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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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Genomic basis for RNA alterations in cancer (vol 578, pg 129, 2020)

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NATURE 2023年第7948期614卷 E37-E37页

作者： Calabrese, Claudia Davidson, Natalie R. Demircioglu, Deniz Fonseca, Nuno A. He, Yao Lehmann, Kjong-Van Liu, Fenglin Shiraishi, Yuichi Soulette, Cameron M. Urban, Lara Greger, Liliana Li, Siliang Liu, Dongbing Perry, Marc D. Xiang, Qian Zhang, Fan Zhang, Junjun Bailey, Peter Erkek, Serap Hoadley, Katherine A. Hou, Yong Huska, Matthew R. Kilpinen, Helena Korbel, Jan O. Marin, Maximillian G. Markowski, Julia Nandi, Tannistha Pan-Hammarstrom, Qiang Pedamallu, Chandra Sekhar Siebert, Reiner Stark, Stefan G. Su, Hong Tan, Patrick Waszak, Sebastian M. Yung, Christina Zhu, Shida Awadalla, Philip Creighton, Chad J. Meyerson, Matthew Ouellette, B. F. Francis Wu, Kui Yang, Huanming Brazma, Alvis Brooks, Angela N. Goke, Jonathan Ratsch, Gunnar Schwarz, Roland F. Stegle, Oliver Zhang, Zemin European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources Universidade do Porto Vairão Portugal Berlin Institute for Medical Systems Biology Max Delbruck Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) partner site Berlin Germany German Cancer Research Center (DKFZ) Heidelberg Germany Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) Partner site Berlin Berlin Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Division of Computational Genomics and Systems Genetics German Cancer Research Center (DKFZ) Heidelberg Germany ETH Zurich Zurich Switzerland Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Medical College New York NY USA SIB Swiss Institute of Bioinformatics Lausanne Switzerland University Hospital Zurich Zurich Switzerland Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Department of Biology ETH Zurich Zürich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Korea University Seoul South Korea Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center 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 New York NY USA National University of Singapore Singapore Singapore Genome Institute of Singapore Singapore Singapore Computational and Systems Biology Genome Institute of Singap

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Eliminating artefacts in polarimetric images using deep learning

arXiv

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arXiv 2019年

作者： Paranjpye, D. Mahabal, A. Ramaprakash, A.N. Panopoulou, G.V. Cleary, K. Readhead, A.C.S. Blinov, D. Tassis, K. Department of Electrical and Computer Engineering University of Michigan 1301 Beal Ave Ann ArborMI48109 United States Division of Physics Mathematics and Astronomy California Institute of Technology PasadenaCA91125 United States Inter-University Center for Astronomy and Astrophysics Post Bag No. 4 Ganeshkhind Pune411007 India Department of Physics Institute of Theoretical & Computational Physics University of Crete Heraklion Greece Institute of Astrophysics Foundation for Research and Technology Hellas Vassilika Vouton HeraklionGR-70013 Greece

Polarization measurements done using Imaging Polarimeters such as the Robotic Polarimeter are very sensitive to the presence of artefacts in images. Artefacts can range from internal reflections in a telescope to satellite trails that could contaminate an area of interest in the image. With the advent of wide-field polarimetry surveys, it is imperative to develop methods that automatically flag artefacts in images. In this paper, we implement a Convolutional Neural Network to identify the most dominant artefacts in the images. We find that our model can successfully classify sources with 98% true positive and 97% true negative rates. Such models, combined with transfer learning, will give us a running start in artefact elimination for near-future surveys like WALOP. Copyright © 2019, The Authors. All rights reserved.

关键词： Polarimeters

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Configurational entropy of magnetic skyrmions as an ideal gas

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Physical Review B 2019年第17期99卷 174440-174440页

作者： R. Zivieri R. Tomasello O. Chubykalo-Fesenko V. Tiberkevich M. Carpentieri G. Finocchio Department of Mathematical and Computer Sciences Physical Sciences and Earth Sciences University of Messina 98166 Messina Italy Institute of Applied and Computational Mathematics Foundation for Research and Technology GR 700 13 Heraklion Crete Greece Instituto de Ciencia de Materiales de Madrid CSIC Cantoblanco 28049 Madrid Spain Department of Physics Oakland University Rochester Michigan 48309 USA Department of Electrical and Information Engineering Politecnico di Bari 70125 Bari Italy

The study of thermodynamics of topological defects is an important challenge to understand their underlying physics. Among them, magnetic skyrmions have a leading role for their physical properties and potential applications in storage and neuromorphic computing. In this paper, the thermodynamic statistics of magnetic skyrmions is derived. It is shown that the skyrmion free energy can be modeled via a parabolic function and the diameters statistics obeys the Maxwell-Boltzmann distribution. This allows for making an analogy between the behavior of the distribution of skyrmion diameters statistics and the diluted gas Maxwell-Boltzmann molecules distribution of velocities at thermodynamic equilibrium. The calculation of the skyrmion configurational entropy, due to thermally induced changes of size and shape of the skyrmion, is essential for the determination of thermal fluctuations of the skyrmion energy around its average value. These results can be employed to advance the field of skyrmionics.

关键词： Micromagnetism Skyrmions Spintronics Ferromagnets Thin films Landau-Lifschitz-Gilbert equation Micromagnetic modeling

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A minimal mechanosensing model predicts keratocyte evolution on flexible substrates

arXiv

引用

arXiv 2018年

作者： Zhang, Zhiwen Rosakis, Phoebus Hou, Thomas Y. Ravichandran, Guruswami Department of Mathematics The University of Hong Kong Pokfulam Road Hong Kong SAR Hong Kong Department of Mathematics and Applied Mathematics University of Crete Heraklion Crete70013 Greece Institute of Applied and Computational Mathematics Foundation for Research and Technology-Hellas Voutes Crete70013 Greece Computing and Mathematical Sciences California Institute of Technology PasadenaCA91125 United States Division of Engineering and Applied Science California Institute of Technology PasadenaCA91125 United States

A mathematical model is proposed for shape evolution and locomotion of fish epidermal keratocytes on elastic substrates. The model is based on mechanosensing concepts: cells apply contractile forces onto the elastic substrate, while cell shape evolution depends locally on the substrate stress generated by themselves or external mechanical stimuli acting on the substrate. We use the level set method to study the behavior of the model numerically, and predict a number of distinct phenomena observed in experiments, such as (i) symmetry breaking from the stationary centrosymmetric to the well-known steadily propagating crescent shape, (ii) asymmetric bipedal oscillations and traveling waves in the lamellipodium leading edge (iii) response to mechanical stress externally applied to the substrate (tensotaxis), (iv) changing direction of motion towards an interface with a rigid substrate (durotaxis) and (v) the configuration of substrate wrinkles induced by contractile forces applied by the keratocyte. Copyright © 2018, The Authors. All rights reserved.

关键词： Substrates

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The Event Horizon Telescope Image of the Quasar NRAO 530

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Astrophysical Journal 2023年第2期943卷 170-170页

作者： Jorstad, Svetlana Wielgus, Maciek Lico, Rocco Issaoun, Sara Broderick, Avery E. Pesce, Dominic W. Liu, Jun Zhao, Guang-Yao Krichbaum, Thomas P. Blackburn, Lindy Chan, Chi-Kwan Janssen, Michael Ramakrishnan, Venkatessh Akiyama, Kazunori Alberdi, Antxon Algaba, Juan Carlos Bouman, Katherine L. Cho, Ilje Fuentes, Antonio Gómez, José L. Gurwell, Mark Johnson, Michael D. Kim, Jae-Young Lu, Ru-Sen Martí-Vidal, Iván Moscibrodzka, Monika Pötzl, Felix M. Traianou, Efthalia van Bemmel, Ilse Alef, Walter Anantua, Richard Asada, Keiichi Azulay, Rebecca Bach, Uwe Baczko, Anne-Kathrin Ball, David Baloković, Mislav Barrett, John Bauböck, Michi Benson, Bradford A. Bintley, Dan Blundell, Raymond Bower, Geoffrey C. Boyce, Hope Bremer, Michael Brinkerink, Christiaan D. Brissenden, Roger Britzen, Silke Broguiere, Dominique Bronzwaer, Thomas Bustamante, Sandra Byun, Do-Young Carlstrom, John E. Ceccobello, Chiara Chael, Andrew Chatterjee, Koushik Chatterjee, Shami Chen, Ming-Tang Chen, Yongjun Cheng, Xiaopeng Christian, Pierre Conroy, Nicholas S. Conway, John E. Cordes, James M. Crawford, Thomas M. Crew, Geoffrey B. Cruz-Osorio, Alejandro Cui, Yuzhu Davelaar, Jordy De Laurentis, Mariafelicia Deane, Roger Dempsey, Jessica Desvignes, Gregory Dexter, Jason Dhruv, Vedant Doeleman, Sheperd S. Dougal, Sean Dzib, Sergio A. Eatough, Ralph P. Emami, Razieh Falcke, Heino Farah, Joseph Fish, Vincent L. Fomalont, Ed Ford, H. Alyson Fraga-Encinas, Raquel Freeman, William T. Friberg, Per Fromm, Christian M. Galison, Peter Gammie, Charles F. García, Roberto Gentaz, Olivier Georgiev, Boris Goddi, Ciriaco Gold, Roman Gómez-Ruiz, Arturo I. Gu, Minfeng Hada, Kazuhiro Haggard, Daryl Haworth, Kari Hecht, Michael H. Hesper, Ronald Heumann, Dirk Ho, Luis C. Ho, Paul Honma, Mareki Huang, Chih-Wei L. Huang, Lei Hughes, David H. Ikeda, Shiro Impellizzeri, C.M. Violette Inoue, Makoto James, David J. Jannuzi, Buell T. Jeter, Britton Jiang, Wu Jiménez-Rosales, Alejandra Joshi, Abhishek V. Jung, Taehyun Karami, Mansour Karuppusamy, Ramesh Kawashima, Tomohisa Keati Institute for Astrophysical Research Boston University 725 Commonwealth Avenue Boston 02215 MA United States Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 Bonn D-53121 Germany Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada E-18008 Spain INAF-Istituto di Radioastronomia Via P. Gobetti 101 Bologna I-40129 Italy Center for Astrophysics Harvard & Smithsonian 60 Garden Street Cambridge 02138 MA United States NASA Hubble Fellowship Program Perimeter Institute for Theoretical Physics 31 Caroline Street North Waterloo N2L 2Y5 ON Canada Department of Physics and Astronomy University of Waterloo 200 University Avenue West Waterloo N2L 3G1 ON Canada Waterloo Centre for Astrophysics University of Waterloo Waterloo N2L 3G1 ON Canada Harvard University 20 Garden Street Cambridge 02138 MA United States Steward Observatory Department of Astronomy University of Arizona 933 N. Cherry Avenue Tucson 85721 AZ United States Data Science Institute University of Arizona 1230 N. Cherry Avenue Tucson 85721 AZ United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita Tucson 85721 AZ United States Astronomy Department Universidad de Concepción Casilla 160-C Concepción Chile Finnish Centre for Astronomy with ESO University of Turku FI-20014 Finland Aalto University Metsähovi Radio Observatory Metsähovintie 114 Kylmälä FI-02540 Finland Massachusetts Institute of Technology Haystack Observatory 99 Millstone Road Westford 01886 MA United States National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo 181-8588 Japan Department of Physics Faculty of Science Universiti Malaya Kuala Lumpur 50603 Malaysia California Institute of Technology 1200 East California Boulevard Pasadena 91125 CA United States Department of Astronomy and Atmospheric Sciences Kyungpook National University Daegu 702-701 South Korea Shanghai Astronomical Observatory Chinese Academy of Sciences 80

We report on the observations of the quasar NRAO 530 with the Event Horizon Telescope (EHT) on 2017 April 5−7, when NRAO 530 was used as a calibrator for the EHT observations of Sagittarius A*. At z = 0.902, this is the most distant object imaged by the EHT so far. We reconstruct the first images of the source at 230 GHz, at an unprecedented angular resolution of ∼20 μas, both in total intensity and in linear polarization (LP). We do not detect source variability, allowing us to represent the whole data set with static images. The images reveal a bright feature located on the southern end of the jet, which we associate with the core. The feature is linearly polarized, with a fractional polarization of ∼5%-8%, and it has a substructure consisting of two components. Their observed brightness temperature suggests that the energy density of the jet is dominated by the magnetic field. The jet extends over 60 μas along a position angle ∼ −28°. It includes two features with orthogonal directions of polarization (electric vector position angle), parallel and perpendicular to the jet axis, consistent with a helical structure of the magnetic field in the jet. The outermost feature has a particularly high degree of LP, suggestive of a nearly uniform magnetic field. Future EHT observations will probe the variability of the jet structure on microarcsecond scales, while simultaneous multiwavelength monitoring will provide insight into the high-energy emission origin. © 2023. The Author(s). Published by the American Astronomical Society.

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Hypocoercivity-compatible finite element methods for the long-time computation of Kolmogorov’s equation

arXiv

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arXiv 2018年

作者： Georgoulis, Emmanuil H. Department of Mathematics University of Leicester LeicesterLE1 7RH United Kingdom Department of Mathematics School of Applied Mathematical and Physical Sciences National Technical University of Athens Zografou15780 Greece Institute of Applied and Computational Mathematics Foundation of Research and Technology – Hellas Vassilika Vouton 700 13 Heraklion Crete Greece

This work is concerned with the development of a family of Galerkin finite element methods for the classical Kolmogorov’s equation. Kolmogorov’s equation serves as a sufficiently rich, for our purposes, model problem for kinetic-type equations and is characterised by diffusion in one of the two (or three) spatial directions only. Nonetheless, its solution admits typically decay properties to some long time equilibrium, depending on closure by suitable boundary/decay-at-infinity conditions. A key attribute of the proposed family of methods is that they also admit similar decay properties at the (semi)discrete level for very general families of triangulations. The method construction uses ideas by the general theory of hypocoercivity developed by Villani [23], along with judicious choice of numerical flux functions. These developments turn out to be sufficient to imply that the proposed finite element methods admit a priori error bounds with constants independent of the final time, despite Kolmogorov equation’s degenerate diffusion nature. Thus, the new methods provably allow for robust error analysis for final times tending to infinity. The extension to three spatial dimensions is also briefly discussed. Copyright © 2018, The Authors. All rights reserved.

关键词： computational complexity

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Author Correction: Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

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Nature genetics 2023年第10期55卷 1778-1779页

作者： Nick Shrine Abril G Izquierdo Jing Chen Richard Packer Robert J Hall Anna L Guyatt Chiara Batini Rebecca J Thompson Chandan Pavuluri Vidhi Malik Brian D Hobbs Matthew Moll Wonji Kim Ruth Tal-Singer Per Bakke Katherine A Fawcett Catherine John Kayesha Coley Noemi Nicole Piga Alfred Pozarickij Kuang Lin Iona Y Millwood Zhengming Chen Liming Li Sara R A Wijnant Lies Lahousse Guy Brusselle Andre G Uitterlinden Ani Manichaikul Elizabeth C Oelsner Stephen S Rich R Graham Barr Shona M Kerr Veronique Vitart Michael R Brown Matthias Wielscher Medea Imboden Ayoung Jeong Traci M Bartz Sina A Gharib Claudia Flexeder Stefan Karrasch Christian Gieger Annette Peters Beate Stubbe Xiaowei Hu Victor E Ortega Deborah A Meyers Eugene R Bleecker Stacey B Gabriel Namrata Gupta Albert Vernon Smith Jian'an Luan Jing-Hua Zhao Ailin F Hansen Arnulf Langhammer Cristen Willer Laxmi Bhatta David Porteous Blair H Smith Archie Campbell Tamar Sofer Jiwon Lee Martha L Daviglus Bing Yu Elise Lim Hanfei Xu George T O'Connor Gaurav Thareja Omar M E Albagha Karsten Suhre Raquel Granell Tariq O Faquih Pieter S Hiemstra Annelies M Slats Benjamin H Mullin Jennie Hui Alan James John Beilby Karina Patasova Pirro Hysi Jukka T Koskela Annah B Wyss Jianping Jin Sinjini Sikdar Mikyeong Lee Sebastian May-Wilson Nicola Pirastu Katherine A Kentistou Peter K Joshi Paul R H J Timmers Alexander T Williams Robert C Free Xueyang Wang John L Morrison Frank D Gilliland Zhanghua Chen Carol A Wang Rachel E Foong Sarah E Harris Adele Taylor Paul Redmond James P Cook Anubha Mahajan Lars Lind Teemu Palviainen Terho Lehtimäki Olli T Raitakari Jaakko Kaprio Taina Rantanen Kirsi H Pietiläinen Simon R Cox Craig E Pennell Graham L Hall W James Gauderman Chris Brightling James F Wilson Tuula Vasankari Tarja Laitinen Veikko Salomaa Dennis O Mook-Kanamori Nicholas J Timpson Eleftheria Zeggini Josée Dupuis Caroline Hayward Ben Brumpton Claudia Langenberg Stefan Weiss Georg Homuth Carsten Oliver Schmidt Nicole Probst-Hensch Marjo-Riitta Jarvelin Alanna C Morrison Ozren Polasek Igor Department of Population Health Sciences University of Leicester Leicester UK. nick.shrine@leicester.ac.uk. Department of Population Health Sciences University of Leicester Leicester UK. Division of Respiratory Medicine and NIHR Nottingham Biomedical Research Centre University of Nottingham Nottingham UK. Leicester National Institute for Health and Care Research Biomedical Research Centre Glenfield Hospital Leicester UK. Channing Division of Network Medicine Division of Pulmonary and Critical Care Medicine Department of Medicine Brigham and Women's Hospital Boston MA USA. Harvard Medical School Boston MA USA. COPD Foundation Washington DC USA. Department of Clinical Science Unversity of Bergen Bergen Norway. Nuffield Department of Population Health University of Oxford Oxford UK. MRC Population Health Research Unit University of Oxford Oxford UK. Department of Epidemiology and Biostatistics School of Public Health Peking University Health Science Center Beijing China. Department of Respiratory Diseases Ghent Universital Hospital Ghent Belgium. Department of Bioanalysis Faculty of Pharmaceutical Sciences Ghent University Ghent Belgium. Department of Epidemiology Eramus Medical Center Rotterdam The Netherlands. Department of Internal Medicine Eramus Medical Center Rotterdam The Netherlands. Center for Public Health Genomics University of Virginia Charlottesville VA USA. Department of Medicine Columbia University Medical Center New York NY USA. Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK. Human Genetics Center Department of Epidemiology Human Genetics and Environmental Sciences School of Public Health The University of Texas Health Science Center at Houston Houston TX USA. MRC Centre for Environment and Health Department of Epidemiology and Biostatistics School of Public Health Imperial College London London UK. Department of Epidemiology and Public Health Swiss Tropical

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Wellcome Sanger Institute Wellcome Genome Campus Hinxton Cambridge CB10 1SA UK Korea Advanced Institute of Science and Technology Daejeon 34141 South Korea Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Korea Advanced Institute of Science and Technology Daejeon South Korea Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston MA USA Ludwig Center at Harvard Medical School Boston MA USA Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Broad Institute of MIT and Harvard

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Gaussian asymptotic limits for the α-transformation in the analysis of compositional data

arXiv

引用

arXiv 2018年

作者： Pantazis, Yannis Tsagris, Michail T. Wood, Andrew T.A. Institute of Applied and Computational Mathematics Foundation for Research and Technology - Hellas Heraklion70013 Greece Department of Economics University of Crete Rethymnon74100 Greece School of Mathematical Sciences University of Nottingham NottinghamNG7 2RD United Kingdom

Compositional data consists of vectors of proportions whose components sum to 1. Such vectors lie in the standard simplex, which is a manifold with boundary. One issue that has been rather controversial within the field of compositional data analysis is the choice of metric on the simplex. One popular possibility has been to use the metric implied by log-transforming the data, as proposed by Aitchison [1, 2];and another popular approach has been to use the standard Euclidean metric inherited from the ambient space. Tsagris et al. [21] proposed a one-parameter family of power transformations, the α-transformations, which include both the metric implied by Aitchison’s transformation and the Euclidean metric as particular cases. Our underlying philosophy is that, with many datasets, it may make sense to use the data to help us determine a suitable metric. A related possibility is to apply the α-transformations to a parametric family of distributions, and then estimate α along with the other parameters. However, as we shall see, when one follows this last approach with the Dirichlet family, some care is needed in a certain limiting case which arises (α → 0), as we found out when fitting this model to real and simulated data. Specifically, when the maximum likelihood estimator of α is close to 0, the other parameters tend to be large. The main purpose of the paper is to study this limiting case both theoretically and numerically and to provide insight into these numerical *** Codes 62E20, 62H12 Copyright © 2018, The Authors. All rights reserved.

关键词： Maximum likelihood estimation

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