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DOUBLY STOCHASTIC CONTINUOUS-TIME HIDDEN MARKOV APPROACH FOR ANALYZING GENOME TILING ARRAYS

ANNALS OF APPLIED STATISTICS 2009年第3期3卷 1183-1203页

作者： Johnson, W. Evan Liu, X. Shirley Liu, Jun S. Brigham Young Univ Dept Stat Provo UT 84602 USA Harvard Univ Dept Stat Cambridge MA 02138 USA Harvard Univ Sch Publ Hlth Dept Biostat & Computat Biol Dana Farber Canc Inst Boston MA 02115 USA

Microarrays have been developed that the the entire nonrepetitive genomes of many different organisms, allowing for the unbiased mapping of active transcription regions or protein binding sites across the entire genome. These tiling array experiments produce massive correlated data sets that have many experimental artifacts, presenting many challenges to researchers that require innovative analysis methods and efficient computational algorithms. This paper presents a doubly stochastic latent variable analysis method for transcript discovery and protein binding region localization using tiling array data. This model is unique in that it considers actual genomic distance between probes. Additionally, the model is designed to be robust to cross-hybridized and nonresponsive probes, which can often lead to false-positive results in microarray experiments. We apply our model to a transcript finding data set to illustrate the consistency of our method. Additionally, we apply our method to a spike-in experiment that can be used as a benchmark data set for researchers interested in developing and comparing future tiling array methods. The results indicate that our method is very powerful, accurate and can be used on a single sample and without control experiments, thus defraying some of the overhead cost of conducting experiments on tiling arrays.

关键词： Tiling microarray continuous-space Markov chain Hidden Markov Model forward-backward algorithm Bayesian hierarchical model Expectation Conditional Maximization Markov chain Monte Carlo

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Estimating hidden semi-Markov chains from discrete sequences

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JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS 2003年第3期12卷 604-639页

作者： Guédon, Y Univ Montpellier 2 INRA CNRS CIRADUnite Mixte Rech F-34398 Montpellier 5 France

This article addresses the estimation of hidden semi-Markov chains from nonstationary discrete sequences. Hidden semi-Markov chains are particularly useful to model the succession of homogeneous zones or segments along sequences. A discrete hidden semi-Markov chain is composed of a nonobservable state process, which is a semi-Markov chain, and a discrete output process. Hidden semi-Markov chains generalize hidden Markov chains and enable the modeling of various durational structures. From an algorithmic point of view, a new forward-backward algorithm is proposed whose complexity is similar to that of the Viterbi algorithm in terms of sequence length (quadratic in the worst case in time and linear in space). This opens the way to the maximum likelihood estimation of hidden semi-Markov chains from long sequences. This statistical modeling approach is illustrated by the analysis of branching and flowering patterns in plants.

关键词： censoring EM algorithm forward-backward algorithm nonparametric maximum likelihood plant structure analysis smoothing algorithm Viterbi algorithm

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Exact filtering for partially observed continuous time models

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JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY 2004年第3期66卷 771-789页

作者： Fearnhead, P Meligkotsidou, L Univ Lancaster Dept Math & Stat Lancaster LA1 4YF England

The forward-backward algorithm is an exact filtering algorithm which can efficiently calculate likelihoods, and which can be used to simulate from posterior distributions. Using a simple result which relates gamma random variables with different rates, wig show how the forward-backward algorithm can be used to calculate the distribution of a sum of gamma random variables, and to simulate from their joint distribution given their sum. One application is to calculating the density of the time of a specific event in a Markov process, as this time is the sum of exponentially distributed interevent times. This enables us to apply the forward-backward algorithm to a range of new problems. We demonstrate our method on three problems: calculating likelihoods and simulating allele frequencies under a non-neutral population genetic model, analysing a stochastic epidemic model and simulating speciation times in phylogenetics.

关键词： Data augmentation EM algorithm Epidemics forward-backward algorithm Gibbssampling Markov chain Monte Carlo methods Phylogenetics Population genetics Susceptible-infected-removed epidemic Wright''s formula

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PCAdmix: Principal Components-Based Assignment of Ancestry along Each Chromosome in Individuals with Admixed Ancestry from Two or More Populations

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HUMAN BIOLOGY 2012年第4期84卷 343-364页

作者： Brisbin, Abra Bryc, Katarzyna Byrnes, Jake Zakharia, Fouad Omberg, Larsson Degenhardt, Jeremiah Reynolds, Andrew Ostrer, Harry Mezey, Jason G. Bustamante, Carlos D. Cornell Univ Dept Biostat & Computat Biol Ithaca NY USA Stanford Univ Dept Genet Stanford CA 94305 USA Albert Einstein Coll Med Dept Pathol & Genet Bronx NY 10467 USA Weill Cornell Med Coll Dept Genet Med New York NY USA

Identifying ancestry along each chromosome in admixed individuals provides a wealth of information for understanding the population genetic history of admixture events and is valuable for admixture mapping and identifying recent targets of selection. We present PCAdmix (available at https://***/site/pcadmix/home), a Principal Components-based algorithm for determining ancestry along each chromosome from a high-density, genome-wide set of phased single-nucleotide polymorphism (SNP) genotypes of admixed individuals. We compare our method to HAPMIX on simulated data from two ancestral populations, and we find high concordance between the methods. Our method also has better accuracy than LAMP when applied to three-population admixture, a situation as yet unaddressed by HAPMIX. Finally, we apply our method to a data set of four Latino populations with European, African, and Native American ancestry. We find evidence of assortative mating in each of the four populations, and we identify regions of shared ancestry that may be recent targets of selection and could serve as candidate regions for admixture-based association mapping.

关键词： ADMIXTURE PRINCIPAL COMPONENTS ANALYSIS (PCA) LOCAL ANCESTRY DECONVOLUTION HAPLOTYPE-BASED forward-backward algorithm

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Membrane profile-based probabilistic method for predicting transmembrane segments via multiple protein sequence alignment

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MOLECULAR BIOLOGY 2006年第3期40卷 481-485页

作者： Sutormin, R. A. Mironov, A. A. State Res Ctr GosNIIGenet Moscow 117545 Russia Russian Acad Sci Inst Informat Transmiss Problems Moscow 127994 Russia Moscow MV Lomonosov State Univ Dept Bioengn & Bioinformat Moscow 119992 Russia

Prediction of transmembrane (TM) segments of amino acid sequences of membrane proteins is a well-known and very important problem. The accuracy of its solution can be improved for approaches that do not use a homology search in an additional data bank. There is a lack of tested data in this area of research, because information on the structure of membrane proteins is scarce. In this work we created a test sample of structural alignments for membrane proteins. The TM segments of these proteins were mapped according to aligned 3D structures resolved for these proteins. A method for predicting TM segments in an alignment was developed on the basis of the forward-backward algorithm from the HMM theory. This method allows a user not only to predict TM segments, but also to create a probabilistic membrane profile, which can be employed in multiple alignment procedures taking the secondary structure of proteins into account. The method was implemented in a computer program available at http://***/fwdbck/. It provides better results than the MEMSAT method, which is nearly the only tool predicting TM segments in multiple alignments, without a homology search.

关键词： membrane protein secondary structure prediction hidden Markov models forward-backward algorithm probabilistic membrane profile test sample

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Comment on the CMS search for charge-asymmetric production of W′ boson in t(t)over-bar + jet events

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PHYSICS LETTERS B 2013年第3期718卷 1070-1072页

作者： Endo, Motoi Iwamoto, Sho Univ Tokyo Dept Phys Tokyo 1130033 Japan

A reanalysis is presented on the CMS result on a search for a W' boson that couples to the top and down quarks. The model is motivated by the Tevatron results on the forward-backward asymmetry of t (t) over bar pair production. In the evaluation of the theoretical cross section of pp -> t (t) over bar j, the interference effect between the SM and W' amplitudes is shown to be important, though it is ignored in the CMS analysis. The lower mass bound on the W' boson is relaxed from 840 GeV to 740 GeV at the 95% C.L. due to the interference effect at the leading order calculation of the cross section. The bound is also compared to the top forward-backward asymmetry. (C) 2012 Elsevier B.V. All rights reserved.

关键词： ASYMMETRY (Chemistry) BOSONS QUARKS forward-backward algorithm CROSS sections (Nuclear physics) COMPARATIVE studies

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Investigation of Drell-Yan processes in the CMS at the LHC

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PHYSICS OF ATOMIC NUCLEI 2015年第5期78卷 603-607页

作者： Gorbunov, I. N. Shmatov, S. V. Joint Inst Nucl Res Dubna 141980 Moscow Oblast Russia

The results obtained by studying dilepton production via gamma*/Z exchange in proton-proton collisions at the LHC are presented. Data from the CMS experiment on differential and double-differential cross sections for Drell-Yan processes (d sigma/dM and d sigma/dMdY), forward-backward asymmetry (Lambda(FB)), and weak mixing angle (sin(2) theta(W)) are given. Within the errors, the results agree with respective Standard Model predictions.

关键词： PROTON-proton interactions LARGE Hadron Collider (France & Switzerland) DIFFERENTIAL cross sections ASYMMETRY (Chemistry) STANDARD model (Nuclear physics) forward-backward algorithm

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An inertial forward-backward splitting method for solving inclusion problems in Hilbert spaces

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JOURNAL OF FIXED POINT THEORY AND APPLICATIONS 2018年第1期20卷 42-42页

作者： Cholamjiak, Watcharaporn Cholamjiak, Prasit Suantai, Suthep Univ Phayao Sch Sci Phayao 56000 Thailand Chiang Mai Univ Dept Math Fac Sci Ctr Excellence Math & Appl Math Chiang Mai 50200 Thailand

In this work, our interest is in investigating the monotone inclusion problems in the framework of real Hilbert spaces. For solving this problem, we propose an inertial forward-backward splitting algorithm involving an extrapolation factor. We then prove its strong convergence under some mild conditions. Finally, we provide some applications including the numerical experiments for supporting our main theorem.

关键词： Inertial method inclusion problem maximal monotone operator forward-backward algorithm Hilbert space

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LHC and Tevatron constraints on a W′ model interpretation of the top quark forward-backward asymmetry

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Physical Review D 2013年第11期88卷 114026-114026页

作者： Edmond L. Berger Zack Sullivan Hao Zhang High Energy Physics Division Argonne National Laboratory Argonne Illinois 60439 USA Department of Physics Illinois Institute of Technology Chicago Illinois 60616-3793 USA

Aspects of a flavor-changing W′ model with right-handed couplings are addressed in this paper in light of Tevatron and LHC data. Our fit to the Tevatron top-quark forward-backward asymmetry and the tt¯ inclusive cross section includes higher-order loop effects in the effective interaction. The higher-order corrections change the best-fit value of the W′ effective coupling strength as a function of the W′ mass. The consistency of the model is checked against the shape of the tt¯ invariant mass distribution. We use these updated W′ parameters to compute the expected contributions from W′t associated production and, for the first time, W′W′ pair production at the LHC. We do a full Monte Carlo simulation of the tt¯X final state, including interference between the tW′-induced tt¯j process and the standard model tt¯j process. Interference effects are shown to be quantitatively important, particularly when the W′ mass is large. The jet-multiplicity distribution in tt¯ jet production at 8 TeV constrains the W′ model severely.

关键词： LARGE Hadron Collider (France & Switzerland) TEVATRON QUARKS forward-backward algorithm SYMMETRY (Physics) NUCLEAR physics -- Mathematical models

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Measurement of the forward-backward asymmetry in Λb0 and Λ¯b0 baryon production in pp¯ collisions at s=1.96 TeV

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Physical Review D 2015年第7期91卷 072008-072008页

作者： V. M. Abazov B. Abbott B. S. Acharya M. Adams T. Adams J. P. Agnew G. D. Alexeev G. Alkhazov A. Alton A. Askew S. Atkins K. Augsten C. Avila F. Badaud L. Bagby B. Baldin D. V. Bandurin S. Banerjee E. Barberis P. Baringer J. F. Bartlett U. Bassler V. Bazterra A. Bean M. Begalli L. Bellantoni S. B. Beri G. Bernardi R. Bernhard I. Bertram M. Besançon R. Beuselinck P. C. Bhat S. Bhatia V. Bhatnagar G. Blazey S. Blessing K. Bloom A. Boehnlein D. Boline E. E. Boos G. Borissov M. Borysova A. Brandt O. Brandt R. Brock A. Bross D. Brown X. B. Bu M. Buehler V. Buescher V. Bunichev S. Burdin C. P. Buszello E. Camacho-Pérez B. C. K. Casey H. Castilla-Valdez S. Caughron S. Chakrabarti K. M. Chan A. Chandra E. Chapon G. Chen S. W. Cho S. Choi B. Choudhary S. Cihangir D. Claes J. Clutter M. Cooke W. E. Cooper M. Corcoran F. Couderc M.-C. Cousinou D. Cutts A. Das G. Davies S. J. de Jong E. De La Cruz-Burelo F. Déliot R. Demina D. Denisov S. P. Denisov S. Desai C. Deterre K. DeVaughan H. T. Diehl M. Diesburg P. F. Ding A. Dominguez A. Dubey L. V. Dudko A. Duperrin S. Dutt M. Eads D. Edmunds J. Ellison V. D. Elvira Y. Enari H. Evans A. Evdokimov V. N. Evdokimov A. Fauré L. Feng T. Ferbel F. Fiedler F. Filthaut W. Fisher H. E. Fisk M. Fortner H. Fox S. Fuess P. H. Garbincius A. Garcia-Bellido J. A. García-González V. Gavrilov W. Geng C. E. Gerber Y. Gershtein G. Ginther O. Gogota G. Golovanov P. D. Grannis S. Greder H. Greenlee G. Grenier Ph. Gris J.-F. Grivaz A. Grohsjean S. Grünendahl M. W. Grünewald T. Guillemin G. Gutierrez P. Gutierrez J. Haley L. Han K. Harder A. Harel J. M. Hauptman J. Hays T. Head T. Hebbeker D. Hedin H. Hegab A. P. Heinson U. Heintz C. Hensel I. Heredia-De La Cruz K. Herner G. Hesketh M. D. Hildreth R. Hirosky T. Hoang J. D. Hobbs B. Hoeneisen J. Hogan M. Hohlfeld J. L. Holzbauer I. Howley Z. Hubacek V. Hynek I. Iashvili Y. Ilchenko R. Illingworth A. S. Ito S. Jabeen M. Jaffré A. Jayasinghe M. S. Jeong R. Jesik P. Jiang K. Johns E. Johnson M. Johnson A. Jonckheere P. Jonsson J. Joshi A. W. Jung A. Juste E. Joint Institute for Nuclear Research Dubna Russia University of Oklahoma Norman Oklahoma 73019 USA Tata Institute of Fundamental Research Mumbai India University of Illinois at Chicago Chicago Illinois 60607 USA Florida State University Tallahassee Florida 32306 USA The University of Manchester Manchester M13 9PL United Kingdom Petersburg Nuclear Physics Institute St. Petersburg Russia University of Michigan Ann Arbor Michigan 48109 USA Louisiana Tech University Ruston Louisiana 71272 USA Czech Technical University in Prague Prague Czech Republic Universidad de los Andes Bogotá Colombia LPC Université Blaise Pascal CNRS/IN2P3 Clermont France Fermi National Accelerator Laboratory Batavia Illinois 60510 USA University of Virginia Charlottesville Virginia 22904 USA Northeastern University Boston Massachusetts 02115 USA University of Kansas Lawrence Kansas 66045 USA CEA Irfu SPP Saclay France Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Panjab University Chandigarh India LPNHE Universités Paris VI and VII CNRS/IN2P3 Paris France Physikalisches Institut Universität Freiburg Freiburg Germany Lancaster University Lancaster LA1 4YB United Kingdom Imperial College London London SW7 2AZ United Kingdom University of Mississippi University Mississippi 38677 USA Northern Illinois University DeKalb Illinois 60115 USA University of Nebraska Lincoln Nebraska 68588 USA State University of New York Stony Brook New York 11794 USA Moscow State University Moscow Russia Taras Shevchenko National University of Kyiv Kiev Ukraine University of Texas Arlington Texas 76019 USA II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Michigan State University East Lansing Michigan 48824 USA Institut für Physik Universität Mainz Mainz Germany Uppsala University Uppsala Sweden CINVESTAV Mexico City Mexico University of Notre Dame Notre Dame Indiana 46556 USA Rice University Houston Texas 77005 USA Korea

We measure the forward-backward asymmetry in the production of Λb0 and Λ¯b0 baryons as a function of rapidity in pp¯ collisions at s=1.96 TeV using 10.4 fb−1 of data collected with the D0 detector at the Fermilab Tevatron collider. The asymmetry is determined by the preference of Λb0 or Λ¯b0 particles to be produced in the direction of the beam protons or antiprotons, respectively. The measured asymmetry integrated over rapidity y in the range 0.1<|y|<2.0 is A=0.04±0.07(stat)±0.02(syst).

关键词： forward-backward algorithm BARYONS COLLISIONS (Nuclear physics) TEVATRON PROTON beams

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