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Agile parallel bioinformatics workflow management using Pwrake

BMC Research Notes 2011年第1期4卷 1-8页

作者： Mishima, Hiroyuki Sasaki, Kensaku Tanaka, Masahiro Tatebe, Osamu Yoshiura, Koh-Ichiro Department of Human Genetics Nagasaki University Graduate School of Biomedical Sciences Nagasaki Nagasaki 1-12-4 Sakamoto Japan Nagasaki University Global Center of Excellence Program Nagasaki Nagasaki 1-12-4 Sakamoto Japan Center for Computational Sciences University of Tsukuba Tsukuba Ibaraki 1-1-1 Tennodai Japan Core Research for Evolutional Science and Technology Japan Science and Technology Agency Kawaguchi Saitama 4-1-8 Honcho Japan Departmentent of Computer Science Graduate School of Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki 1-1-1 Tennodai Japan

Background: In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error. Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. Findings. We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Conclusions: Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability

关键词： Ruby Iterative Development Agile Software Development Host Language Bioinformatics Domain

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Electronic medical information systems and timeliness of care in the emergency department: a scoping review

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Discover Health Systems 2024年第1期3卷 1-22页

作者： Lacasse, Melissa L. Hendel, Ericha T. Farhat, Nawal Kelly, Dayton J. Mah, Emily M. Campbell, Alanna Ansell, Dominique R. Bourdon, Christopher A. Christie, Tyler S. Volpini, Steve Liu, Lisa J. W. Cragg, Jacquelyn J. Crispo, James A. G. Undergraduate Medical Education Program NOSM University Thunder Bay Canada Undergraduate Medical Education Program NOSM University Sudbury Canada School of Mathematics and Statistics Carleton University Ottawa Canada TruEffect Inc. Sudbury Canada Faculty of Health Sciences McMaster University Hamilton Canada Health Sciences Library NOSM University Sudbury Canada Human Sciences Division NOSM University Sudbury Canada Emergency Department Health Sciences North Sudbury Canada Clinical Sciences Division NOSM University Sudbury Canada Information Technology & Privacy Health Sciences North Sudbury Canada Collaboration for Outcomes Research and Evaluation (CORE) Faculty of Pharmaceutical Sciences University of British Columbia Vancouver Canada International Collaboration on Repair Discoveries (ICORD) University of British Columbia Vancouver Canada

Although many emergency department (ED) settings have implemented an electronic medical information system (EMIS) and EMIS tools in an effort to improve timeliness of care outcomes, there remains a paucity of scientific information on this topic. We therefore performed a scoping review to describe the range of EMIS interventions and their impacts on time-based outcomes in the ED. We searched four bibliographic databases to identify potentially relevant records published after 2014 in English. Two reviewers assessed records for eligibility using a two-step screening process. We then extracted data on the type of EMIS, outcomes assessed, and reported results. Findings were summarized in tabular form and grouped by time-based outcome. Twenty-five studies met the eligibility criteria, with approximately half being retrospective studies. Interventions varied among studies; they generally included a new or updated EMIS, EMIS tools related to disease diagnosis and/or management, triage tools, or health information exchange platforms. Included studies compared interventions with relevant comparator groups, such as prior versions of an EMIS, absence of an EMIS, pen-and-paper documentation, and/or communication via telephone and fax. The most common outcomes reported were length of stay (n = 17 studies) and time to medication (n = 6 studies), followed by time to order, time to provider, and time from result to disposition. Reported effects of the interventions were generally inconsistent, showing either improvements, delays, or no change in examined outcomes. Additional research is needed to determine how electronic medical information may be used in the ED to improve timeliness of care. Findings from this review can be used to inform future systematic reviews that evaluate the impact of these systems and tools on specific quality of care measures.

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Generating dermatopathology reports from gigapixel whole slide images with HistoGPT

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Nature communications 2025年第1期16卷 4886页

作者： Manuel Tran Paul Schmidle Ruifeng Ray Guo Sophia J Wagner Valentin Koch Valerio Lupperger Brenna Novotny Dennis H Murphree Heather D Hardway Marina D'Amato Judith Lefkes Daan J Geijs Annette Feuchtinger Alexander Böhner Robert Kaczmarczyk Tilo Biedermann Avital L Amir Antien L Mooyaart Francesco Ciompi Geert Litjens Chen Wang Nneka I Comfere Kilian Eyerich Stephan A Braun Carsten Marr Tingying Peng Helmholtz AI Helmholtz Munich Neuherberg Germany. School of Computation Information and Technology Technical University of Munich Munich Germany. Department of Dermatology Medical Center University of Freiburg Freiburg Germany. Department of Laboratory Medicine and Pathology Mayo Clinic Jacksonville FL USA. Institute of AI for Health Helmholtz Munich Neuherberg Germany. MLL Munich Leukemia Laboratory Munich Germany. Department of Quantitative Health Sciences Mayo Clinic Rochester MN USA. Digital Health Artificial Intelligence and Innovations Program Mayo Clinic Rochester MN USA. Computational Pathology Group Radboud University Medical Center Nijmegen The Netherlands. Oncode Institute Utrecht The Netherlands. Core Facility Pathology and Tissue Analytics Helmholtz Munich Neuherberg Germany. Department of Dermatology and Allergy Technical University of Munich Munich Germany. Department of Pathology Radboud University Medical Center Nijmegen The Netherlands. Department of Pathology Erasmus University Medical Center Rotterdam The Netherlands. Department of Dermatology and Laboratory Medicine & Pathology Mayo Clinic Rochester MN USA. Department of Dermatology Medical Center University of Freiburg Freiburg Germany. kilian.eyerich@uniklinik-freiburg.de. Dermatology Department University Hospital Münster Münster Germany. stephanalexander.braun@ukmuenster.de. Department of Dermatology Medical Faculty Heinrich-Heine University Düsseldorf Germany. stephanalexander.braun@ukmuenster.de. Helmholtz AI Helmholtz Munich Neuherberg Germany. carsten.marr@helmholtz-munich.de. Institute of AI for Health Helmholtz Munich Neuherberg Germany. carsten.marr@helmholtz-munich.de. Helmholtz AI Helmholtz Munich Neuherberg Germany. tingying.peng@helmholtz-munich.de. School of Computation Information and Technology Technical University of Munich Munich Germany. tingying.peng@helmholtz-munich.de.

Histopathology is the reference standard for diagnosing the presence and nature of many diseases, including cancer. However, analyzing tissue samples under a microscope and summarizing the findings in a comprehensive pathology report is time-consuming, labor-intensive, and non-standardized. To address this problem, we present HistoGPT, a vision language model that generates pathology reports from a patient's multiple full-resolution histology images. It is trained on 15,129 whole slide images from 6705 dermatology patients with corresponding pathology reports. The generated reports match the quality of human-written reports for common and homogeneous malignancies, as confirmed by natural language processing metrics and domain expert analysis. We evaluate HistoGPT in an international, multi-center clinical study and show that it can accurately predict tumor subtypes, tumor thickness, and tumor margins in a zero-shot fashion. Our model demonstrates the potential of artificial intelligence to assist pathologists in evaluating, reporting, and understanding routine dermatopathology cases.

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A Moment-Based Method for Large-Scale Generalized Eigenvalue Problems

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Applied Numerical Analysis & Computational Mathematics 2004年第2期1卷

作者： Tetsuya Sakurai Hiroto Tadano Yuichi Inadomi Umpei Nagashima Department of Computer Science University of Tsukuba Tsukuba 305-8573 Japan Core Research for Evolutional Science and Technology Japan (CREST) Doctoral Program of Systems and Information Engineering University of Tsukuba Tsukuba 305-8573 Japan Grid Technology Research Center National Institute of Advanced Industrial Science and Technology Tsukuba 305-8568 Japan

In this paper we consider a method for finding several eigenvalues and corresponding eigenvectors of large-scale generalized eigenvalue problems. In this method, a small matrix pencil that has only the desired eigenvalues is derived using complex moments obtained via numerical integration. Since the process to derive the moments can be performed in parallel and we do not need to exchange data between processes, the presented method is suitable for master-worker programming models. We have implemented and tested the proposed method in a grid RPC (remote procedure call) system. Numerical examples illustrate the properties of our approach. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

关键词： Eigenvalue problems moment-based method parallel algorithm

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Kidney multiome-based genetic scorecard reveals convergent coding and regulatory variants

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Science (New York, N.Y.) 2025年第6734期387卷 eadp4753页

作者： Liu, Hongbo Abedini, Amin Ha, Eunji Ma, Ziyuan Sheng, Xin Dumoulin, Bernhard Qiu, Chengxiang Aranyi, Tamas Li, Shen Dittrich, Nicole Chen, Hua-Chang Tao, Ran Tarng, Der-Cherng Hsieh, Feng-Jen Chen, Shih-Ann Yang, Shun-Fa Lee, Mei-Yueh Kwok, Pui-Yan Wu, Jer-Yuarn Chen, Chien-Hsiun Khan, Atlas Limdi, Nita A. Wei, Wei-Qi Walunas, Theresa L. Karlson, Elizabeth W. Kenny, Eimear E. Luo, Yuan Kottyan, Leah Connolly, John J. Jarvik, Gail P. Weng, Chunhua Shang, Ning Cole, Joanne B. Mercader, Josep M. Mandla, Ravi Majarian, Timothy D. Florez, Jose C. Haas, Mary E. Lotta, Luca A. Drivas, Theodore G. Vy, Ha My T Nadkarni, Girish N. Wiley, Laura K. Wilson, Melissa P. Gignoux, Christopher R. Rasheed, Humaira Thomas, Laurent F. Åsvold, Bjørn Olav Brumpton, Ben M. Hallan, Stein I. Hveem, Kristian Zheng, Jie Hellwege, Jacklyn N. Zawistowski, Matthew Zöllner, Sebastian Franceschini, Nora Hu, Hailong Zhou, Jianfu Kiryluk, Krzysztof Ritchie, Marylyn D. Palmer, Matthew Edwards, Todd L. Voight, Benjamin F. Hung, Adriana M. Susztak, Katalin Department of Medicine Renal Electrolyte and Hypertension Division University of Pennsylvania Philadelphia PA United States Institute of Diabetes Obesity and Metabolism University of Pennsylvania Philadelphia PA United States Department of Genetics University of Pennsylvania Philadelphia PA United States Penn-CHOP Kidney Innovation Center University of Pennsylvania Philadelphia PA United States Liangzhu Laboratory Zhejiang University 1369 West Wenyi Road Hangzhou Zhejiang China Department of Nephrology Children' Hospital Zhejiang University School of Medicine National Clinical Research Center for Child Health Hangzhou Zhejiang China Institute of Molecular Life Sciences HUN-REN Research Center for Natural Sciences Budapest Hungary Department of Molecular Biology Semmelweis University Budapest Hungary Department of Medicine Federal University of São Paulo São Paulo Brazil Department of Biostatistics Vanderbilt University Medical Center Nashville TN United States Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN United States Institute of Clinical Medicine School of Medicine National Yang Ming Chiao Tung University ROC Taipei Taiwan Division of Nephrology Department of Medicine Taipei Veterans General Hospital ROC Taipei Taiwan Institute of Biomedical Sciences Academia Sinica ROC Taipei Taiwan Cardiovascular Center Taichung Veterans General Hospital Taichung Taiwan ROC National Chung Hsing University Taichung Taiwan ROC Heart Rhythm Center Division of Cardiology Department of Medicine Taipei Veterans General Hospital ROC Taipei Taiwan Department of Internal Medicine College of Medicine National Yang Ming Chiao Tung University ROC Taipei Taiwan Institute of Medicine Chung Shan Medical University Taichung Taiwan ROC Department of Medical Research Chung Shan Medical University Hospital Taichung Taiwan ROC Division of Endocrinology and Metabolism Department of Internal Medicine Kaohsiung Medical Universit

Kidney dysfunction is a major cause of mortality, but its genetic architecture remains elusive. In this study, we conducted a multiancestry genome-wide association study in 2.2 million individuals and identified 1026 (97 previously unknown) independent loci. Ancestry-specific analysis indicated an attenuation of newly identified signals on common variants in European ancestry populations and the power of population diversity for further discoveries. We defined genotype effects on allele-specific gene expression and regulatory circuitries in more than 700 human kidneys and 237,000 cells. We found 1363 coding variants disrupting 782 genes, with 601 genes also targeted by regulatory variants and convergence in 161 genes. Integrating 32 types of genetic information, we present the "Kidney Disease Genetic Scorecard" for prioritizing potentially causal genes, cell types, and druggable targets for kidney disease.

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A consensus protocol for functional connectivity analysis in the rat brain (vol 26, pg 673, 2023)

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NATURE NEUROSCIENCE 2023年第6期26卷 1127-1128页

作者： Grandjean, Joanes Desrosiers-Gregoire, Gabriel Anckaerts, Cynthia Angeles-Valdez, Diego Ayad, Fadi Barriere, David A. Blockx, Ines Bortel, Aleksandra Broadwater, Margaret Cardoso, Beatriz M. Celestine, Marina Chavez-Negrete, Jorge E. Choi, Sangcheon Christiaen, Emma Clavijo, Perrin Colon-Perez, Luis Cramer, Samuel Daniele, Tolomeo Dempsey, Elaine Diao, Yujian Doelemeyer, Arno Dopfel, David Dvorakova, Lenka Falfan-Melgoza, Claudia Fernandes, Francisca F. Fowler, Caitlin F. Fuentes-Ibanez, Antonio Garin, Clement M. Gelderman, Eveline Golden, Carla E. M. Guo, Chao C. G. Henckens, Marloes J. A. G. Hennessy, Lauren A. Herman, Peter Hofwijks, Nita Horien, corey Ionescu, Tudor M. Jones, Jolyon Kaesser, Johannes Kim, Eugene Lambers, Henriette Lazari, Alberto Lee, Sung-Ho Lillywhite, Amanda Liu, Yikang Liu, Yanyan Y. Lopez-Castro, Alejandra Lopez-Gil, Xavier Ma, Zilu MacNicol, Eilidh Madularu, Dan Mandino, Francesca Marciano, Sabina McAuslan, Matthew J. McCunn, Patrick McIntosh, Alison Meng, Xianzong Meyer-Baese, Lisa Missault, Stephan Moro, Federico Naessens, Daphne M. P. Nava-Gomez, Laura J. Nonaka, Hiroi Ortiz, Juan J. Paasonen, Jaakko Peeters, Lore M. Pereira, Mickael Perez, Pablo D. Pompilus, Marjory Prior, Malcolm Rakhmatullin, Rustam Reimann, Henning M. Reinwald, Jonathan Del Rio, Rodrigo Triana Rivera-Olvera, Alejandro Ruiz-Perez, Daniel Russo, Gabriele Rutten, Tobias J. Ryoke, Rie Sack, Markus Salvan, Piergiorgio Sanganahalli, Basavaraju G. Schroeter, Aileen Seewoo, Bhedita J. Selingue, Erwan Seuwen, Aline Shi, Bowen Sirmpilatze, Nikoloz Smith, Joanna A. B. Smith, Corrie Sobczak, Filip Stenroos, Petteri J. Straathof, Milou Strobelt, Sandra Sumiyoshi, Akira Takahashi, Kengo Torres-Garcia, Maria E. Tudela, Raul van den Berg, Monica van der Marel, Kajo van Hout, Aran T. B. Vertullo, Roberta Vidal, Benjamin Vrooman, Roel M. Wang, Victora X. Wank, Isabel Watson, David J. G. Yin, Ting Zhang, Yongzhi Zurbruegg, Stefan Achard, Sophie Alcauter, Sarael Auer, Dorothee P. Barbier, Emmanuel L. Baudewig, Juergen Beckmann, Chri Donders Institute for Brain Behaviour and Cognition Radboud University Nijmegen The Netherlands Department for Medical Imaging Radboud University Medical Center Nijmegen The Netherlands Cerebral Imaging Centre Douglas Mental Health University Institute Verdun QC Canada Integrated Program in Neuroscience McGill University Montreal QC Canada Bio-imaging Lab University of Antwerp Antwerp Belgium µNEURO Research Centre of Excellence University of Antwerp Antwerp Belgium Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro Mexico Biological and Biomedical Engineering McGill University Montreal QC Canada McConnell Brain Imaging Centre McGill University Montreal QC Canada Montreal Neurological Institute McGill University Montreal QC Canada UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction Physiologie de la reproduction et des comportements Centre de recherche INRAE de Nouzilly Tours France Department of Neurology and Neurosurgery McGill University Montreal QC Canada Center for Animal MRI University of North Carolina at Chapel Hill Chapel Hill NC USA Department of Neurology University of North Carolina at Chapel Hill Chapel Hill NC USA Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill NC USA Preclinical MRI Champalimaud Research Champalimaud Centre for the Unknown Lisbon Portugal Laboratoire des Maladies Neurodégénératives Molecular Imaging Research Center (MIRCen) Université Paris-Saclay Commissariat à l’Énergie Atomique et aux Énergies Alternatives (CEA) CNRS Fontenay-aux-Roses France Departamento de Neurobiología Conductual y Cognitiva Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro México Translational Neuroimaging and Neural Control Group High-Field Magnetic Resonance Max Planck Institute for Biological Cybernetics Tuebingen Germany Graduate Training Centre of Neuroscience International Max

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.

关键词： Databases Neural circuits

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Genome-wide association study of long COVID

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Nature Genetics 2025年 1-16页

作者： Vilma Lammi Tomoko Nakanishi Samuel E. Jones Juha Karjalainen Martin Broberg Hele H. Haapaniemi Matti Pirinen Mari E. K. Niemi Mattia Cordioli Mark J. Daly Andrea Ganna Hanna M. Ollila J. Brent Richards Yukinori Okada Shea J. Andrews Beatriz Cortés Rafael de Cid Susana Iraola-Guzmán Natalia Blay Xavier Farré Heath E. O’Brien Thompson Hannah Patrick J. Short Ana Ochoa-Guzman Michelle Duran-Gomez Brian E. Fulton-Howard Masahiro Kanai Axel Schmidt Daniella Balla Julia Heggemann Sonja Schultz Pari Behzad Markus M. Nöthen Abigail Miller Kerstin U. Ludwig Ruth E. Mitchell George Davey Smith Nicholas J. Timpson Abdou Mousas Evangelos Evangelou Evangelia Ntzani Konstantinos K. Tsilidis Massimo Mangino Alicia Huerta-Chagoya Nasa Sinnott-Armstrong Elizabeth T. Cirulli Francisco Tanudjaja Efren Sandoval Nicole L. Washington Simon White Alexandre Bolze Kelly M. Schiabor Barrett Marc Vaudel Alex S. F. Kwong Amit K. Maiti Minttu M. Marttila Daniel C. Posner Alexis A. Rodriguez Chiara Batini Beatriz Guillen-Guio Olivia C. Leavy Anna L. Guyatt Catherine John Louise V. Wain Francesca Minnai Anna R. Dearman Benedict Hignell Meena Kumari C. A. Robert Warmerdam Lude H. Franke Celia B. Sequeros Søren Brunak David Westergaard Karina Banasik Thomas W. Winkler Iris M. Heid Daniel M. Jordan Ryan C. Thompson Alexander W. Charney Laura G. Sloofman Nicole W. Simons Noam D. Beckmann Raimonds Rešcenko Vita Rovite Peculis Raitis Monta Briviba Janis Klovinš Laura Ansone Lorenzo Miano Flora Peyvandi Francesco Malvestiti Nicola Montano Alessandra Bandera Francesco Bruno Arturo Blasi Jacqueline M. Lane Jakob M. Cherry Ryan K. Chung Laura Carvajal-Silva Kevin Aguilar-Valdés Leslie C. Cerpa Tamara V. Arévalo Eduardo Lamoza Alicia Colombo Ricardo A. Verdugo Erika Frangione Xu Xinyi Jennifer Taher Jordan Lerner-Ellis Lindsay Guare Shefali S. Verma Ekaterina Vergasova Michil Trofimov Layal Shaheen Nikolay Plotnikov Anna Kim Dmitrii Kharitonov Alexei Kamelin Alexander Rakitko Eirini Marouli Pasquale Striano Ummu Afeera Zainulabid Ashutosh Kumar Hajar Fa Institute for Molecular Medicine Finland (FIMM) Helsinki Institute of Life Science (HiLIFE) University of Helsinki Helsinki Finland Department of Human Genetics McGill University Montreal Quebec Canada Centre for Clinical Epidemiology Department of Medicine Lady Davis Institute Jewish General Hospital McGill University Montreal Quebec Canada Kyoto-McGill International Collaborative Program in Genomic Medicine Graduate School of Medicine Kyoto University Kyoto Japan Department of Genome Informatics Graduate School of Medicine the University of Tokyo Tokyo Japan Research Fellow Japan Society for the Promotion of Science Tokyo Japan Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of Harvard and MIT Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Department of Mathematics and Statistics University of Helsinki Helsinki Finland Department of Public Health University of Helsinki Helsinki Finland Broad Institute Cambridge MA USA Analytical and Translational Genetics Unit Massachusetts General Hospital Harvard Medical School Boston MA USA Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Anesthesia Critical Care and Pain Medicine Massachusetts General Hospital and Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Twin Research King’s College London London UK 5 Prime Sciences Inc Montreal Quebec Canada Department of Epidemiology Biostatistics and Occupational Health McGill University Montreal Quebec Canada Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan Laboratory for Systems Genetics RIKEN Center for Integrative Medical Sciences Yokohama Japan Laboratory of Statistical Immunology Immunology Frontier Research Center (WPI-IFReC) Osaka University Suita Japan Departmen

Infections can lead to persistent symptoms and diseases such as shingles after varicella zoster or rheumatic fever after streptococcal infections. Similarly, severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) infection can result in long coronavirus disease (COVID), typically manifesting as fatigue, pulmonary symptoms and cognitive dysfunction. The biological mechanisms behind long COVID remain unclear. We performed a genome-wide association study for long COVID including up to 6,450 long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We discovered an association ofFOXP4with long COVID, independent of its previously identified association with severe COVID-19. The signal was replicated in 9,500 long COVID cases and 798,835 population controls. Given the transcription factor FOXP4’s role in lung physiology and pathology, our findings highlight the importance of lung function in the pathophysiology of long COVID.

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FinnGen provides genetic insights from a well-phenotyped isolated population (vol 613, pg 508, 2023)

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NATURE 2023年第7952期615卷 E19-E19页

作者： Kurki, Mitja I. Karjalainen, Juha Palta, Priit Sipila, Timo P. Kristiansson, Kati Donner, Kati M. Reeve, Mary P. Laivuori, Hannele Aavikko, Mervi Kaunisto, Mari A. Loukola, Anu Lahtela, Elisa Mattsson, Hannele Laiho, Paivi Parolo, Pietro Della Briotta Lehisto, Arto A. Kanai, Masahiro Mars, Nina Ramo, Joel Kiiskinen, Tuomo Heyne, Henrike O. Veerapen, Kumar Rueger, Sina Lemmela, Susanna Zhou, Wei Ruotsalainen, Sanni Parn, Kalle Hiekkalinna, Tero Koskelainen, Sami Paajanen, Teemu Llorens, Vincent Gracia-Tabuenca, Javier Siirtola, Harri Reis, Kadri Elnahas, Abdelrahman G. Sun, Benjamin Foley, Christopher N. Aalto-Setala, Katriina Alasoo, Kaur Arvas, Mikko Auro, Kirsi Biswas, Shameek Bizaki-Vallaskangas, Argyro Carpen, Olli Chen, Chia-Yen Dada, Oluwaseun A. Ding, Zhihao Ehm, Margaret G. Eklund, Kari Farkkila, Martti Finucane, Hilary Ganna, Andrea Ghazal, Awaisa Graham, Robert R. Green, Eric M. Hakanen, Antti Hautalahti, Marco Hedman, Asa K. Hiltunen, Mikko Hinttala, Reetta Hovatta, Iiris Hu, Xinli Huertas-Vazquez, Adriana Huilaja, Laura Hunkapiller, Julie Jacob, Howard Jensen, Jan-Nygaard Joensuu, Heikki John, Sally Julkunen, Valtteri Jung, Marc Junttila, Juhani Kaarniranta, Kai Kahonen, Mika Kajanne, Risto Kallio, Lila Kalviainen, Reetta Kaprio, Jaakko Kerimov, Nurlan Kettunen, Johannes Kilpelainen, Elina Kilpi, Terhi Klinger, Katherine Kosma, Veli-Matti Kuopio, Teijo Kurra, Venla Laisk, Triin Laukkanen, Jari Lawless, Nathan Liu, Aoxing Longerich, Simonne Magi, Reedik Makela, Johanna Makitie, Antti Malarstig, Anders Mannermaa, Arto Maranville, Joseph Matakidou, Athena Meretoja, Tuomo Mozaffari, Sahar V. Niemi, Mari E. K. Niemi, Marianna Niiranen, Teemu O'Donnell, Christopher J. Obeidat, Ma'En Okafo, George Ollila, Hanna M. Palomaki, Antti Palotie, Tuula Partanen, Jukka Paul, Dirk S. Pelkonen, Margit Pendergrass, Rion K. Petrovski, Slave Pitkaranta, Anne Platt, Adam Pulford, David Punkka, Eero Pussinen, Pirkko Raghavan, Neha Rahimov, Fedik Rajpal, Deepak Renaud, Nicole A. Riley-Gillis, Bridget Rodosthenous, Rodostheni Institute for Molecular Medicine Finland (FIMM) Helsinki Institute of Life Science (HiLIFE) University of Helsinki Helsinki Finland Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of Harvard and MIT Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Estonian Genome Centre Institute of Genomics University of Tartu Tartu Estonia Medical and Clinical Genetics University of Helsinki and Helsinki University Hospital Helsinki Finland Department of Obstetrics and Gynecology Tampere University Hospital Tampere Finland Faculty of Medicine and Health Technology Center for Child Adolescent and Maternal Health University of Tampere Tampere Finland Department of Biomedical Informatics Harvard Medical School Boston MA USA Digital Health Center Hasso Plattner Institute for Digital Engineering University of Potsdam Potsdam Potsdam Germany Hasso Plattner Institute for Digital Health at Mount Sinai Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY USA Finnish Institute for Health and Welfare (THL) Helsinki Finland Department of Public Health University of Helsinki Helsinki Finland Anesthesia Critical Care and Pain Medicine Massachusetts General Hospital Boston MA USA Abdominal Center Endocrinology Helsinki University Hospital Helsinki Finland Folkhalsan Research Center Helsinki Finland Research Program of Clinical and Molecular Metabolism University of Helsinki Helsinki Finland Biocenter Oulu University of Oulu Oulu Finland Computational Medicine Center for Life Course Health Research Faculty of Medicine University of Oulu Oulu Finland Turku University Hospital and University of Turku Turku Finland University of Turku Turku Finland Helsinki Biobank University of Helsinki and Hospital District of Helsinki and Uusimaa Helsinki Finland TAUCHI Research Center

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Mapping the Human Body at Cellular Resolution -- The NIH Common Fund Human BioMolecular Atlas program

arXiv

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arXiv 2019年

作者： Snyder, Michael P. Lin, Shin Posgai, Amanda Atkinson, Mark Regev, Aviv Rood, Jennifer Rozenblatt-Rosen, Orit Gaffney, Leslie Hupalowska, Anna Satija, Rahul Gehlenborg, Nils Shendure, Jay Laskin, Julia Harbury, Pehr Nystrom, Nicholas A. Bar-Joseph, Ziv Zhang, Kun Börner, Katy Lin, Yiing Conroy, Richard Procaccini, Dena Roy, Ananda L. Pillai, Ajay Brown, Marishka Galis, Zorina S. Cai, Long Shendure, Jay Trapnell, Cole Lin, Shin Jackson, Dana Snyder, Michael P. Nolan, Garry Greenleaf, William James Lin, Yiing Plevritis, Sylvia Ahadi, Sara Lee, Hayan Nevins, Stephanie Esplin, Ed Horning, Aaron Bahmani, Amir Zhang, Kun Sun, Xin Jain, Sanjay Hagood, James Kharchenko, Peter Atkinson, Mark Bodenmiller, Bernd Brusko, Todd Clare-Salzler, Michael Nick, Harry Otto, Kevin Posgai, Amanda Wasserfall, Clive Maffioletti, Sergio Caprioli, Richard M. Spraggins, Jeffrey M. Gutierrez, Danielle Patterson, Nathan Heath Neumann, Elizabeth K. Harris, Raymond deCaestecker, Mark de Plas, Raf Van Lau, Ken Cai, Long Yuan, Guo-Cheng Zhu, Qian Dries, Ruben Yin, Peng Saka, Sinem K. Kishi, Jocelyn Y. Wang, Yu Goldaracena, Isabel Laskin, Julia Ye, DongHye Burnum-Johnson, Kristin E. Piehowski, Paul D. Ansong, Charles Zhu, Ying Harbury, Pehr Desai, Tushar Mulye, Jay Chou, Peter Nagendran, Monica Bar-Joseph, Ziv Teichmann, Sarah A. Paten, Benedict Murphy, Robert F. Ma, Jian Kiselev, Vladimir Yu Kingsford, Carl Ricarte, Allyson Ruffalo, Matthew Gehlenborg, Nils Kharchenko, Peter Vella, Margaret McCallum, Chuck Börner, Katy Cross, Leonard E. Friedman, Samuel H. Heiland, Randy Herr, Bruce Macklin, Paul Quardokus, Ellen M. Record, Lisel Sluka, James P. Weber, Griffin M. Nystrom, Nicholas A. Silverstein, Jonathan C. Blood, Philip D. Ropelewski, Alexander J. Shirey, William E. Mabee, Paula Lenhardt, W. Christopher Robasky, Kimberly Michailidis, Stavros Satija, Rahul Marioni, John Regev, Aviv Butler, Andrew Stuart, Tim Fisher, Eyal Ghazanfar, Shila Rood, Jennifer Gaffney, Leslie Ersalan, Gokcen Biancalani, Tommaso Conroy, Richard Procaccini, Dena Roy, Anan School of Medicine Stanford University 300 Pasteur Drive United States Department of Genetics Stanford School of Medicine StanfordCA94305 United States Department of Medicine University of Washington SeattleWA98195 United States Department of Pathology University of Florida Diabetes Institute GainesvilleFL32610 United States Klarman Cell Observatory Broad Institute of MIT and Harvard CambridgeMA02142 United States Howard Hughes Medical Institute Koch Institute of Integrative Cancer Research Department of Biology Massachusetts Institute of Technology CambridgeMA02140 United States New York Genome Center New York CityNY10013 United States New York University New YorkNY10012 United States Department of Biomedical Informatics Harvard Medical School BostonMA02115 United States Department of Genome Sciences University of Washington SeattleWA98105 United States Department of Chemistry Purdue University West LafayetteIN47907 United States Department of Biochemistry Stanford University School of Medicine StanfordCA94305 United States Pittsburgh Supercomputing Center Carnegie Mellon University PittsburghPA15213 United States Department of Computational Biology School of Computer Science Carnegie Mellon University PittsburghPA15213 United States Department of Bioengineering University of California San Diego La JollaCA92093 United States Department of Intelligent Systems Engineering School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Surgery Washington University School of Medicine St LouisMO63110 United States Division of Program Coordination Planning and Strategic Initiatives National Institutes of Health BethesdaMD20892 United States National Human Genome Research Institute National Institutes of Health BethesdaMD20892 United States National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20892 United States Caltech-UW TMC Departmen

Transformative technologies are enabling the construction of three dimensional (3D) maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible 3D molecular and cellular atlas of the human body, in health and various disease settings. Copyright © 2019, The Authors. All rights reserved.

关键词： Mapping

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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