RNA
Abstract

SUMMARY: Large-scale sharing of genomic quantification data requires standardized access interfaces. In this Global Alliance for Genomics and Health project, we developed RNAget, an API for secure access to genomic quantification data in matrix form. RNAget provides for slicing matrices to extract desired subsets of data and is applicable to all expression matrix-format data, including RNA sequencing and microarrays. Further, it generalizes to quantification matrices of other sequence-based genomics such as ATAC-seq and ChIP-seq. AVAILABILITY AND IMPLEMENTATION: https://ga4gh-rnaseq.github.io/schema/docs/index.html.

Published
2023

6. Gaps and complex structurally variant loci in phased genome assemblies

Author

Porubsky, David, Vollger, Mitchell R, Harvey, William T, Rozanski, Allison N, Ebert, Peter, Hickey, Glenn, Hasenfeld, Patrick, Sanders, Ashley D, Stober, Catherine, Consortium, Human Pangenome Reference, Korbel, Jan O, Paten, Benedict, Marschall, Tobias, Eichler, Evan E, Abel, Haley J, Antonacci-Fulton, Lucinda L, Asri, Mobin, Baid, Gunjan, Baker, Carl A, Belyaeva, Anastasiya, Billis, Konstantinos, Bourque, Guillaume, Buonaiuto, Silvia, Carroll, Andrew, Chaisson, Mark JP, Chang, Pi-Chuan, Chang, Xian H, Cheng, Haoyu, Chu, Justin, Cody, Sarah, Colonna, Vincenza, Cook, Daniel E, Cook-Deegan, Robert M, Cornejo, Omar E, Diekhans, Mark, Doerr, Daniel, Ebler, Jana, Eizenga, Jordan M, Fairley, Susan, Fedrigo, Olivier, Felsenfeld, Adam L, Feng, Xiaowen, Fischer, Christian, Flicek, Paul, Formenti, Giulio, Frankish, Adam, Fulton, Robert S, Gao, Yan, Garg, Shilpa, Garrison, Erik, Garrison, Nanibaa’ A, Giron, Carlos Garcia, Green, Richard E, Groza, Cristian, Guarracino, Andrea, Haggerty, Leanne, Hall, Ira M, Haukness, Marina, Haussler, David, Heumos, Simon, Hoekzema, Kendra, Hourlier, Thibaut, Howe, Kerstin, Jain, Miten, Jarvis, Erich D, Ji, Hanlee P, Kenny, Eimear E, Koenig, Barbara A, Kolesnikov, Alexey, Kordosky, Jennifer, Koren, Sergey, Lee, HoJoon, Lewis, Alexandra P, Li, Heng, Liao, Wen-Wei, Lu, Shuangjia, Lu, Tsung-Yu, Lucas, Julian K, Magalhães, Hugo, Marco-Sola, Santiago, Marijon, Pierre, Markello, Charles, Martin, Fergal J, McCartney, Ann, McDaniel, Jennifer, Miga, Karen H, Mitchell, Matthew W, Monlong, Jean, Mountcastle, Jacquelyn, Munson, Katherine M, Mwaniki, Moses Njagi, Nattestad, Maria, Novak, Adam M, and Nurk, Sergey

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, Humans, DNA, Satellite, Polymorphism, Genetic, Haplotypes, Segmental Duplications, Genomic, Sequence Analysis, DNA, Human Pangenome Reference Consortium, Medical and Health Sciences, Bioinformatics
Abstract

There has been tremendous progress in phased genome assembly production by combining long-read data with parental information or linked-read data. Nevertheless, a typical phased genome assembly generated by trio-hifiasm still generates more than 140 gaps. We perform a detailed analysis of gaps, assembly breaks, and misorientations from 182 haploid assemblies obtained from a diversity panel of 77 unique human samples. Although trio-based approaches using HiFi are the current gold standard, chromosome-wide phasing accuracy is comparable when using Strand-seq instead of parental data. Importantly, the majority of assembly gaps cluster near the largest and most identical repeats (including segmental duplications [35.4%], satellite DNA [22.3%], or regions enriched in GA/AT-rich DNA [27.4%]). Consequently, 1513 protein-coding genes overlap assembly gaps in at least one haplotype, and 231 are recurrently disrupted or missing from five or more haplotypes. Furthermore, we estimate that 6-7 Mbp of DNA are misorientated per haplotype irrespective of whether trio-free or trio-based approaches are used. Of these misorientations, 81% correspond to bona fide large inversion polymorphisms in the human species, most of which are flanked by large segmental duplications. We also identify large-scale alignment discontinuities consistent with 11.9 Mbp of deletions and 161.4 Mbp of insertions per haploid genome. Although 99% of this variation corresponds to satellite DNA, we identify 230 regions of euchromatic DNA with frequent expansions and contractions, nearly half of which overlap with 197 protein-coding genes. Such variable and incompletely assembled regions are important targets for future algorithmic development and pangenome representation.

Published
2023

7. Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative.

Author

Butler-Laporte, Guillaume, Povysil, Gundula, Kosmicki, Jack, Cirulli, Elizabeth, Drivas, Theodore, Furini, Simone, Saad, Chadi, Schmidt, Axel, Olszewski, Pawel, Korotko, Urszula, Quinodoz, Mathieu, Çelik, Elifnaz, Kundu, Kousik, Walter, Klaudia, Jung, Junghyun, Stockwell, Amy, Sloofman, Laura, Jordan, Daniel, Thompson, Ryan, Del Valle, Diane, Simons, Nicole, Cheng, Esther, Sebra, Robert, Schadt, Eric, Kim-Schulze, Seunghee, Gnjatic, Sacha, Merad, Miriam, Buxbaum, Joseph, Beckmann, Noam, Charney, Alexander, Przychodzen, Bartlomiej, Chang, Timothy, Pottinger, Tess, Shang, Ning, Brand, Fabian, Fava, Francesca, Mari, Francesca, Chwialkowska, Karolina, Niemira, Magdalena, Pula, Szymon, Baillie, J, Stuckey, Alex, Salas, Antonio, Bello, Xabier, Pardo-Seco, Jacobo, Gómez-Carballa, Alberto, Rivero-Calle, Irene, Martinón-Torres, Federico, Ganna, Andrea, Karczewski, Konrad, Veerapen, Kumar, Bourgey, Mathieu, Bourque, Guillaume, Eveleigh, Robert, Forgetta, Vincenzo, Morrison, David, Langlais, David, Lathrop, Mark, Mooser, Vincent, Nakanishi, Tomoko, Frithiof, Robert, Hultström, Michael, Lipcsey, Miklos, Marincevic-Zuniga, Yanara, Nordlund, Jessica, Schiabor Barrett, Kelly, Lee, William, Bolze, Alexandre, White, Simon, Riffle, Stephen, Tanudjaja, Francisco, Sandoval, Efren, Neveux, Iva, Dabe, Shaun, Casadei, Nicolas, Motameny, Susanne, Alaamery, Manal, Massadeh, Salam, Aljawini, Nora, Almutairi, Mansour, Arabi, Yaseen, Alqahtani, Saleh, Al Harthi, Fawz, Almutairi, Amal, Alqubaishi, Fatima, Alotaibi, Sarah, Binowayn, Albandari, Alsolm, Ebtehal, El Bardisy, Hadeel, Fawzy, Mohammad, Cai, Fang, Soranzo, Nicole, Butterworth, Adam, Geschwind, Daniel, Arteaga, Stephanie, Stephens, Alexis, Butte, Manish, Boutros, Paul, Yamaguchi, Takafumi, and Tao, Shu

Subjects
Humans, Exome, Genome-Wide Association Study, COVID-19, Genetic Predisposition to Disease, Toll-Like Receptor 7, SARS-CoV-2
Abstract

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Published
2022

8. TULIPs decorate the three-dimensional genome of PFA ependymoma

Author

Johnston, Michael J., Lee, John J.Y., Hu, Bo, Nikolic, Ana, Hasheminasabgorji, Elham, Baguette, Audrey, Paik, Seungil, Chen, Haifen, Kumar, Sachin, Chen, Carol C.L., Jessa, Selin, Balin, Polina, Fong, Vernon, Zwaig, Melissa, Michealraj, Kulandaimanuvel Antony, Chen, Xun, Zhang, Yanlin, Varadharajan, Srinidhi, Billon, Pierre, Juretic, Nikoleta, Daniels, Craig, Rao, Amulya Nageswara, Giannini, Caterina, Thompson, Eric M., Garami, Miklos, Hauser, Peter, Pocza, Timea, Ra, Young Shin, Cho, Byung-Kyu, Kim, Seung-Ki, Wang, Kyu-Chang, Lee, Ji Yeoun, Grajkowska, Wieslawa, Perek-Polnik, Marta, Agnihotri, Sameer, Mack, Stephen, Ellezam, Benjamin, Weil, Alex, Rich, Jeremy, Bourque, Guillaume, Chan, Jennifer A., Yong, V. Wee, Lupien, Mathieu, Ragoussis, Jiannis, Kleinman, Claudia, Majewski, Jacek, Blanchette, Mathieu, Jabado, Nada, Taylor, Michael D., and Gallo, Marco

Published
2024
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9. Evolution of chromosome-arm aberrations in breast cancer through genetic network rewiring

Author

Kuzmin, Elena, Baker, Toby M., Lesluyes, Tom, Monlong, Jean, Abe, Kento T., Coelho, Paula P., Schwartz, Michael, Del Corpo, Joseph, Zou, Dongmei, Morin, Genevieve, Pacis, Alain, Yang, Yang, Martinez, Constanza, Barber, Jarrett, Kuasne, Hellen, Li, Rui, Bourgey, Mathieu, Fortier, Anne-Marie, Davison, Peter G., Omeroglu, Atilla, Guiot, Marie-Christine, Morris, Quaid, Kleinman, Claudia L., Huang, Sidong, Gingras, Anne-Claude, Ragoussis, Jiannis, Bourque, Guillaume, Van Loo, Peter, and Park, Morag

Published
2024
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11. A draft human pangenome reference

Author

Liao, Wen-Wei, Asri, Mobin, Ebler, Jana, Doerr, Daniel, Haukness, Marina, Hickey, Glenn, Lu, Shuangjia, Lucas, Julian K., Monlong, Jean, Abel, Haley J., Buonaiuto, Silvia, Chang, Xian H., Cheng, Haoyu, Chu, Justin, Colonna, Vincenza, Eizenga, Jordan M., Feng, Xiaowen, Fischer, Christian, Fulton, Robert S., Garg, Shilpa, Groza, Cristian, Guarracino, Andrea, Harvey, William T., Heumos, Simon, Howe, Kerstin, Jain, Miten, Lu, Tsung-Yu, Markello, Charles, Martin, Fergal J., Mitchell, Matthew W., Munson, Katherine M., Mwaniki, Moses Njagi, Novak, Adam M., Olsen, Hugh E., Pesout, Trevor, Porubsky, David, Prins, Pjotr, Sibbesen, Jonas A., Sirén, Jouni, Tomlinson, Chad, Villani, Flavia, Vollger, Mitchell R., Antonacci-Fulton, Lucinda L., Baid, Gunjan, Baker, Carl A., Belyaeva, Anastasiya, Billis, Konstantinos, Carroll, Andrew, Chang, Pi-Chuan, Cody, Sarah, Cook, Daniel E., Cook-Deegan, Robert M., Cornejo, Omar E., Diekhans, Mark, Ebert, Peter, Fairley, Susan, Fedrigo, Olivier, Felsenfeld, Adam L., Formenti, Giulio, Frankish, Adam, Gao, Yan, Garrison, Nanibaa’ A., Giron, Carlos Garcia, Green, Richard E., Haggerty, Leanne, Hoekzema, Kendra, Hourlier, Thibaut, Ji, Hanlee P., Kenny, Eimear E., Koenig, Barbara A., Kolesnikov, Alexey, Korbel, Jan O., Kordosky, Jennifer, Koren, Sergey, Lee, HoJoon, Lewis, Alexandra P., Magalhães, Hugo, Marco-Sola, Santiago, Marijon, Pierre, McCartney, Ann, McDaniel, Jennifer, Mountcastle, Jacquelyn, Nattestad, Maria, Nurk, Sergey, Olson, Nathan D., Popejoy, Alice B., Puiu, Daniela, Rautiainen, Mikko, Regier, Allison A., Rhie, Arang, Sacco, Samuel, Sanders, Ashley D., Schneider, Valerie A., Schultz, Baergen I., Shafin, Kishwar, Smith, Michael W., Sofia, Heidi J., Abou Tayoun, Ahmad N., Thibaud-Nissen, Françoise, Tricomi, Francesca Floriana, Wagner, Justin, Walenz, Brian, Wood, Jonathan M. D., Zimin, Aleksey V., Bourque, Guillaume, Chaisson, Mark J. P., Flicek, Paul, Phillippy, Adam M., Zook, Justin M., Eichler, Evan E., Haussler, David, Wang, Ting, Jarvis, Erich D., Miga, Karen H., Garrison, Erik, Marschall, Tobias, Hall, Ira M., Li, Heng, and Paten, Benedict

Published
2023
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12. Genomics of perivascular space burden unravels early mechanisms of cerebral small vessel disease

Author

Duperron, Marie-Gabrielle, Knol, Maria J., Le Grand, Quentin, Evans, Tavia E., Mishra, Aniket, Tsuchida, Ami, Roshchupkin, Gennady, Konuma, Takahiro, Trégouët, David-Alexandre, Romero, Jose Rafael, Frenzel, Stefan, Luciano, Michelle, Hofer, Edith, Bourgey, Mathieu, Dueker, Nicole D., Delgado, Pilar, Hilal, Saima, Tankard, Rick M., Dubost, Florian, Shin, Jean, Saba, Yasaman, Armstrong, Nicola J., Bordes, Constance, Bastin, Mark E., Beiser, Alexa, Brodaty, Henry, Bülow, Robin, Carrera, Caty, Chen, Christopher, Cheng, Ching-Yu, Deary, Ian J., Gampawar, Piyush G., Himali, Jayandra J., Jiang, Jiyang, Kawaguchi, Takahisa, Li, Shuo, Macalli, Melissa, Marquis, Pascale, Morris, Zoe, Muñoz Maniega, Susana, Miyamoto, Susumu, Okawa, Masakazu, Paradise, Matthew, Parva, Pedram, Rundek, Tatjana, Sargurupremraj, Muralidharan, Schilling, Sabrina, Setoh, Kazuya, Soukarieh, Omar, Tabara, Yasuharu, Teumer, Alexander, Thalamuthu, Anbupalam, Trollor, Julian N., Valdés Hernández, Maria C., Vernooij, Meike W., Völker, Uwe, Wittfeld, Katharina, Wong, Tien Yin, Wright, Margaret J., Zhang, Junyi, Zhao, Wanting, Zhu, Yi-Cheng, Schmidt, Helena, Sachdev, Perminder S., Wen, Wei, Yoshida, Kazumichi, Joutel, Anne, Satizabal, Claudia L., Sacco, Ralph L., Bourque, Guillaume, Lathrop, Mark, Paus, Tomas, Fernandez-Cadenas, Israel, Yang, Qiong, Mazoyer, Bernard, Boutinaud, Philippe, Okada, Yukinori, Grabe, Hans J., Mather, Karen A., Schmidt, Reinhold, Joliot, Marc, Ikram, M. Arfan, Matsuda, Fumihiko, Tzourio, Christophe, Wardlaw, Joanna M., Seshadri, Sudha, Adams, Hieab H. H., and Debette, Stéphanie

Published
2023
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13. GA4GH: International policies and standards for data sharing across genomic research and healthcare

Author

Rehm, Heidi L, Page, Angela JH, Smith, Lindsay, Adams, Jeremy B, Alterovitz, Gil, Babb, Lawrence J, Barkley, Maxmillian P, Baudis, Michael, Beauvais, Michael JS, Beck, Tim, Beckmann, Jacques S, Beltran, Sergi, Bernick, David, Bernier, Alexander, Bonfield, James K, Boughtwood, Tiffany F, Bourque, Guillaume, Bowers, Sarion R, Brookes, Anthony J, Brudno, Michael, Brush, Matthew H, Bujold, David, Burdett, Tony, Buske, Orion J, Cabili, Moran N, Cameron, Daniel L, Carroll, Robert J, Casas-Silva, Esmeralda, Chakravarty, Debyani, Chaudhari, Bimal P, Chen, Shu Hui, Cherry, J Michael, Chung, Justina, Cline, Melissa, Clissold, Hayley L, Cook-Deegan, Robert M, Courtot, Mélanie, Cunningham, Fiona, Cupak, Miro, Davies, Robert M, Denisko, Danielle, Doerr, Megan J, Dolman, Lena I, Dove, Edward S, Dursi, L Jonathan, Dyke, Stephanie OM, Eddy, James A, Eilbeck, Karen, Ellrott, Kyle P, Fairley, Susan, Fakhro, Khalid A, Firth, Helen V, Fitzsimons, Michael S, Fiume, Marc, Flicek, Paul, Fore, Ian M, Freeberg, Mallory A, Freimuth, Robert R, Fromont, Lauren A, Fuerth, Jonathan, Gaff, Clara L, Gan, Weiniu, Ghanaim, Elena M, Glazer, David, Green, Robert C, Griffith, Malachi, Griffith, Obi L, Grossman, Robert L, Groza, Tudor, Auvil, Jaime M Guidry, Guigó, Roderic, Gupta, Dipayan, Haendel, Melissa A, Hamosh, Ada, Hansen, David P, Hart, Reece K, Hartley, Dean Mitchell, Haussler, David, Hendricks-Sturrup, Rachele M, Ho, Calvin WL, Hobb, Ashley E, Hoffman, Michael M, Hofmann, Oliver M, Holub, Petr, Hsu, Jacob Shujui, Hubaux, Jean-Pierre, Hunt, Sarah E, Husami, Ammar, Jacobsen, Julius O, Jamuar, Saumya S, Janes, Elizabeth L, Jeanson, Francis, Jené, Aina, Johns, Amber L, Joly, Yann, Jones, Steven JM, Kanitz, Alexander, Kato, Kazuto, Keane, Thomas M, and Kekesi-Lafrance, Kristina

Subjects
Biological Sciences, Genetics, Human Genome, Clinical Research, Health Services, Generic health relevance, Good Health and Well Being
Abstract

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

Published
2021

15. Pan-conserved segment tags identify ultra-conserved sequences across assemblies in the human pangenome

Author

Liao, Wen-Wei, Asri, Mobin, Ebler, Jana, Doerr, Daniel, Haukness, Marina, Hickey, Glenn, Lu, Shuangjia, Lucas, Julian K., Monlong, Jean, Abel, Haley J., Buonaiuto, Silvia, Chang, Xian H., Cheng, Haoyu, Chu, Justin, Colonna, Vincenza, Eizenga, Jordan M., Feng, Xiaowen, Fischer, Christian, Fulton, Robert S., Garg, Shilpa, Groza, Cristian, Guarracino, Andrea, Harvey, William T., Heumos, Simon, Howe, Kerstin, Jain, Miten, Lu, Tsung-Yu, Markello, Charles, Martin, Fergal J., Mitchell, Matthew W., Munson, Katherine M., Mwaniki, Moses Njagi, Novak, Adam M., Olsen, Hugh E., Pesout, Trevor, Porubsky, David, Prins, Pjotr, Sibbesen, Jonas A., Tomlinson, Chad, Villani, Flavia, Vollger, Mitchell R., Antonacci-Fulton, Lucinda L., Baid, Gunjan, Baker, Carl A., Belyaeva, Anastasiya, Billis, Konstantinos, Carroll, Andrew, Chang, Pi-Chuan, Cody, Sarah, Cook, Daniel E., Cornejo, Omar E., Diekhans, Mark, Ebert, Peter, Fairley, Susan, Fedrigo, Olivier, Felsenfeld, Adam L., Formenti, Giulio, Frankish, Adam, Gao, Yan, Giron, Carlos Garcia, Green, Richard E., Haggerty, Leanne, Hoekzema, Kendra, Hourlier, Thibaut, Ji, Hanlee P., Kolesnikov, Alexey, Korbel, Jan O., Kordosky, Jennifer, Lee, HoJoon, Lewis, Alexandra P., Magalhães, Hugo, Marco-Sola, Santiago, Marijon, Pierre, McDaniel, Jennifer, Mountcastle, Jacquelyn, Nattestad, Maria, Olson, Nathan D., Puiu, Daniela, Regier, Allison A., Rhie, Arang, Sacco, Samuel, Sanders, Ashley D., Schneider, Valerie A., Schultz, Baergen I., Shafin, Kishwar, Sirén, Jouni, Smith, Michael W., Sofia, Heidi J., Abou Tayoun, Ahmad N., Thibaud-Nissen, Françoise, Tricomi, Francesca Floriana, Wagner, Justin, Wood, Jonathan M.D., Zimin, Aleksey V., Popejoy, Alice B., Bourque, Guillaume, Chaisson, Mark J.P., Flicek, Paul, Phillippy, Adam M., Zook, Justin M., Eichler, Evan E., Haussler, David, Jarvis, Erich D., Miga, Karen H., Wang, Ting, Garrison, Erik, Marschall, Tobias, Hall, Ira, Li, Heng, Paten, Benedict, Greer, Stephanie U., Pavlichin, Dmitri S., Zhou, Bo, Urban, Alexander E., and Weissman, Tsachy

Published
2023
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19. Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition.

Author

Rodriguez-Martin, Bernardo, Alvarez, Eva G, Baez-Ortega, Adrian, Zamora, Jorge, Supek, Fran, Demeulemeester, Jonas, Santamarina, Martin, Ju, Young Seok, Temes, Javier, Garcia-Souto, Daniel, Detering, Harald, Li, Yilong, Rodriguez-Castro, Jorge, Dueso-Barroso, Ana, Bruzos, Alicia L, Dentro, Stefan C, Blanco, Miguel G, Contino, Gianmarco, Ardeljan, Daniel, Tojo, Marta, Roberts, Nicola D, Zumalave, Sonia, Edwards, Paul A, Weischenfeldt, Joachim, Puiggròs, Montserrat, Chong, Zechen, Chen, Ken, Lee, Eunjung Alice, Wala, Jeremiah A, Raine, Keiran M, Butler, Adam, Waszak, Sebastian M, Navarro, Fabio CP, Schumacher, Steven E, Monlong, Jean, Maura, Francesco, Bolli, Niccolo, Bourque, Guillaume, Gerstein, Mark, Park, Peter J, Wedge, David C, Beroukhim, Rameen, Torrents, David, Korbel, Jan O, Martincorena, Iñigo, Fitzgerald, Rebecca C, Van Loo, Peter, Kazazian, Haig H, Burns, Kathleen H, PCAWG Structural Variation Working Group, Campbell, Peter J, Tubio, Jose MC, and PCAWG Consortium

Subjects
PCAWG Structural Variation Working Group, PCAWG Consortium, Humans, Neoplasms, Retroelements, Gene Rearrangement, Long Interspersed Nucleotide Elements, Genome, Human, Carcinogenesis, Genetics, Digestive Diseases, Human Genome, Cancer, Rare Diseases, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

About half of all cancers have somatic integrations of retrotransposons. Here, to characterize their role in oncogenesis, we analyzed the patterns and mechanisms of somatic retrotransposition in 2,954 cancer genomes from 38 histological cancer subtypes within the framework of the Pan-Cancer Analysis of Whole Genomes (PCAWG) project. We identified 19,166 somatically acquired retrotransposition events, which affected 35% of samples and spanned a range of event types. Long interspersed nuclear element (LINE-1; L1 hereafter) insertions emerged as the first most frequent type of somatic structural variation in esophageal adenocarcinoma, and the second most frequent in head-and-neck and colorectal cancers. Aberrant L1 integrations can delete megabase-scale regions of a chromosome, which sometimes leads to the removal of tumor-suppressor genes, and can induce complex translocations and large-scale duplications. Somatic retrotranspositions can also initiate breakage-fusion-bridge cycles, leading to high-level amplification of oncogenes. These observations illuminate a relevant role of L1 retrotransposition in remodeling the cancer genome, with potential implications for the development of human tumors.

Published
2020

22. Mouse embryonic stem cells require sustained DNMT1-mediated DNA methylation maintenance for epigenomic, genomic and functional integrity

Author

Elder, Elizabeth, primary, Lemieux, Anthony, additional, Legault, Lisa-Marie, additional, Caron, Maxime, additional, Bertrand-Lehouillier, Virginie, additional, Dupas, Thomas, additional, Raynal, Noël, additional, Bourque, Guillaume, additional, Sinnett, Daniel, additional, Gévry, Nicolas, additional, and McGraw, Serge, additional

Published
2024
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23. Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic Data

Author

Hocking, Toby Dylan, Rigaill, Guillem, Fearnhead, Paul, and Bourque, Guillaume

Subjects
Statistics - Computation
Abstract

We describe a new algorithm and R package for peak detection in genomic data sets using constrained changepoint algorithms. These detect changes from background to peak regions by imposing the constraint that the mean should alternately increase then decrease. An existing algorithm for this problem exists, and gives state-of-the-art accuracy results, but it is computationally expensive when the number of changes is large. We propose the GFPOP algorithm that jointly estimates the number of peaks and their locations by minimizing a cost function which consists of a data fitting term and a penalty for each changepoint. Empirically this algorithm has a cost that is $O(N \log(N))$ for analysing data of length $N$. We also propose a sequential search algorithm that finds the best solution with $K$ segments in $O(\log(K)N \log(N))$ time, which is much faster than the previous $O(KN \log(N))$ algorithm. We show that our disk-based implementation in the PeakSegDisk R package can be used to quickly compute constrained optimal models with many changepoints, which are needed to analyze typical genomic data sets that have tens of millions of observations.

Published
2018

24. PrecisionFDA Truth Challenge V2: Calling variants from short and long reads in difficult-to-map regions

Author

Olson, Nathan D., Wagner, Justin, McDaniel, Jennifer, Stephens, Sarah H., Westreich, Samuel T., Prasanna, Anish G., Johanson, Elaine, Boja, Emily, Maier, Ezekiel J., Serang, Omar, Jáspez, David, Lorenzo-Salazar, José M., Muñoz-Barrera, Adrián, Rubio-Rodríguez, Luis A., Flores, Carlos, Kyriakidis, Konstantinos, Malousi, Andigoni, Shafin, Kishwar, Pesout, Trevor, Jain, Miten, Paten, Benedict, Chang, Pi-Chuan, Kolesnikov, Alexey, Nattestad, Maria, Baid, Gunjan, Goel, Sidharth, Yang, Howard, Carroll, Andrew, Eveleigh, Robert, Bourgey, Mathieu, Bourque, Guillaume, Li, Gen, Ma, ChouXian, Tang, LinQi, Du, YuanPing, Zhang, ShaoWei, Morata, Jordi, Tonda, Raúl, Parra, Genís, Trotta, Jean-Rémi, Brueffer, Christian, Demirkaya-Budak, Sinem, Kabakci-Zorlu, Duygu, Turgut, Deniz, Kalay, Özem, Budak, Gungor, Narcı, Kübra, Arslan, Elif, Brown, Richard, Johnson, Ivan J., Dolgoborodov, Alexey, Semenyuk, Vladimir, Jain, Amit, Tetikol, H. Serhat, Jain, Varun, Ruehle, Mike, Lajoie, Bryan, Roddey, Cooper, Catreux, Severine, Mehio, Rami, Ahsan, Mian Umair, Liu, Qian, Wang, Kai, Ebrahim Sahraeian, Sayed Mohammad, Fang, Li Tai, Mohiyuddin, Marghoob, Hung, Calvin, Jain, Chirag, Feng, Hanying, Li, Zhipan, Chen, Luoqi, Sedlazeck, Fritz J., and Zook, Justin M.

Published
2022
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26. IHEC Data Portal

Author

Bujold, David, Grégoire, Romain, Brownlee, David, Zaytseva, Ksenia, Bourque, Guillaume, Abugessaisa, Imad, editor, and Kasukawa, Takeya, editor

Published
2021
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27. A log-linear time algorithm for constrained changepoint detection

Author

Hocking, Toby Dylan, Rigaill, Guillem, Fearnhead, Paul, and Bourque, Guillaume

Subjects
Statistics - Computation, Quantitative Biology - Genomics, Statistics - Machine Learning
Abstract

Changepoint detection is a central problem in time series and genomic data. For some applications, it is natural to impose constraints on the directions of changes. One example is ChIP-seq data, for which adding an up-down constraint improves peak detection accuracy, but makes the optimization problem more complicated. We show how a recently proposed functional pruning technique can be adapted to solve such constrained changepoint detection problems. This leads to a new algorithm which can solve problems with arbitrary affine constraints on adjacent segment means, and which has empirical time complexity that is log-linear in the amount of data. This algorithm achieves state-of-the-art accuracy in a benchmark of several genomic data sets, and is orders of magnitude faster than existing algorithms that have similar accuracy. Our implementation is available as the PeakSegPDPA function in the coseg R package, https://github.com/tdhock/coseg

Published
2017

28. Author Correction: Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition

Author

Rodriguez-Martin, Bernardo, Alvarez, Eva G., Baez-Ortega, Adrian, Zamora, Jorge, Supek, Fran, Demeulemeester, Jonas, Santamarina, Martin, Ju, Young Seok, Temes, Javier, Garcia-Souto, Daniel, Detering, Harald, Li, Yilong, Rodriguez-Castro, Jorge, Dueso-Barroso, Ana, Bruzos, Alicia L., Dentro, Stefan C., Blanco, Miguel G., Contino, Gianmarco, Ardeljan, Daniel, Tojo, Marta, Roberts, Nicola D., Zumalave, Sonia, Edwards, Paul A., Weischenfeldt, Joachim, Puiggròs, Montserrat, Chong, Zechen, Chen, Ken, Lee, Eunjung Alice, Wala, Jeremiah A., Raine, Keiran M., Butler, Adam, Waszak, Sebastian M., Navarro, Fabio C. P., Schumacher, Steven E., Monlong, Jean, Maura, Francesco, Bolli, Niccolo, Bourque, Guillaume, Gerstein, Mark, Park, Peter J., Wedge, David C., Beroukhim, Rameen, Torrents, David, Korbel, Jan O., Martincorena, Iñigo, Fitzgerald, Rebecca C., Van Loo, Peter, Kazazian, Haig H., Burns, Kathleen H., Campbell, Peter J., and Tubio, Jose M. C.

Published
2023
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32. CircRNAome of Childhood Acute Lymphoblastic Leukemia: Deciphering Subtype-Specific Expression Profiles and Involvement in TCF3::PBX1 ALL

Author

Gutierrez-Camino, Angela, primary, Caron, Maxime, additional, Richer, Chantal, additional, Fuchs, Claire, additional, Illarregi, Unai, additional, Poncelet, Lucas, additional, St-Onge, Pascal, additional, Bataille, Alain R., additional, Tremblay-Dauphinais, Pascal, additional, Lopez-Lopez, Elixabet, additional, Camos, Mireia, additional, Ramirez-Orellana, Manuel, additional, Astigarraga, Itziar, additional, Lécuyer, Éric, additional, Bourque, Guillaume, additional, Martin-Guerrero, Idoia, additional, and Sinnett, Daniel, additional

Published
2024
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35. Integrated (epi)-Genomic Analyses Identify Subgroup-Specific Therapeutic Targets in CNS Rhabdoid Tumors

Author

Torchia, Jonathon, Golbourn, Brian, Feng, Shengrui, Ho, Ching, Sin-Chan, Patrick, Vasiljevic, Alexandre, Norman, Joseph D, Guilhamon, Paul, Garzia, Livia, Agamez, Natalia R, Lu, Mei, Chan, Tiffany S, Picard, Daniel, de Antonellis, Pasqualino, Khuong-Quang, Dong-Anh, Planello, Aline C, Zeller, Constanze, Barsyte-Lovejoy, Dalia, Lafay-Cousin, Lucie, Letourneau, Louis, Bourgey, Mathieu, Yu, Man, Gendoo, Deena MA, Dzamba, Misko, Barszczyk, Mark, Medina, Tiago, Riemenschneider, Alexandra N, Morrissy, A Sorana, Ra, Young-Shin, Ramaswamy, Vijay, Remke, Marc, Dunham, Christopher P, Yip, Stephen, Ng, Ho-keung, Lu, Jian-Qiang, Mehta, Vivek, Albrecht, Steffen, Pimentel, Jose, Chan, Jennifer A, Somers, Gino R, Faria, Claudia C, Roque, Lucia, Fouladi, Maryam, Hoffman, Lindsey M, Moore, Andrew S, Wang, Yin, Choi, Seung Ah, Hansford, Jordan R, Catchpoole, Daniel, Birks, Diane K, Foreman, Nicholas K, Strother, Doug, Klekner, Almos, Bognár, Laszló, Garami, Miklós, Hauser, Péter, Hortobágyi, Tibor, Wilson, Beverly, Hukin, Juliette, Carret, Anne-Sophie, Van Meter, Timothy E, Hwang, Eugene I, Gajjar, Amar, Chiou, Shih-Hwa, Nakamura, Hideo, Toledano, Helen, Fried, Iris, Fults, Daniel, Wataya, Takafumi, Fryer, Chris, Eisenstat, David D, Scheinemann, Katrin, Fleming, Adam J, Johnston, Donna L, Michaud, Jean, Zelcer, Shayna, Hammond, Robert, Afzal, Samina, Ramsay, David A, Sirachainan, Nongnuch, Hongeng, Suradej, Larbcharoensub, Noppadol, Grundy, Richard G, Lulla, Rishi R, Fangusaro, Jason R, Druker, Harriet, Bartels, Ute, Grant, Ronald, Malkin, David, McGlade, C Jane, Nicolaides, Theodore, Tihan, Tarik, Phillips, Joanna, Majewski, Jacek, Montpetit, Alexandre, Bourque, Guillaume, Bader, Gary D, Reddy, Alyssa T, Gillespie, G Yancey, and Warmuth-Metz, Monika

Subjects
Genetics, Human Genome, Rare Diseases, Orphan Drug, Cancer, 2.1 Biological and endogenous factors, Development of treatments and therapeutic interventions, Aetiology, 5.1 Pharmaceuticals, Cell Line, Tumor, Cell Proliferation, Cell Survival, Central Nervous System Neoplasms, Chromatin, DNA Methylation, Dasatinib, Epigenesis, Genetic, Epigenomics, Humans, Mutation, Protein Kinase Inhibitors, Pyrimidines, Receptor, Platelet-Derived Growth Factor beta, Rhabdoid Tumor, SMARCB1 Protein, Teratoma, ATRT, enhancer, epigenomics, genomics, rhabdoid tumors, subgroup-specific therapeutics, Neurosciences, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

We recently reported that atypical teratoid rhabdoid tumors (ATRTs) comprise at least two transcriptional subtypes with different clinical outcomes; however, the mechanisms underlying therapeutic heterogeneity remained unclear. In this study, we analyzed 191 primary ATRTs and 10 ATRT cell lines to define the genomic and epigenomic landscape of ATRTs and identify subgroup-specific therapeutic targets. We found ATRTs segregated into three epigenetic subgroups with distinct genomic profiles, SMARCB1 genotypes, and chromatin landscape that correlated with differential cellular responses to a panel of signaling and epigenetic inhibitors. Significantly, we discovered that differential methylation of a PDGFRB-associated enhancer confers specific sensitivity of group 2 ATRT cells to dasatinib and nilotinib, and suggest that these are promising therapies for this highly lethal ATRT subtype.

Published
2016

36. PeakSegJoint: fast supervised peak detection via joint segmentation of multiple count data samples

Author

Hocking, Toby Dylan and Bourque, Guillaume

Subjects
Statistics - Machine Learning, Quantitative Biology - Genomics
Abstract

Joint peak detection is a central problem when comparing samples in genomic data analysis, but current algorithms for this task are unsupervised and limited to at most 2 sample types. We propose PeakSegJoint, a new constrained maximum likelihood segmentation model for any number of sample types. To select the number of peaks in the segmentation, we propose a supervised penalty learning model. To infer the parameters of these two models, we propose to use a discrete optimization heuristic for the segmentation, and convex optimization for the penalty learning. In comparisons with state-of-the-art peak detection algorithms, PeakSegJoint achieves similar accuracy, faster speeds, and a more interpretable model with overlapping peaks that occur in exactly the same positions across all samples., Comment: 11 pages, 5 figures

Published
2015

37. Pangenome graph construction from genome alignments with Minigraph-Cactus.

Author

Hickey, Glenn, Monlong, Jean, Ebler, Jana, Novak, Adam M., Eizenga, Jordan M., Gao, Yan, Abel, Haley J., Antonacci-Fulton, Lucinda L., Asri, Mobin, Baid, Gunjan, Baker, Carl A., Belyaeva, Anastasiya, Billis, Konstantinos, Bourque, Guillaume, Buonaiuto, Silvia, Carroll, Andrew, Chaisson, Mark J. P., Chang, Pi-Chuan, Chang, Xian H., and Cheng, Haoyu

Abstract

Pangenome references address biases of reference genomes by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles determined by variant callers can be used to construct pangenome graphs, but advances in long-read sequencing are leading to widely available, high-quality phased assemblies. Constructing a pangenome graph directly from assemblies, as opposed to variant calls, leverages the graph's ability to represent variation at different scales. Here we present the Minigraph-Cactus pangenome pipeline, which creates pangenomes directly from whole-genome alignments, and demonstrate its ability to scale to 90 human haplotypes from the Human Pangenome Reference Consortium. The method builds graphs containing all forms of genetic variation while allowing use of current mapping and genotyping tools. We measure the effect of the quality and completeness of reference genomes used for analysis within the pangenomes and show that using the CHM13 reference from the Telomere-to-Telomere Consortium improves the accuracy of our methods. We also demonstrate construction of a Drosophila melanogaster pangenome. Constructing genome graphs directly from genome assemblies overcomes single-reference bias. [ABSTRACT FROM AUTHOR]

Published
2024
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39. Visual annotations and a supervised learning approach for evaluating and calibrating ChIP-seq peak detectors

Author

Hocking, Toby Dylan, Goerner-Potvin, Patricia, Morin, Andreanne, Shao, Xiaojian, and Bourque, Guillaume

Subjects
Quantitative Biology - Genomics
Abstract

Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which method and what parameters are optimal for any given data set. In contrast, peaks can easily be located by visual inspection of profile data on a genome browser. We thus propose a supervised machine learning approach to ChIP-seq data analysis, using annotated regions that encode an expert's qualitative judgments about which regions contain or do not contain peaks. The main idea is to manually annotate a small subset of the genome, and then learn a model that makes consistent predictions on the rest of the genome. We show how our method can be used to quantitatively calibrate and benchmark the performance of peak detection algorithms on specific data sets. We compare several peak detectors on 7 annotated region data sets, consisting of 2 histone marks, 4 expert annotators, and several different cell types. In these data the macs algorithm was best for a narrow peak histone profile (H3K4me3) while the hmcan.broad algorithm was best for a broad histone profile (H3K36me3). Our benchmark annotated region data sets can be downloaded from a public website, and there is an R package for computing the annotation error on GitHub., Comment: includes supplementary materials

Published
2014

42. A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada

Author

Murall, Carmen Lía, Fournier, Eric, Galvez, Jose Hector, N’Guessan, Arnaud, Reiling, Sarah J., Quirion, Pierre-Olivier, Naderi, Sana, Roy, Anne-Marie, Chen, Shu-Huang, Stretenowich, Paul, Bourgey, Mathieu, Bujold, David, Gregoire, Romain, Lepage, Pierre, St-Cyr, Janick, Willet, Patrick, Dion, Réjean, Charest, Hugues, Lathrop, Mark, Roger, Michel, Bourque, Guillaume, Ragoussis, Jiannis, Shapiro, B. Jesse, and Moreira, Sandrine

Published
2021
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47. Single-cell analysis of human adipose tissue identifies depot- and disease-specific cell types

Author

Vijay, Jinchu, Gauthier, Marie-Frédérique, Biswell, Rebecca L., Louiselle, Daniel A., Johnston, Jeffrey J., Cheung, Warren A., Belden, Bradley, Pramatarova, Albena, Biertho, Laurent, Gibson, Margaret, Simon, Marie-Michelle, Djambazian, Haig, Staffa, Alfredo, Bourque, Guillaume, Laitinen, Anita, Nystedt, Johanna, Vohl, Marie-Claude, Fraser, Jason D., Pastinen, Tomi, Tchernof, André, and Grundberg, Elin

Published
2020
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48. Stalled developmental programs at the root of pediatric brain tumors

Author

Jessa, Selin, Blanchet-Cohen, Alexis, Krug, Brian, Vladoiu, Maria, Coutelier, Marie, Faury, Damien, Poreau, Brice, De Jay, Nicolas, Hébert, Steven, Monlong, Jean, Farmer, W. Todd, Donovan, Laura K., Hu, Yixing, McConechy, Melissa K., Cavalli, Florence M. G., Mikael, Leonie G., Ellezam, Benjamin, Richer, Maxime, Allaire, Andréa, Weil, Alexander G., Atkinson, Jeffrey, Farmer, Jean-Pierre, Dudley, Roy W. R., Larouche, Valerie, Crevier, Louis, Albrecht, Steffen, Filbin, Mariella G., Sartelet, Hervé, Lutz, Pierre-Eric, Nagy, Corina, Turecki, Gustavo, Costantino, Santiago, Dirks, Peter B., Murai, Keith K., Bourque, Guillaume, Ragoussis, Jiannis, Garzia, Livia, Taylor, Michael D., Jabado, Nada, and Kleinman, Claudia L.

Published
2019
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