Research papers

Gold Nanoparticles for Biology and Medicine

David A. Giljohann, Dwight S. Seferos, Weston L. Daniel, Matthew D. Massich, Pinal C. Patel, Chad A. Mirkin

Gold colloids have fascinated scientists for over a century and are now heavily utilized in chemistry, biology, engineering, and medicine. Today these materials can be synthesized reproducibly, modified with seemingly limitless chemical functional groups, and, in certain cases, characterized with atomic-level precision. This Review highlights recent advances in the synthesis, bioconjugation, and cellular uses of gold nanoconjugates. There are now many examples of highly sensitive and selective assays based upon gold nanoconjugates. In recent years, focus has turned to therapeutic possibilities for such materials. Structures which behave as gene-regulating agents, drug carriers, imaging agents, and photoresponsive therapeutics have been developed and studied in the context of cells and many debilitating diseases. These structures are not simply chosen as alternatives to molecule-based systems, but rather for their new physical and chemical properties, which confer substantive advantages in cellular and medical applications.

QIIME allows analysis of high-throughput community sequencing data

J. Gregory Caporaso, Justin Kuczynski, Jesse Stombaugh, Kyle Bittinger, Frederic D. Bushman, Elizabeth K. Costello, Noah Fie…

A basic introduction to fixed-effect and random-effects models for meta-analysis

Michael Borenstein, Larry V. Hedges, Julian P. T. Higgins, Hannah R. Rothstein

There are two popular statistical models for meta-analysis, the fixed-effect model and the random-effects model. The fact that these two models employ similar sets of formulas to compute statistics, and sometimes yield similar estimates for the various parameters, may lead people to believe that the models are interchangeable. In fact, though, the models represent fundamentally different assumptions about the data. The selection of the appropriate model is important to ensure that the various statistics are estimated correctly. Additionally, and more fundamentally, the model serves to place the analysis in context. It provides a framework for the goals of the analysis as well as for the interpretation of the statistics. In this paper we explain the key assumptions of each model, and then outline the differences between the models. We conclude with a discussion of factors to consider when choosing between the two models. Copyright © 2010 John Wiley & Sons, Ltd.

Features and development of Coot

Paul Emsley, Bernhard Lohkamp, W. G. Scott, Kevin Cowtan

Coot is a molecular-graphics application for model building and validation of biological macromolecules. The program displays electron-density maps and atomic models and allows model manipulations such as idealization, real-space refinement, manual rotation/translation, rigid-body fitting, ligand search, solvation, mutations, rotamers and Ramachandran idealization. Furthermore, tools are provided for model validation as well as interfaces to external programs for refinement, validation and graphics. The software is designed to be easy to learn for novice users, which is achieved by ensuring that tools for common tasks are 'discoverable' through familiar user-interface elements (menus and toolbars) or by intuitive behaviour (mouse controls). Recent developments have focused on providing tools for expert users, with customisable key bindings, extensions and an extensive scripting interface. The software is under rapid development, but has already achieved very widespread use within the crystallographic community. The current state of the software is presented, with a description of the facilities available and of some of the underlying methods employed.

Connecting high school physics experiences, outcome expectations, physics identity, and physics career choice: A gender study

Zahra Hazari, Gerhard Sonnert, Philip M. Sadler, Marie‐Claire Shanahan

Abstract This study explores how students' physics identities are shaped by their experiences in high school physics classes and by their career outcome expectations. The theoretical framework focuses on physics identity and includes the dimensions of student performance, competence, recognition by others, and interest. Drawing data from the Persistence Research in Science and Engineering (PRiSE) project, which surveyed college English students nationally about their backgrounds, high school science experiences, and science attitudes, the study uses multiple regression to examine the responses of 3,829 students from 34 randomly selected US colleges/universities. Confirming the salience of the identity dimension for young persons' occupational plans, the measure for students' physics identity used in this study was found to strongly predict their intended choice of a physics career. Physics identity, in turn, was found to correlate positively with a desire for an intrinsically fulfilling career and negatively with a desire for personal/family time and opportunities to work with others. Physics identity was also positively predicted by several high school physics characteristics/experiences such as a focus on conceptual understanding, real‐world/contextual connections, students answering questions or making comments, students teaching classmates, and having an encouraging teacher. Even though equally beneficial for both genders, females reported experiencing a conceptual focus and real‐world/contextual connections less frequently. The explicit discussion of under‐representation of women in science was positively related to physics identity for female students but had no impact for male students. Surprisingly, several experiences that were hypothesized to be important for females' physics identity were found to be non‐significant including having female scientist guest speakers, discussion of women scientists' work, and the frequency of group work. This study exemplifies a useful theoretical framework based on identity, which can be employed to further examine persistence in science, and illustrates possible avenues for change in high school physics teaching. © 2010 Wiley Periodicals, Inc. J Res Sci Teach 47: 978–1003, 2010

BEDTools: a flexible suite of utilities for comparing genomic features

Aaron R. Quinlan, Ira M. Hall

MOTIVATION: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. RESULTS: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. AVAILABILITY AND IMPLEMENTATION: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools CONTACT: aaronquinlan@gmail.com; imh4y@virginia.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Statsmodels: Econometric and Statistical Modeling with Python

Skipper Seabold, Josef Perktold

Statsmodels is a library for statistical and econometric analysis in Python. This paper discusses the current relationship between statistics and Python and open source more generally, outlining how the statsmodels package fills a gap in this relationship. An overview of statsmodels is provided, including a discussion of the overarching design and philosophy, what can be found in the package, and some usage examples. The paper concludes with a look at what the future holds.

Regularization Paths for Generalized Linear Models via Coordinate Descent.

Jerome H. Friedman, Trevor Hastie, Rob Tibshirani

We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multinomial regression problems while the penalties include ℓ(1) (the lasso), ℓ(2) (ridge regression) and mixtures of the two (the elastic net). The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In comparative timings we find that the new algorithms are considerably faster than competing methods.

Factors influencing knowledge about childhood autism among final year undergraduate Medical, Nursing and Psychology students of University of Nigeria, Enugu State, Nigeria

Monday N. Igwe, Muideen O. Bakare, Ahamefule O Agomoh, Gabriel M Onyeama, Kevin O Okonkwo

BACKGROUND: Knowledge and awareness about childhood autism is low among health care workers and the general populace in Nigeria. Poor knowledge about childhood autism among final year medical, nursing and psychology students who would form tomorrow's child health care professionals can compromise early recognition and interventions that are known to improve prognosis in childhood autism. Educational factors that could be influencing knowledge about childhood autism among these future health care professionals are unknown. This study assessed knowledge about childhood autism among final year undergraduate medical, nursing and psychology students in south-eastern Nigeria and determined the factors that could be influencing such knowledge. METHODS: One hundred final year undergraduate students were randomly selected from each of the Departments of Medicine, Nursing Science and Psychology respectively of University of Nigeria, Enugu State, Nigeria making a sample size of three hundred. A socio-demographic questionnaire and knowledge about childhood autism among health workers (KCAHW) questionnaire were administered to the students. RESULTS: The total mean score for the three groups of students on the KCAHW questionnaire was 10.67+/-3.73 out of a possible total score of 19, with medical, nursing and psychology students having total mean scores of 12.24+/-3.24, 10.76+/-3.50 and 9.01+/-3.76 respectively. The mean scores for the three groups showed statistically significant difference for domain 1 (p=0.000), domain 3 (p=0.029), domain 4 (p=0.000) and total score (p=0.000), with medical students more likely to recognise symptoms and signs of autism compared to nursing and psychology students. The mean score in domain 2 did not show statistically significant difference among the three groups (p=0.769). The total score on the KCAHW questionnaire is positively correlated with the number of weeks of posting in psychiatry (r=0.319, p=0.000) and the number of weeks of posting in paediatrics (r=0.372, p=0.000). The total score is also positively correlated with the number of credit hours of lectures in psychiatry/abnormal psychology (r=0.324, p=0.000) and the number of credit hours of lectures in paediatrics (r=0.372, p=0.000). The field of study also influenced knowledge about childhood autism (p=0.000). CONCLUSION: Peculiar situation in this environment as signified by inadequate human resources needed in the area of clinical psychology training often times necessitates employing first degree graduates in psychology into clinical positions. This calls for additional exposure of the undergraduate psychology students to training curriculum aimed at improving their early recognition of symptoms of autism spectrum disorders in this environment.

Assessing the Performance of Prediction Models

Ewout W. Steyerberg, Andrew J. Vickers, Nancy R. Cook, Thomas Alexander Gerds, Mithat Gönen, Nancy A. Obuchowski, Michael Pe…

The performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the receiver operating characteristic [ROC] curve), and goodness-of-fit statistics for calibration.Several new measures have recently been proposed that can be seen as refinements of discrimination measures, including variants of the c statistic for survival, reclassification tables, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Moreover, decision-analytic measures have been proposed, including decision curves to plot the net benefit achieved by making decisions based on model predictions.We aimed to define the role of these relatively novel approaches in the evaluation of the performance of prediction models. For illustration, we present a case study of predicting the presence of residual tumor versus benign tissue in patients with testicular cancer (n = 544 for model development, n = 273 for external validation).We suggest that reporting discrimination and calibration will always be important for a prediction model. Decision-analytic measures should be reported if the predictive model is to be used for clinical decisions. Other measures of performance may be warranted in specific applications, such as reclassification metrics to gain insight into the value of adding a novel predictor to an established model.

Astrocytes: biology and pathology

Michael V. Sofroniew, Harry V. Vinters

Astrocytes are specialized glial cells that outnumber neurons by over fivefold. They contiguously tile the entire central nervous system (CNS) and exert many essential complex functions in the healthy CNS. Astrocytes respond to all forms of CNS insults through a process referred to as reactive astrogliosis, which has become a pathological hallmark of CNS structural lesions. Substantial progress has been made recently in determining functions and mechanisms of reactive astrogliosis and in identifying roles of astrocytes in CNS disorders and pathologies. A vast molecular arsenal at the disposal of reactive astrocytes is being defined. Transgenic mouse models are dissecting specific aspects of reactive astrocytosis and glial scar formation in vivo. Astrocyte involvement in specific clinicopathological entities is being defined. It is now clear that reactive astrogliosis is not a simple all-or-none phenomenon but is a finely gradated continuum of changes that occur in context-dependent manners regulated by specific signaling events. These changes range from reversible alterations in gene expression and cell hypertrophy with preservation of cellular domains and tissue structure, to long-lasting scar formation with rearrangement of tissue structure. Increasing evidence points towards the potential of reactive astrogliosis to play either primary or contributing roles in CNS disorders via loss of normal astrocyte functions or gain of abnormal effects. This article reviews (1) astrocyte functions in healthy CNS, (2) mechanisms and functions of reactive astrogliosis and glial scar formation, and (3) ways in which reactive astrocytes may cause or contribute to specific CNS disorders and lesions.

DETERMINISTIC SEISMIC GROUND MOTION MODELLING OF THE GREATER ACCRA METROPOLITAN AREA, SOUTHEASTERN GHANA

Paulina Amponsah, Bruce Banoeng‐Yakubo, G. F. Panza, Franco Vaccari

Research Article| December 01, 2009 DETERMINISTIC SEISMIC GROUND MOTION MODELLING OF THE GREATER ACCRA METROPOLITAN AREA, SOUTHEASTERN GHANA P.E. AMPONSAH; P.E. AMPONSAH Geological Survey Department, Accra, Ghana, e-mail: pekua2@yahoo.com Search for other works by this author on: GSW Google Scholar B.K. BANOENG-YAKUBO; B.K. BANOENG-YAKUBO Geology Department, University of Ghana, Legon, Ghana, e-mail: bbruce@ug.edu.gh Search for other works by this author on: GSW Google Scholar G.F. PANZA; G.F. PANZA Department of Earth Sciences, University of Trieste, Italy, The Abdus Salam International Centre for Theoretical Physics- ESP SAND group, Trieste, Italy, e-mail: panza@dst.units.it Search for other works by this author on: GSW Google Scholar F. VACCARI F. VACCARI Department of Earth Sciences, University of Trieste, Italy, e-mail: vaccari@dst.units.it Search for other works by this author on: GSW Google Scholar Author and Article Information P.E. AMPONSAH Geological Survey Department, Accra, Ghana, e-mail: pekua2@yahoo.com B.K. BANOENG-YAKUBO Geology Department, University of Ghana, Legon, Ghana, e-mail: bbruce@ug.edu.gh G.F. PANZA Department of Earth Sciences, University of Trieste, Italy, The Abdus Salam International Centre for Theoretical Physics- ESP SAND group, Trieste, Italy, e-mail: panza@dst.units.it F. VACCARI Department of Earth Sciences, University of Trieste, Italy, e-mail: vaccari@dst.units.it Publisher: Geological Society of South Africa First Online: 09 Mar 2017 Online ISSN: 1996-8590 Print ISSN: 1012-0750 © 2009 Geological Society of South Africa South African Journal of Geology (2009) 112 (3-4): 317–328. https://doi.org/10.2113/gssajg.112.3-4.317 Article history First Online: 09 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation P.E. AMPONSAH, B.K. BANOENG-YAKUBO, G.F. PANZA, F. VACCARI; DETERMINISTIC SEISMIC GROUND MOTION MODELLING OF THE GREATER ACCRA METROPOLITAN AREA, SOUTHEASTERN GHANA. South African Journal of Geology 2009;; 112 (3-4): 317–328. doi: https://doi.org/10.2113/gssajg.112.3-4.317 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySouth African Journal of Geology Search Advanced Search Abstract The seismic ground motion of the greater Accra Metropolitan Area has been modelled for land use planning and disaster mitigation. The deterministic computation, a hybrid method based on the modal summation and finite difference method was used. Using these techniques, the seismic ground motion along four profiles located in the metropolis has been computed. The 1939 earthquake of magnitude 6.5 (ML ) was used as the scenario earthquake. Synthetic seismic waveforms from which parameters for engineering design such as peak ground acceleration, velocity and spectral amplifications have been produced along the geological cross sections. The peak ground acceleration and velocity computed for the metropolis ranges from 0.14 g to 0.57 g and 9.2 cms−1 to 37.1 cms−1, respectively. These correspond to intensity ranging from VII to IX on the Modified Mercalli Intensity scale. Areas in the metropolis underlain by unconsolidated sediments experience the largest shakings. The results illustrated represent a useful guide for civil engineers in the design of buildings in the metropolis for safe and sustainable development. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

The chemistry of graphene oxide

Daniel R. Dreyer, Sungjin Park, Christopher W. Bielawski, Rodney S. Ruoff

The chemistry of graphene oxide is discussed in this critical review. Particular emphasis is directed toward the synthesis of graphene oxide, as well as its structure. Graphene oxide as a substrate for a variety of chemical transformations, including its reduction to graphene-like materials, is also discussed. This review will be of value to synthetic chemists interested in this emerging field of materials science, as well as those investigating applications of graphene who would find a more thorough treatment of the chemistry of graphene oxide useful in understanding the scope and limitations of current approaches which utilize this material (91 references).

The spectrum of latent tuberculosis: rethinking the biology and intervention strategies

Clifton E. Barry, Helena I. Boshoff, Véronique Dartois, Thomas Dick, Sabine Ehrt, JoAnne L. Flynn, Dirk Schnappinger, Robert…

Lectures on holographic methods for condensed matter physics

Sean A. Hartnoll

These notes are loosely based on lectures given at the CERN Winter School on Supergravity, Strings and Gauge theories, February 2009, and at the IPM String School in Tehran, April 2009. I have focused on a few concrete topics and also on addressing questions that have arisen repeatedly. Background condensed matter physics material is included as motivation and easy reference for the high energy physics community. The discussion of holographic techniques progresses from equilibrium, to transport and to superconductivity.

Object Detection with Discriminatively Trained Part-Based Models

Pedro F. Felzenszwalb, Ross Girshick, David McAllester, Deva Ramanan

We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object detection challenges. While deformable part models have become quite popular, their value had not been demonstrated on difficult benchmarks such as the PASCAL data sets. Our system relies on new methods for discriminative training with partially labeled data. We combine a margin-sensitive approach for data-mining hard negative examples with a formalism we call latent SVM. A latent SVM is a reformulation of MI--SVM in terms of latent variables. A latent SVM is semiconvex, and the training problem becomes convex once latent information is specified for the positive examples. This leads to an iterative training algorithm that alternates between fixing latent values for positive examples and optimizing the latent SVM objective function.

QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials

Paolo Giannozzi, Stefano Baroni, Nicola Bonini, Matteo Calandra, Roberto Car, Carlo Cavazzoni, Davide Ceresoli, G. Chiarotti…

QUANTUM ESPRESSO is an integrated suite of computer codes for electronic-structure calculations and materials modeling, based on density-functional theory, plane waves, and pseudopotentials (norm-conserving, ultrasoft, and projector-augmented wave). The acronym ESPRESSO stands for opEn Source Package for Research in Electronic Structure, Simulation, and Optimization. It is freely available to researchers around the world under the terms of the GNU General Public License. QUANTUM ESPRESSO builds upon newly-restructured electronic-structure codes that have been developed and tested by some of the original authors of novel electronic-structure algorithms and applied in the last twenty years by some of the leading materials modeling groups worldwide. Innovation and efficiency are still its main focus, with special attention paid to massively parallel architectures, and a great effort being devoted to user friendliness. QUANTUM ESPRESSO is evolving towards a distribution of independent and interoperable codes in the spirit of an open-source project, where researchers active in the field of electronic-structure calculations are encouraged to participate in the project by contributing their own codes or by implementing their own ideas into existing codes.

Physics of laser-driven plasma-based electron accelerators

E. Esarey, C. B. Schroeder, Wim Leemans

Laser-driven plasma-based accelerators, which are capable of supporting fields in excess of $100\phantom{\rule{0.3em}{0ex}}\mathrm{GV}∕\mathrm{m}$, are reviewed. This includes the laser wakefield accelerator, the plasma beat wave accelerator, the self-modulated laser wakefield accelerator, plasma waves driven by multiple laser pulses, and highly nonlinear regimes. The properties of linear and nonlinear plasma waves are discussed, as well as electron acceleration in plasma waves. Methods for injecting and trapping plasma electrons in plasma waves are also discussed. Limits to the electron energy gain are summarized, including laser pulse diffraction, electron dephasing, laser pulse energy depletion, and beam loading limitations. The basic physics of laser pulse evolution in underdense plasmas is also reviewed. This includes the propagation, self-focusing, and guiding of laser pulses in uniform plasmas and with preformed density channels. Instabilities relevant to intense short-pulse laser-plasma interactions, such as Raman, self-modulation, and hose instabilities, are discussed. Experiments demonstrating key physics, such as the production of high-quality electron bunches at energies of $0.1--1\phantom{\rule{0.3em}{0ex}}\mathrm{GeV}$, are summarized.

Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling

Hoshin V. Gupta, Harald Kling, Koray K. Yılmaz, Guillermo F. Martinez

Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science

Laura J. Damschroder, David C. Aron, Rosalind E. Keith, Susan Kirsh, J Alexander, Julie C. Lowery

BACKGROUND: Many interventions found to be effective in health services research studies fail to translate into meaningful patient care outcomes across multiple contexts. Health services researchers recognize the need to evaluate not only summative outcomes but also formative outcomes to assess the extent to which implementation is effective in a specific setting, prolongs sustainability, and promotes dissemination into other settings. Many implementation theories have been published to help promote effective implementation. However, they overlap considerably in the constructs included in individual theories, and a comparison of theories reveals that each is missing important constructs included in other theories. In addition, terminology and definitions are not consistent across theories. We describe the Consolidated Framework For Implementation Research (CFIR) that offers an overarching typology to promote implementation theory development and verification about what works where and why across multiple contexts. METHODS: We used a snowball sampling approach to identify published theories that were evaluated to identify constructs based on strength of conceptual or empirical support for influence on implementation, consistency in definitions, alignment with our own findings, and potential for measurement. We combined constructs across published theories that had different labels but were redundant or overlapping in definition, and we parsed apart constructs that conflated underlying concepts. RESULTS: The CFIR is composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Eight constructs were identified related to the intervention (e.g., evidence strength and quality), four constructs were identified related to outer setting (e.g., patient needs and resources), 12 constructs were identified related to inner setting (e.g., culture, leadership engagement), five constructs were identified related to individual characteristics, and eight constructs were identified related to process (e.g., plan, evaluate, and reflect). We present explicit definitions for each construct. CONCLUSION: The CFIR provides a pragmatic structure for approaching complex, interacting, multi-level, and transient states of constructs in the real world by embracing, consolidating, and unifying key constructs from published implementation theories. It can be used to guide formative evaluations and build the implementation knowledge base across multiple studies and settings.

The Systems Biology Graphical Notation

Nicolas Le Novère, Michael Hucka, Huaiyu Mi, Stuart Moodie, Falk Schreiber, Anatoly Sorokin, Emek Demir, Katja Wegner, Mirit…

Probabilistic graphical models : principles and techniques

Daniel L. Koller, Nir Friedman

Most tasks require a person or an automated system to reason -- to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality. Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

Fast model-based estimation of ancestry in unrelated individuals

David H. Alexander, John Novembre, Kenneth Lange

Population stratification has long been recognized as a confounding factor in genetic association studies. Estimated ancestries, derived from multi-locus genotype data, can be used to perform a statistical correction for population stratification. One popular technique for estimation of ancestry is the model-based approach embodied by the widely applied program structure. Another approach, implemented in the program EIGENSTRAT, relies on Principal Component Analysis rather than model-based estimation and does not directly deliver admixture fractions. EIGENSTRAT has gained in popularity in part owing to its remarkable speed in comparison to structure. We present a new algorithm and a program, ADMIXTURE, for model-based estimation of ancestry in unrelated individuals. ADMIXTURE adopts the likelihood model embedded in structure. However, ADMIXTURE runs considerably faster, solving problems in minutes that take structure hours. In many of our experiments, we have found that ADMIXTURE is almost as fast as EIGENSTRAT. The runtime improvements of ADMIXTURE rely on a fast block relaxation scheme using sequential quadratic programming for block updates, coupled with a novel quasi-Newton acceleration of convergence. Our algorithm also runs faster and with greater accuracy than the implementation of an Expectation-Maximization (EM) algorithm incorporated in the program FRAPPE. Our simulations show that ADMIXTURE's maximum likelihood estimates of the underlying admixture coefficients and ancestral allele frequencies are as accurate as structure's Bayesian estimates. On real-world data sets, ADMIXTURE's estimates are directly comparable to those from structure and EIGENSTRAT. Taken together, our results show that ADMIXTURE's computational speed opens up the possibility of using a much larger set of markers in model-based ancestry estimation and that its estimates are suitable for use in correcting for population stratification in association studies.

Freezing light with cold atoms

M. D. Havey

The impact of disorder and localisation in electronic conduction was introduced more than half a century ago by Philip Anderson. In a much broader context of disorder-mediated wave dynamics it remains an important research area, and surprises abound. Meanwhile, research in ultracold atomic physics has led to phenomenally detailed elucidation of properties, including changes in phase, of quantum degenerate Bosonic and Fermionic gases. For example, beautiful experiments have recently demonstrated, in quasi one-dimensional systems, Anderson localisation of matter waves. In this brief essay, we describe and discuss research on wave localisation in the context of ultracold atomic physics, with a particular emphasis on light localisation in ultracold and high-density atomic gases. Essential ideas are reviewed, along with the current experimental status of the field, and promising avenues for future research are discussed.