PhyInformR: phylogenetic experimental design and phylogenomic data exploration in R.

BACKGROUND: Analyses of phylogenetic informativeness represent an important step in screening potential or existing datasets for their proclivity toward convergent or parallel evolution of molecular sites. However, while new theory has been developed from which to predict the utility of sequence data, adoption of these advances have been stymied by a lack of software enabling application of advances in theory, especially for large next-generation sequence data sets. Moreover, there are no theoretical barriers to application of the phylogenetic informativeness or the calculation of quartet internode resolution probabilities in a Bayesian setting that more robustly accounts for uncertainty, yet there is no software with which a computationally intensive Bayesian approach to experimental design could be implemented. RESULTS: We introduce PhyInformR, an open source software package that performs rapid calculation of phylogenetic information content using the latest advances in phylogenetic informativeness based theory. These advances include modifications that incorporate uneven branch lengths and any model of nucleotide substitution to provide assessments of the phylogenetic utility of any given dataset or dataset partition. PhyInformR provides new tools for data visualization and routines optimized for rapid statistical calculations, including approaches making use of Bayesian posterior distributions and parallel processing. By implementing the computation on user hardware, PhyInformR increases the potential power users can apply toward screening datasets for phylogenetic/genomic information content by orders of magnitude. CONCLUSIONS: PhyInformR provides a means to implement diverse substitution models and specify uneven branch lengths for phylogenetic informativeness or calculations providing quartet based probabilities of resolution, produce novel visualizations, and facilitate analyses of next-generation sequence datasets while incorporating phylogenetic uncertainty through the use parallel processing. As an open source program, PhyInformR is fully customizable and expandable, thereby allowing for advanced methodologies to be readily integrated into local bioinformatics pipelines. Software is available through CRAN and a package containing the software, a detailed manual, and additional sample data is also provided freely through github: https://github.com/carolinafishes/PhyInformR .

Development of the Central Dogma Concept Inventory (CDCI) Assessment Tool.

Scientific teaching requires scientifically constructed, field-tested instruments to accurately evaluate student thinking and gauge teacher effectiveness. We have developed a 23-question, multiple select-format assessment of student understanding of the essential concepts of the central dogma of molecular biology that is appropriate for all levels of undergraduate biology. Questions for the Central Dogma Concept Inventory (CDCI) tool were developed and iteratively revised based on student language and review by experts. The ability of the CDCI to discriminate between levels of understanding of the central dogma is supported by field testing (N= 54), and large-scale beta testing (N= 1733). Performance on the assessment increased with experience in biology; scores covered a broad range and showed no ceiling effect, even with senior biology majors, and pre/posttesting of a single class focused on the central dogma showed significant improvement. The multiple-select format reduces the chances of correct answers by random guessing, allows students at different levels to exhibit the extent of their knowledge, and provides deeper insight into the complexity of student thinking on each theme. To date, the CDCI is the first tool dedicated to measuring student thinking about the central dogma of molecular biology, and version 5 is ready to use.

DNA → RNA: What Do Students Think the Arrow Means?

The central dogma of molecular biology, a model that has remained intact for decades, describes the transfer of genetic information from DNA to protein though an RNA intermediate. While recent work has illustrated many exceptions to the central dogma, it is still a common model used to describe and study the relationship between genes and protein products. We investigated understanding of central dogma concepts and found that students are not primed to think about information when presented with the canonical figure of the central dogma. We also uncovered conceptual errors in student interpretation of the meaning of the transcription arrow in the central dogma representation; 36% of students (n = 128; all undergraduate levels) described transcription as a chemical conversion of DNA into RNA or suggested that RNA existed before the process of transcription began. Interviews confirm that students with weak conceptual understanding of information flow find inappropriate meaning in the canonical representation of central dogma. Therefore, we suggest that use of this representation during instruction can be counterproductive unless educators are explicit about the underlying meaning.