Generalizations of Ripley's K-function with Application to Space Curves

The intensity function and Ripley's K-function have been used extensively in the literature to describe the first and second moment structure of spatial point sets. This has many applications including describing the statistical structure of synaptic vesicles. Some attempts have been made to extend Ripley's K-function to curve pieces. Such an extension can be used to describe the statistical structure of muscle fibers and brain fiber tracks. In this paper, we take a computational perspective and construct new and very general variants of Ripley's K-function for curves pieces, surface patches etc. We discuss the method from [Chiu, Stoyan, Kendall, & Mecke 2013] and compare it with our generalizations theoretically, and we give examples demonstrating the difference in their ability to separate sets of curve pieces.Comment: 9 pages & 8 figure

Likelihood informed dimension reduction for inverse problems in remote sensing of atmospheric constituent profiles

We use likelihood informed dimension reduction (LIS) (T. Cui et al. 2014) for inverting vertical profile information of atmospheric methane from ground based Fourier transform infrared (FTIR) measurements at Sodankyl\"a, Northern Finland. The measurements belong to the word wide TCCON network for greenhouse gas measurements and, in addition to providing accurate greenhouse gas measurements, they are important for validating satellite observations. LIS allows construction of an efficient Markov chain Monte Carlo sampling algorithm that explores only a reduced dimensional space but still produces a good approximation of the original full dimensional Bayesian posterior distribution. This in effect makes the statistical estimation problem independent of the discretization of the inverse problem. In addition, we compare LIS to a dimension reduction method based on prior covariance matrix truncation used earlier (S. Tukiainen et al. 2016)

The radiation of cynodonts and the ground plan of mammalian morphological diversity

Cynodont therapsids diversified extensively after the Permo-Triassic mass extinction event, and gave rise to mammals in the Jurassic. We use an enlarged and revised dataset of discrete skeletal characters to build a new phylogeny for all main cynodont clades from the Late Permian to the Early Jurassic, and we analyse models of morphological diversification in the group. Basal taxa and epicynodonts are paraphyletic relative to eucynodonts, and the latter are divided into cynognathians and probainognathians, with tritylodonts and mammals forming sister groups. Disparity analyses reveal a heterogeneous distribution of cynodonts in a morphospace derived from cladistic characters. Pairwise morphological distances are weakly correlated with phylogenetic distances. Comparisons of disparity by groups and through time are non-significant, especially after the data are rarefied. A disparity peak occurs in the Early/Middle Triassic, after which period the mean disparity fluctuates little. Cynognathians were characterized by high evolutionary rates and high diversity early in their history, whereas probainognathian rates were low. Community structure may have been instrumental in imposing different rates on the two clades

Bayesian astrostatistics: a backward look to the future

This perspective chapter briefly surveys: (1) past growth in the use of Bayesian methods in astrophysics; (2) current misconceptions about both frequentist and Bayesian statistical inference that hinder wider adoption of Bayesian methods by astronomers; and (3) multilevel (hierarchical) Bayesian modeling as a major future direction for research in Bayesian astrostatistics, exemplified in part by presentations at the first ISI invited session on astrostatistics, commemorated in this volume. It closes with an intentionally provocative recommendation for astronomical survey data reporting, motivated by the multilevel Bayesian perspective on modeling cosmic populations: that astronomers cease producing catalogs of estimated fluxes and other source properties from surveys. Instead, summaries of likelihood functions (or marginal likelihood functions) for source properties should be reported (not posterior probability density functions), including nontrivial summaries (not simply upper limits) for candidate objects that do not pass traditional detection thresholds.Comment: 27 pp, 4 figures. A lightly revised version of a chapter in "Astrostatistical Challenges for the New Astronomy" (Joseph M. Hilbe, ed., Springer, New York, forthcoming in 2012), the inaugural volume for the Springer Series in Astrostatistics. Version 2 has minor clarifications and an additional referenc

Mapping Dynamic Histone Acetylation Patterns to Gene Expression in Nanog-depleted Murine Embryonic Stem Cells

Embryonic stem cells (ESC) have the potential to self-renew indefinitely and to differentiate into any of the three germ layers. The molecular mechanisms for self-renewal, maintenance of pluripotency and lineage specification are poorly understood, but recent results point to a key role for epigenetic mechanisms. In this study, we focus on quantifying the impact of histone 3 acetylation (H3K9,14ac) on gene expression in murine embryonic stem cells. We analyze genome-wide histone acetylation patterns and gene expression profiles measured over the first five days of cell differentiation triggered by silencing Nanog, a key transcription factor in ESC regulation. We explore the temporal and spatial dynamics of histone acetylation data and its correlation with gene expression using supervised and unsupervised statistical models. On a genome-wide scale, changes in acetylation are significantly correlated to changes in mRNA expression and, surprisingly, this coherence increases over time. We quantify the predictive power of histone acetylation for gene expression changes in a balanced cross-validation procedure. In an in-depth study we focus on genes central to the regulatory network of Mouse ESC, including those identified in a recent genome-wide RNAi screen and in the PluriNet, a computationally derived stem cell signature. We find that compared to the rest of the genome, ESC-specific genes show significantly more acetylation signal and a much stronger decrease in acetylation over time, which is often not reflected in an concordant expression change. These results shed light on the complexity of the relationship between histone acetylation and gene expression and are a step forward to dissect the multilayer regulatory mechanisms that determine stem cell fate.Comment: accepted at PLoS Computational Biolog

Estimating Dengue Transmission Intensity from Case-Notification Data from Multiple Countries

Despite being the most widely distributed mosquito-borne viral infection, estimates of dengue transmission intensity and associated burden remain ambiguous. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing the burden of disease and the likely impact of interventions.We estimated the force of infection (λ) and corresponding basic reproduction numbers (R0) by fitting catalytic models to age-stratified incidence data identified from the literature. We compared estimates derived from incidence and seroprevalence data and assessed the level of under-reporting of dengue disease. In addition, we estimated the relative contribution of primary to quaternary infections to the observed burden of dengue disease incidence. The majority of R0 estimates ranged from one to five and the force of infection estimates from incidence data were consistent with those previously estimated from seroprevalence data. The baseline reporting rate (or the probability of detecting a secondary infection) was generally low (<25%) and varied within and between countries.As expected, estimates varied widely across and within countries, highlighting the spatio-temporally heterogeneous nature of dengue transmission. Although seroprevalence data provide the maximum information, the incidence models presented in this paper provide a method for estimating dengue transmission intensity from age-stratified incidence data, which will be an important consideration in areas where seroprevalence data are not available

Too close for comfort: spatial patterns in acorn barnacle populations

Spatial patterns in aggregations form as a result of the interplay between costs and benefits experienced by individuals. Such self-organisation of aggregations can be explained using a zonal model in which a short-range zone of repulsion and longer-range zone of attraction surrounding individuals leads to emergent pattern properties. The signal of these processes can be detected using spatial pattern analyses. Furthermore, in sessile organisms, post-settlement mortality reveals the relative costs and benefits of positions within the aggregation. Acorn barnacles are known to require contact with conspecifics for reproduction and are therefore believed to aggregate for this purpose; isolated individuals may also be more susceptible to abiotic stress and predation. At short distances, however, competition for space and resources is likely to occur. In this study spatial patterns of barnacles (Semibalanus balanoides L.) were analysed using pair-correlation functions. Individuals were dispersed at distances below 0.30 cm, but peak relative density occurred at a distance of 0.36 cm from conspecifics. This is much closer than required for reproductive access, implying a strong aggregative drive, up to the point of physical contact with neighbours. Nevertheless, analysis of dead barnacles illustrated that such proximity carries a cost as barnacles with many neighbours were more likely to have died. The inferences obtained from these patterns are that barnacles aggregate as closely as they can, and that local neighbourhood competition is a powerful determinant of mortality. These processes give rise to the observed pattern properties

Are all ‘research fields’ equal? Rethinking practice for the use of data from crowd-sourcing market places

New technologies like large-scale social media sides (e.g., Facebook and Twitter) and crowdsourcing services (e.g., Amazon Mechanical Turk, Crowdflower, Clickworker) impact social science research and provide many new and interesting avenues for research. The use of these new technologies for research has not been without challenges and a recently published psychological study on Facebook led to a widespread discussion on the ethics of conducting large-scale experiments online. Surprisingly little has been said about the ethics of conducting research using commercial crowdsourcing market places. In this paper, I want to focus on the question of which ethical questions are raised by data collection with crowdsourcing tools. I briefly draw on implications of internet research more generally and then focus on the specific challenges that research with crowdsourcing tools faces. I identify fair-pay and related issues of respect for autonomy as well as problems with power dynamics between researcher and participant, which has implications for ‘withdrawal-withoutprejudice’, as the major ethical challenges with crowdsourced data. Further, I will to draw attention on how we can develop a ‘best practice’ for researchers using crowdsourcing tools

Examination of the Effects of Heterogeneous Organization of RyR Clusters, Myofibrils and Mitochondria on Ca2+ Release Patterns in Cardiomyocytes

Spatio-temporal dynamics of intracellular calcium, [Ca2+]i, regulate the contractile function of cardiac muscle cells. Measuring [Ca2+]i flux is central to the study of mechanisms that underlie both normal cardiac function and calcium-dependent etiologies in heart disease. However, current imaging techniques are limited in the spatial resolution to which changes in [Ca2+]i can be detected. Using spatial point process statistics techniques we developed a novel method to simulate the spatial distribution of RyR clusters, which act as the major mediators of contractile Ca2+ release, upon a physiologically-realistic cellular landscape composed of tightly-packed mitochondria and myofibrils.We applied this method to computationally combine confocal-scale (~ 200 nm) data of RyR clusters with 3D electron microscopy data (~ 30 nm) of myofibrils and mitochondria, both collected from adult rat left ventricular myocytes. Using this hybrid-scale spatial model, we simulated reaction-diffusion of [Ca2+]i during the rising phase of the transient (first 30 ms after initiation). At 30 ms, the average peak of the simulated [Ca2+]i transient and of the simulated fluorescence intensity signal, F/F0, reached values similar to that found in the literature ([Ca2+]i 1 μM; F/F0 5.5). However, our model predicted the variation in [Ca2+]i to be between 0.3 and 12.7 μM (~3 to 100 fold from resting value of 0.1 μM) and the corresponding F/F0 signal ranging from 3 to 9.5. We demonstrate in this study that: (i) heterogeneities in the [Ca2+]i transient are due not only to heterogeneous distribution and clustering of mitochondria; (ii) but also to heterogeneous local densities of RyR clusters. Further, we show that: (iii) these structureinduced heterogeneities in [Ca2+]i can appear in line scan data. Finally, using our unique method for generating RyR cluster distributions, we demonstrate the robustness in the [Ca2+]i transient to differences in RyR cluster distributions measured between rat and human cardiomyocytes

Overrepresentation of South Asian ethnic groups among cases of influenza A(H1N1)pdm09 during the first phase of the 2009 pandemic in England

Background During the first wave of the influenza A(H1N1)pdm09 pandemic in England in 2009, morbidity and mortality were higher in patients of South Asian (Indian, Pakistani or Bangladeshi) ethnic minority groups. Objectives This study aims to provide insights in the representation of this group among reported cases, indicating susceptibility and exposure. Methods All laboratory‐confirmed cases including basic demographic and limited clinical information that were reported to the FluZone surveillance system between April and October 2009 were retrieved. Missing ethnicity data were imputed using the previously developed and validated South Asian Names and Group Recognition Algorithm (SANGRA). Differences between ethnic groups were calculated using chi‐square, log‐rank and t tests and rate ratios. Geographic clustering was compared using Ripley's K functions. Results SANGRA identified 2447 (28%) of the total of 8748 reported cases as South Asian. South Asian cases were younger (P < .001), more often male (P = .002) and more often from deprived areas (P < .001) than cases of other ethnic groups. Time between onset of symptoms and laboratory sampling was longer in this group (P < .001), and they were less often advised antiviral treatment (P < .001), however, declined treatment less. The highest cumulative incidence was seen in the West Midlands region (32.7/10 000), London (7.0/10 000) and East of England region (5.7/10 000). Conclusions People of South Asian ethnic groups were disproportionally affected by the first wave of the influenza pandemic in England in 2009. The findings presented contribute to further understanding of demographic, socioeconomic and ethnic factors of the outbreak and inform future influenza preparedness to ensure appropriate prevention and care