Faisal Ababneh

The biasing effect of compositional heterogeneity on phylogenetic estimates may be underestimated.

The effect of compositional heterogeneity in sequence data on phylogenetic inference was first identified as a potential problem in the late 1980s and early 1990s (Chang and Campbell, 2000; Conant and Lewis, 2001; Foster and Hickey, 1999; Hasegawa et al., 1993; Klenk et al., 1994; Lockhart et al., 1992a, 1992b; Loomis and Smith, 1990; Olsen and Woese, 1993; Penny et al., 1990; Sogin et al., 1993; Tarrio et al., 2001; Van Den Bussche et al., 1998; Weisburg et al., 1989), and by 1993 the first methods had been developed to measure the extent of the problem (Lockhart et al., 1993, 1994; Steel et al., 1993, 1995) or to overcome it (Foster, 2004; Galtier and Gouy, 1995, 1998; Galtier et al., 1999; Gu and Li, 1996, 1998; Lake, 1994; Steel, 1994; Steel et al., 1993, 1995; Tamura and Kumar, 2002; Yang and Roberts, 1995). It is now widely accepted that compositional heterogeneity in aligned sequence data can mislead methods commonly used to infer phylogenetic trees, but it is still unclear (i) why phylogenetic studies based on the LogDet (or paralinear) distance (Lockhart et al., 1994; Steel, 1994) sometimes fail to recover the expected tree topology from compositionally heterogeneous alignments (e.g., Foster and Hickey, 1999; Tarrio et al., 2001), and (ii) how much compositional convergence is necessary before the phylogenetic methods fail to recover the correct topology. Using Monte Carlo simulations to address the second point, Conant and Lewis (2001) concluded that “rather extreme amounts of convergence are necessary before parsimony begins to prefer the incorrect tree.” Other simulation studies have reached similar conclusions (e.g., Galtier and Gouy, 1995; Rosenberg and Kumar, 2003; Van Den Bussche et al., 1998). Based on the study by Galtier and Gouy (1995), it would appear that it is safe to use DNA for phylogenetic inference as long as the difference in GC content is less than 8% to 10%. This im-

Matched-pairs tests of homogeneity with applications to homologous nucleotide sequences

MOTIVATIONnMost phylogenetic methods assume that the sequences of nucleotides or amino acids have evolved under stationary, reversible and homogeneous conditions. When these assumptions are violated by the data, there is an increased probability of errors in the phylogenetic estimates. Methods to examine aligned sequences for these violations are available, but they are rarely used, possibly because they are not widely known or because they are poorly understood.nnnRESULTSnWe describe and compare the available tests for symmetry of k-dimensional contingency tables from homologous sequences, and develop two new tests to evaluate different aspects of the evolutionary processes. For any pair of sequences, we consider a partition of the test for symmetry into a test for marginal symmetry and a test for internal symmetry. The proposed tests can be used to identify appropriate models for estimation of evolutionary relationships under a Markovian model. Simulations under more or less complex evolutionary conditions were done to display the performance of the tests. Finally, the tests were applied to an alignment of small-subunit ribosomal RNA sequences of five species of bacteria to outline the evolutionary processes under which they evolved.nnnAVAILABILITYnPrograms written in R to do the tests on nucleotides are available from http://www.maths.usyd.edu.au/u/johnr/testsym/

Phylogenetic Model Evaluation

Most phylogenetic methods are model-based and depend on Markov models designed to approximate the evolutionary rates between nucleotides or amino acids. When Markov models are selected for analysis of alignments of these characters, it is assumed that they are close approximations of the evolutionary processes that gave rise to the data. A variety of methods have been developed for estimating the fit of Markov models, and some of these methods are now frequently used for the selection of Markov models. In a growing number of cases, however, it appears that the investigators have used the model-selection methods without acknowledging their inherent shortcomings. This chapter reviews the issue of model selection and model evaluation.

Generation of the Exact Distribution and Simulation of Matched Nucleotide Sequences on a Phylogenetic Tree

Nucleotide sequences are often generated by Monte Carlo simulations to address complex evolutionary or analytic questions but the simulations are rarely described in sufficient detail to allow the research to be replicated. Here we briefly review the Markov processes of substitution in a pair of matching (homologous) nucleotide sequences and then extend it to k matching nucleotide sequences. We describe calculation of the joint distribution of nucleotides of two matching sequences. Based on this distribution, we give a method for simulation of the divergence matrix for n sites using the multinomial distribution. This is then extended to the joint distribution for k nucleotide sequences and the corresponding 4k divergence array, generalizing Felsenstein (Journal of Molecular Evolution, 17, 368–376, 1981), who considered stationary, homogeneous and reversible processes on trees. We give a second method to generate matched sequences that begins with a random ancestral sequence and applies a continuous Markov process to each nucleotide site as in Rambaut and Grassly (Computer Applications in the Biosciences, 13, 235–238, 1997); further, we relate this to an equivalent approach based on an embedded Markov chain. Finally, we describe an approximate method that was recently implemented in a program developed by Jermiin et al. (Applied Bioinformatics, 2, 159–163, 2003). The three methods presented here cater for different computational and mathematical limitations and are shown in an example to produce results close to those expected on theoretical grounds. All methods are implemented using functions in the S-plus or R languages.

Reducing model complexity of the general Markov model of evolution.

The selection of an optimal model for data analysis is an important component of model-based molecular phylogenetic studies. Owing to the large number of Markov models that can be used for data analysis, model selection is a combinatorial problem that cannot be solved by performing an exhaustive search of all possible models. Currently, model selection is based on a small subset of the available Markov models, namely those that assume the evolutionary process to be globally stationary, reversible, and homogeneous. This forces the optimal model to be time reversible even though the actual data may not satisfy these assumptions. This problem can be alleviated by including more complex models during the model selection. We present a novel heuristic that evaluates a small fraction of these complex models and identifies the optimal model.

Substantial gender gap reduction in Bangladesh explained by the proximity measure of literacy and life expectancy

ABSTRACT The Human Development Index (HDI) is an indicator that substantially captures the overall country level status on human welfare based on issues of equity, poverty, and gender. This study uses a proximity measure of simultaneous effect of literacy and life expectancy called literate life expectancy (LLE) as a measure of human quality. This study discusses the distribution of LLE along with giving a detail gender and spatial differentials. With the proximity indicator we quantify gander gap between the year 1981 and 2008. Over the 27 years more than substantial improvement in LLE are found among women than with far less improvement rate among men in both national and residence level. We also learn that measured over time, the indicator allows statements about the rate of change and not just static differences. The LLE is useful as this index could be used to calculate future social development by adopting different mortality and educational scenarios such as health treatment facilities, nutritious food, easy access to clean drinking water, air pollution, greenhouse emissions, psychological stress, and most importantly, poverty, which can be associated with specific policy assumptions.

Identifying Optimal Models of Evolution

Most phylogenetic methods are model-based and depend on models of evolution designed to approximate the evolutionary processes. Several methods have been developed to identify suitable models of evolution for phylogenetic analysis of alignments of nucleotide or amino acid sequences and some of these methods are now firmly embedded in the phylogenetic protocol. However, in a disturbingly large number of cases, it appears that these models were used without acknowledgement of their inherent shortcomings. In this chapter, we discuss the problem of model selection and show how some of the inherent shortcomings may be identified and overcome.

CONSANGUINEOUS MARRIAGE IN JORDAN: AN UPDATE

This study examined the recent level, trends and determinants of consanguineous marriage in Jordan using time-series data from the Jordan Population and Family Health Surveys (JPFHSs). According to the 2012 JPFHS, 35% of all marriages were consanguineous in Jordan in 2012. There has been a declining trend in consanguinity in the country, with the rate decreasing from a level of 57% in 1990. Most consanguineous marriage in 2012 were first cousin marriages, constituting 23% of all marriages and 66% of all consanguineous marriages. The data show that women with a lower age at marriage, older marriage cohort, larger family size, less than secondary level of education, rural place of residence, no employment, no exposure to mass media, a monogamous marriage, a husband with less than higher level of education and lower economic status, and those from the Badia region, were more likely to have a consanguineous marriage. Increasing age at marriage, level of education, urbanization and knowledge about the health consequences of consanguinity, and the ongoing socioeconomic and demographic transition in the country, will be the driving forces for further decline in consanguinity in Jordan.

Simulation of time series wind speed at an international airport

The sporadic and unstable nature of wind speed renders it very difficult to predict accurately to serve various decisions, such as safety in the air traffic flow and reliable power generation system. In this study we assessed the autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models on the wind speed time series problem. Data on wind speed and minimum and maximum temperatures were evaluated. Wind speed was established to follow a time series that fluctuated around ARIMA (0,1,1) and ARIMA (1,1,1). The optimal ANN model was established at 10 hidden neurons. The performance indices considered all indicated that the ANN wind speed model was superior to the ARIMA model. Wind speed prediction accuracy can be improved to secure the safety of air traffic flow as well support the implementation of a reliable and secure power generation system at the airport.

730 Factors causing deaths due to injury among children in Bangladesh

Background Child injury has become a public health concern in both developing and developed world. In recent times, injury has been identified as a leading cause for both morbidity and mortality among children. This study has concentrated on a holistic statistical inquest into injuries and deaths among children in Bangladesh. Methods A population-based cross-sectional survey was conducted between January and December 2003 in Bangladesh. Nationally representative data were collected from 171,366 rural and urban households, with a total sample size of 819,429. A simple association test and the binary logistic regression was designed to identify the factors causing child death due to injury. Results Drowning found the leading cause of death of children in Bangladesh. Approximately 26% children died from drowning each year. Almost 50% of children died in a year from just because they did not get proper care after getting injured. Mother’s education has a significant influence on child injury and death. The percentage of child death due to injury was the highest from a mother’s lack of awareness and education (54%). The odds of dying due to injury among children of secondary and graduate level educated mothers are respectively 1.4 and 1.6 times more than the odds in the chances of death of an illiterate mother’s child. This may be due to the fact that educated mothers have less time to supervise their children because of their daily activities. It was also found that almost 63% of the children who died from injury were from rural areas. Conclusion Child injury is an emerging cause of mortality and morbidity in both urban and rural areas of Bangladesh. Children from rural area were the more vulnerable group for different types of injuries compared to urban population. The home is the most common place for injury occurrence. Acknowledgements The financial support of UNICEF is acknowledged.