Phylogenetic reconstruction from transpositions

Background Because of the advent of high-throughput sequencing and the consequent reduction in the cost of sequencing, many organisms have been completely sequenced and most of their genes identified. It thus has become possible to represent whole genomes as ordered lists of gene identifiers and to study the rearrangement of these entities through computational means. As a result, genome rearrangement data has attracted increasing attentions from both biologists and computer scientists as a new type of data for phylogenetic analysis. The main events of genome rearrangements include inversions, transpositions and transversions. To date, GRAPPA and MGR are the most accurate methods for rearrangement phylogeny, both assuming inversion as the only event. However, due to the complexity of computing transposition distance, it is very difficult to analyze datasets when transpositions are dominant. Results We extend GRAPPA to handle transpositions. The new method is named GRAPPA-TP, with two major extensions: a heuristic method to estimate transposition distance, and a new transposition median solver for three genomes. Although GRAPPA-TP uses a greedy approach to compute the transposition distance, it is very accurate when genomes are relatively close. The new GRAPPA-TP is available from http://phylo.cse.sc.edu/ Conclusion Our extensive testing using simulated datasets shows that GRAPPA-TP is very accurate in terms of ancestor genome inference and phylogenetic reconstruction. Simulation results also suggest that model match is critical in genome rearrangement analysis: it is not accurate to simulate transpositions with other events including inversions

The Relationship between Teacher Unions and Teacher Quality in Large Urban and Suburban School Districts

This study utilizes the binomial hierarchical generalized linear modeling (HGLM) technique and nationally representative data (SASS 2003-2004) to examine the relationship between teacher unions and teacher quality in America's large urban and suburban districts and the effect of teacher unions on the intra-district distribution of teacher quality across schools with varying poverty and minority student concentration in the largest districts. Results reveal that compared with non-unionized districts, strongly unionized districts tend to have higher proportions of NCLB defined highly qualified teachers, teachers with at least five years of experience, teachers with subject-area degrees, and teachers with subject-area certifications in the large urban and suburban districts. But, strongly unionized and non-unionized districts have comparable proportions of empirically-defined high quality teachers and teachers who graduated from selective colleges. Weakly unionized districts are less likely to attract and retain experienced teachers than non-unionized ones. This study also finds that in the largest districts school poverty/minority level has a stronger (and negative) effect on the distribution of experienced teachers in strongly unionized districts than in non-unionized districts, which suggests that in strongly unionized districts the teacher quality gap is much wider across high and low poverty/minority schools in terms of employing experienced teachers

Using Jackknife to Assess the Quality of Gene Order Phylogenies

Background In recent years, gene order data has attracted increasing attention from both biologists and computer scientists as a new type of data for phylogenetic analysis. If gene orders are viewed as one character with a large number of states, traditional bootstrap procedures cannot be applied. Researchers began to use a jackknife resampling method to assess the quality of gene order phylogenies. Results In this paper, we design and conduct a set of experiments to validate the performance of this jackknife procedure and provide discussions on how to conduct it properly. Our results show that jackknife is very useful to determine the confidence level of a phylogeny obtained from gene orders and a jackknife rate of 40% should be used. However, although a branch with support value of 85% can be trusted, low support branches require careful investigation before being discarded. Conclusions Our experiments show that jackknife is indeed necessary and useful for gene order data, yet some caution should be taken when the results are interpreted