Statistical designs for two-color spotted microarray experiments

Two-color cDNA or oligonucleotide-based spotted microarrays have been commonly used in measuring the expression levels of thousands of genes simultaneously. To realize the immense potential of this powerful new technology, budgeted within limited resources or other constraints, practical designs with high efficiencies are in demand. In this study, we address the design issue concerning the arrangement of the mRNA samples labeled with fluorescent dyes and hybridized on the slides. A normalization model is proposed to characterize major sources of systematic variation in a two-color microarray experiment. This normalization model establishes a connection between designs for two-color microarray experiments with a particular class of classical row-column designs. A heuristic algorithm for constructing A-optimal or highly efficient designs is provided. Statistical optimality results are found for some of the designs generated from the algorithm. It is believed that the constructed designs are the best or very close to the best possible for estimating the relative gene expression levels among the mRNA samples of interest.     

A modified Bayes information criterion with applications to the analysis of comparative genomic hybridization data

In the analysis of data generated by change-point processes, one critical challenge is to determine the number of change-points. The classic Bayes information criterion (BIC) statistic does not work well here because of irregularities in the likelihood function. By asymptotic approximation of the Bayes factor, we derive a modified BIC for the model of Brownian motion with changing drift. The modified BIC is similar to the classic BIC in the sense that the first term consists of the log likelihood, but it differs in the terms that penalize for model dimension. As an example of application, this new statistic is used to analyze array-based comparative genomic hybridization (array-CGH) data. Array-CGH measures the number of chromosome copies at each genome location of a cell sample, and is useful for finding the regions of genome deletion and amplification in tumor cells. The modified BIC performs well compared to existing methods in accurately choosing the number of regions of changed copy number. Unlike existing methods, it does not rely on tuning parameters or intensive computing. Thus it is impartial and easier to understand and to use.     

A unified likelihood-based approach for estimating population size in continuous-time capture-recapture experiments with frailty

A unified likelihood-based approach is proposed to estimate population size for a continuous-time closed capture-recapture experiment with frailty. The frailty model allows the capture intensity to vary with individual heterogeneity, time, and behavioral response. The individual heterogeneity effect is modeled as being gamma distributed. The first-capture and recapture intensities are assumed to be in constant proportion but may otherwise vary arbitrarily through time. The approach is also extended to capture-recapture experiments with possible random removals. Simulation studies are conducted to examine the performance of the proposed estimators. By asymptotic efficiency comparison and simulation studies, the proposed estimators have been shown to be superior to their discrete-time model counterparts in genuine continuous-time capture-recapture experiments.     

Empirical‐likelihood‐based criteria for model selection on marginal analysis of longitudinal data with dropout missingness

Longitudinal data are common in clinical trials and observational studies, where missing outcomes due to dropouts are always encountered. Under such context with the assumption of missing at random, the weighted generalized estimating equation (WGEE) approach is widely adopted for marginal analysis. Model selection on marginal mean regression is a crucial aspect of data analysis, and identifying an appropriate correlation structure for model fitting may also be of interest and importance. However, the existing information criteria for model selection in WGEE have limitations, such as separate criteria for the selection of marginal mean and correlation structures, unsatisfactory selection performance in small‐sample setups, and so forth. In particular, there are few studies to develop joint information criteria for selection of both marginal mean and correlation structures. In this work, by embedding empirical likelihood into the WGEE framework, we propose two innovative information criteria named a joint empirical Akaike information criterion and a joint empirical Bayesian information criterion, which can simultaneously select the variables for marginal mean regression and also correlation structure. Through extensive simulation studies, these empirical‐likelihood‐based criteria exhibit robustness, flexibility, and outperformance compared to the other criteria including the weighted quasi‐likelihood under the independence model criterion, the missing longitudinal information criterion, and the joint longitudinal information criterion. In addition, we provide a theoretical justification of our proposed criteria, and present two real data examples in practice for further illustration.     

Larger brains spur species diversification in birds

Evidence is accumulating that species traits can spur their evolutionary diversification by influencing niche shifts, range expansions, and extinction risk. Previous work has shown that larger brains (relative to body size) facilitate niche shifts and range expansions by enhancing behavioral plasticity but whether larger brains also promote evolutionary diversification is currently backed by insufficient evidence. We addressed this gap by combining a brain size dataset for >1900 avian species worldwide with estimates of diversification rates based on two conceptually different phylogenetic‐based approaches. We found consistent evidence that lineages with larger brains (relative to body size) have diversified faster than lineages with relatively smaller brains. The best supported trait‐dependent model suggests that brain size primarily affects diversification rates by increasing speciation rather than decreasing extinction rates. In addition, we found that the effect of relatively brain size on species‐level diversification rate is additive to the effect of other intrinsic and extrinsic factors. Altogether, our results highlight the importance of brain size as an important factor in evolution and reinforce the view that intrinsic features of species have the potential to influence the pace of evolution.     

Food waste posing a serious threat to sustainability in the Kingdom of Saudi Arabia – A systematic review

Worldwide, food waste is one of the prime issues threatening food security and the Kingdom of Saudi Arabia (KSA) is not an exception. With 427 kg of food wasted per capita per year, the country ranks among the top food wasters. Ironically, the Kingdom has limited arable lands and scarce water resources to support mass-scale agriculture and to feed its increasing population, KSA relies heavily on imports and subsidized food to meet needs. Yet, food is wasted at restaurants, caterers, cafeterias and, especially, by households such that food waste is the single-largest component of the landfills. The review article is based on the grey and scientific literature published in the English and Arabic languages on the issue of food waste in Saudi Arabia. Information sources like Web of knowledge, online resources and the databases available through the King Saud University, Saudi Arabia were accessed and used to collect information on food waste, its social, cultural, economic and environmental impacts and related topics. Since food items and groceries are abundantly available to all living in KSA and they are highly subsidized, the residents take food for granted. According to a recent survey, about 78% of food purchased in KSA is discarded each week in order to make room for new groceries. The factors responsible for food waste include: lack of awareness; and insufficient and inappropriate planning when shopping. Food waste in restaurants, celebrations, social events and occasions are enormous. Waste is common in festivals and special events where the customs is to provide more food than required. There is a need to change society’s food culture, particularly among the women and the youth, as they are largest segment of the society and the prime food wasters. The analysis of the factors responsible for food waste, identified in this article suggests a “Stop Wasting Food” campaign should be launched. It is also recommended to determine and activate the role of extension education to reduce food waste in the KSA through vibrant capacity building programs for youth and women, in particular, and society in general.