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E-Canada and the Emerging Cyber Attack Exigency
Craig MacEachern
Dalhousie Journal of Interdisciplinary Management , 2011, DOI: 10.5931/djim.v7i2.65
Abstract: This paper examines the growing concern surrounding cyber-attacks, and warns about the possible impacts of a cyber-attack upon Canadian e-government, economy, and infrastructure. This paper covers historical examples of cyber-attacks on a global scale, then focuses on Canadian e-government vulnerabilities, and suggests some ways in which Canadian government must adapt its domestic security and internet policies to confront the future inevitability of cyber-attacks.
Genome-Wide Identification and Quantification of cis- and trans-Regulated Genes Responding to Marek’s Disease Virus Infection via Analysis of Allele-Specific Expression
Sean MacEachern,Seth D. Crosby
Frontiers in Genetics , 2012, DOI: 10.3389/fgene.2011.00113
Abstract: Marek’s disease (MD) is a commercially important neoplastic disease of chickens caused by Marek’s disease virus (MDV), a naturally occurring oncogenic alphaherpesvirus. Selecting for increased genetic resistance to MD is a control strategy that can augment vaccinal control measures. To identify high-confidence candidate MD resistance genes, we conducted a genome-wide screen for allele-specific expression (ASE) amongst F1 progeny of two inbred chicken lines that differ substantially in MD resistance. High throughput sequencing was initially used to profile transcriptomes from pools of uninfected and infected individuals at 4 days post-infection to identify any genes showing ASE in response to MDV infection. RNA sequencing identified 22,655 single nucleotide polymorphisms (SNPs) of which 5,360 in 3,773 genes exhibited significant allelic imbalance. Illumina GoldenGate assays were subsequently used to quantify regulatory variation controlled at the gene (cis) and elsewhere in the genome (trans) by examining differences in expression between F1 individuals and artificial F1 RNA pools over six time periods in 1,536 of the most significant SNPs identified by RNA sequencing. Allelic imbalance as a result of cis-regulatory changes was confirmed in 861 of the 1,233 GoldenGate assays successfully examined. Furthermore we have identified seven genes that display trans-regulation only in infected animals and ～500 SNP that show a complex interaction between cis- and trans-regulatory changes. Our results indicate ASE analyses are a powerful approach to identify regulatory variation responsible for differences in transcript abundance in genes underlying complex traits. And the genes with SNPs exhibiting ASE provide a strong foundation to further investigate the causative polymorphisms and genetic mechanisms for MD resistance. Finally, the methods used here for identifying specific genes and SNPs have practical implications for applying marker-assisted selection to complex traits that are difficult to measure in agricultural species, when expression differences are expected to control a portion of the phenotypic variance.
Phylogenetic reconstruction and the identification of ancient polymorphism in the Bovini tribe (Bovidae, Bovinae)
Sean MacEachern, John McEwan, Mike Goddard
BMC Genomics , 2009, DOI: 10.1186/1471-2164-10-177
Abstract: We identified 3 distinct lineages after the Bovini split from the Boselaphini and Tragelaphini tribes, which has lead to the (1) Buffalo clade (Bubalus and Syncerus species) and a more recent divergence leading to the (2) Banteng, Gaur and Mithan and (3) Domestic cattle clades. A fourth lineage may also exist that leads to Bison and Yak. However, there was some ambiguity as to whether this was a divergence from the Banteng/Gaur/Mithan or the Domestic cattle clade. From an analysis of approximately 30,000 sites that were amplified in all species 133 sites were identified with ambiguous inheritance, in that all trees implied more than one mutation at the same site. Closer examination of these sites has identified that they are the result of ancient polymorphisms that have subsequently undergone lineage sorting in the Bovini tribe, of which 53 have remained polymorphic since Bos and Bison species last shared a common ancestor with Bubalus between 5–8 million years ago (MYA).Uncertainty arises in our phylogenetic reconstructions because many species in the Bovini diverged over a short period of time. It appears that a number of sites with ambiguous inheritance have been maintained in subsequent populations by chance (lineage sorting) and that they have contributed to an association between Yak and Domestic cattle and an unreliable phylogenetic reconstruction for the Bison/Yak clade. Interestingly, a number of these aberrant sites are in coding sections of the genome and their identification may have important implications for studying the neutral rate of mutation at nonsynonymous sites. The presence of these sites could help account for the apparent contradiction between levels of polymorphism and effective population size in domesticated cattle.The Bovine genome project http://www.hgsc.bcm.tmc.edu/projects/bovine/ webcite has provided researchers with an excellent resource for bovine phylogenetic studies. Genomic resources from B. taurus should have some transferabilit
Case-deletion importance sampling estimators: Central limit theorems and related results
Ilenia Epifani,Steven N. MacEachern,Mario Peruggia
Statistics , 2008, DOI: 10.1214/08-EJS259
Abstract: Case-deleted analysis is a popular method for evaluating the influence of a subset of cases on inference. The use of Monte Carlo estimation strategies in complicated Bayesian settings leads naturally to the use of importance sampling techniques to assess the divergence between full-data and case-deleted posteriors and to provide estimates under the case-deleted posteriors. However, the dependability of the importance sampling estimators depends critically on the variability of the case-deleted weights. We provide theoretical results concerning the assessment of the dependability of case-deleted importance sampling estimators in several Bayesian models. In particular, these results allow us to establish whether or not the estimators satisfy a central limit theorem. Because the conditions we derive are of a simple analytical nature, the assessment of the dependability of the estimators can be verified routinely before estimation is performed. We illustrate the use of the results in several examples.
Regularization of Case-Specific Parameters for Robustness and Efficiency
Yoonkyung Lee,Steven N. MacEachern,Yoonsuh Jung
Statistics , 2012, DOI: 10.1214/11-STS377
Abstract: Regularization methods allow one to handle a variety of inferential problems where there are more covariates than cases. This allows one to consider a potentially enormous number of covariates for a problem. We exploit the power of these techniques, supersaturating models by augmenting the "natural" covariates in the problem with an additional indicator for each case in the data set. We attach a penalty term for these case-specific indicators which is designed to produce a desired effect. For regression methods with squared error loss, an $\ell_1$ penalty produces a regression which is robust to outliers and high leverage cases; for quantile regression methods, an $\ell_2$ penalty decreases the variance of the fit enough to overcome an increase in bias. The paradigm thus allows us to robustify procedures which lack robustness and to increase the efficiency of procedures which are robust. We provide a general framework for the inclusion of case-specific parameters in regularization problems, describing the impact on the effective loss for a variety of regression and classification problems. We outline a computational strategy by which existing software can be modified to solve the augmented regularization problem, providing conditions under which such modification will converge to the optimum solution. We illustrate the benefits of including case-specific parameters in the context of mean regression and quantile regression through analysis of NHANES and linguistic data sets.
Bayesian Synthesis: Combining subjective analyses, with an application to ozone data
Qingzhao Yu,Steven N. MacEachern,Mario Peruggia
Statistics , 2011, DOI: 10.1214/10-AOAS444
Abstract: Bayesian model averaging enables one to combine the disparate predictions of a number of models in a coherent fashion, leading to superior predictive performance. The improvement in performance arises from averaging models that make different predictions. In this work, we tap into perhaps the biggest driver of different predictions---different analysts---in order to gain the full benefits of model averaging. In a standard implementation of our method, several data analysts work independently on portions of a data set, eliciting separate models which are eventually updated and combined through a specific weighting method. We call this modeling procedure Bayesian Synthesis. The methodology helps to alleviate concerns about the sizable gap between the foundational underpinnings of the Bayesian paradigm and the practice of Bayesian statistics. In experimental work we show that human modeling has predictive performance superior to that of many automatic modeling techniques, including AIC, BIC, Smoothing Splines, CART, Bagged CART, Bayes CART, BMA and LARS, and only slightly inferior to that of BART. We also show that Bayesian Synthesis further improves predictive performance. Additionally, we examine the predictive performance of a simple average across analysts, which we dub Convex Synthesis, and find that it also produces an improvement.
Review of Scott Thumma & Edward R. Gray (Eds.), Gay Religion
Craig This
Journal of Men, Masculinities and Spirituality , 2007,
Abstract: Review of Scott Thumma & Edward R. Gray (Eds.), Gay Religion (Walnut Creek, CA: AltaMira Press, 2004), xvi + 376 pp.
Model-Based Forecasts of North American Forest Growth: A Review  [PDF]
Craig Loehle
American Journal of Climate Change (AJCC) , 2018, DOI: 10.4236/ajcc.2018.74032
Abstract: In the context of climate change, planning for forest management goals becomes more complicated. Possible changes in precipitation, temperature, and CO2 can affect tree growth substantially and potential effects differ by species and region. However, integration of potential forest growth responses to these factors can be achieved using models. Because of the need to understand the range of forest growth forecasts and the strengths and limitations of different modeling approaches, I summarized results from 25 studies of forecasted forest responses over coming decades. Some models used statistical relationships between tree rings and climate to forecast growth responses to future climate, some simulated net photosynthesis of a standard forest canopy, and many used tree or stand growth models at various levels of mechanistic detail. In general, models that included CO2 responses predicted enhanced forest growth by 2100 across most of the commercial timberland areas of the US and Canada. For modest warming, most models showed growth enhancement in most regions. For hotter scenarios, many models and regions showed even more growth enhancement, but some regions such as the Southwest, mountain West, and southwestern Canada were predicted to experience drought stress and increased fire incidence, although projections in these regions were variable. Young stands, angiosperms, and early-successional species were predicted to exhibit the most positive responses. As a result, commercial harvest ages might be accelerated by several years, depending on species. Some simulations for the Midwest and Northeast US predicted a doubling or more of net primary productivity although other studies show a lesser response. Model runs that did not include mechanisms of CO2 fertilization showed positive growth responses in only limited cases and generally showed growth declines. There also was some evidence indicating the potential spread of forest into woodland at shrub or prairie ecotones.
An examination of positive selection and changing effective population size in Angus and Holstein cattle populations (Bos taurus) using a high density SNP genotyping platform and the contribution of ancient polymorphism to genomic diversity in Domestic cattle
Sean MacEachern, Ben Hayes, John McEwan, Mike Goddard
BMC Genomics , 2009, DOI: 10.1186/1471-2164-10-181
Abstract: Outgroup species: Bison, Yak and Banteng, were genotyped with high levels of success (90%) and used to determine ancestral and derived allele states in domestic cattle. Frequency spectrums of the derived alleles in Angus and Holstein were examined using Fay and Wu's H test. Significant divergences from the predicted frequency spectrums expected under neutrality were identified. This appeared to be the result of combined influences of positive selection, inbreeding and ascertainment bias for moderately frequent SNP. Approximately 10% of all polymorphisms identified as segregating in B. taurus were also segregating in Bison, Yak or Banteng; highlighting a large number of polymorphisms that are ancient in origin.These results suggest that a large effective population size (Ne) of approximately 90,000 or more existed in B. taurus since they shared a common ancestor with Bison, Yak and Banteng ~1–2 million years ago (MYA). More recently Ne decreased sharply probably associated with domestication. This may partially explain the paradox of high levels of polymorphism in Domestic cattle and the relatively small recent Ne in this species. The period of inbreeding caused Fay and Wu's H statistic to depart from its expectation under neutrality mimicking the effect of selection. However, there was also evidence for selection, because high frequency derived alleles tended to cluster near each other on the genome.Identifying positive genomic selection in domestic animals is a major challenge in contemporary agricultural research. To date only a small number of examples have successfully identified genomic regions subject to positive selection in domestic animals [1-10]. Increasing the understanding of positive selection and how it shapes genetic variation in domestic animals has the potential to provide powerful insights into the mechanisms involved in evolution, help target loci for selection and possibly highlight the genetic basis of phenotypic diversity for complex traits [5,
Collagen-based wound dressings for the treatment of diabetes-related foot ulcers: a systematic review
Holmes C, Wrobel JS, MacEachern MP, Boles BR
Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy , 2013, DOI: http://dx.doi.org/10.2147/DMSO.S36024
Abstract: llagen-based wound dressings for the treatment of diabetes-related foot ulcers: a systematic review Review (1205) Total Article Views Authors: Holmes C, Wrobel JS, MacEachern MP, Boles BR Published Date January 2013 Volume 2013:6 Pages 17 - 29 DOI: http://dx.doi.org/10.2147/DMSO.S36024 Received: 17 July 2012 Accepted: 07 September 2012 Published: 21 January 2013 Crystal Holmes,1 James S Wrobel,1 Mark P MacEachern,2 Blaise R Boles3 1Department of Internal Medicine, University of Michigan Medical School, 2A Alfred Taubman Health Sciences Library, University of Michigan, 3Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI, USA Background: Diabetic foot ulcers are a major source of morbidity, limb loss, and mortality. A prolonged inflammatory response, extracellular matrix degradation irregularities, and increased bacteria presence have all been hypothesized as major contributing factors in the delayed healing of diabetic wounds. Collagen components such as fibroblast and keratinocytes are fundamental to the process of wound healing and skin formation. Wound dressings that contain collagen products create a biological scaffold matrix that supports the regulation of extracellular components and promotes wound healing. Methods: A systematic review of studies reporting collagen wound dressings used in the treatment of Diabetic foot ulcers was conducted. Comprehensive searches were run in Ovid MEDLINE, PubMed, EMBASE, and ISI Web of Science to capture citations pertaining to the use of collagen wound dressings in the treatment of diabetic foot ulcers. The searches were limited to human studies reported in English. Results: Using our search strategy, 26 papers were discussed, and included 13 randomized designs, twelve prospective cohorts, and one retrospective cohort, representing 2386 patients with diabetic foot ulcers. Our design was not a formal meta-analysis. In those studies where complete epithelialization, 58% of collagen-treated wounds completely healed (weighted mean 67%). Only 23% of studies reported control group healing with 29% healing (weighted mean 11%) described for controls. Conclusion: Collagen- based wound dressings can be an effective tool in the healing of diabetic foot wounds. The current studies show an overall increase in healing rates despite limitations in study designs. This study suggests that future works focus on biofilms and extracellular regulation, and include high risk patients.
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