Comparing Objective and Subjective Bayes Factors for the Two-Sample Comparison: The Classification Theorem in Action.

Many Bayes factors have been proposed for comparing population means in two-sample (independent samples) studies. Recently, Wang and Liu (2015) presented an "objective" Bayes factor (BF) as an alternative to a "subjective" one presented by Gönen et al. (2005).

Teaching Principal Components Using Correlations.

Introducing principal components (PCs) to students is difficult. First, the matrix algebra and mathematical maximization lemmas are daunting, especially for students in the social and behavioral sciences. Second, the standard motivation involving variance maximization subject to unit length constraint does not directly connect to the "variance explained" interpretation.

Pathway crosstalk effects: Shrinkage and disentanglement using a Bayesian hierarchical model.

Identifying the biological pathways that are related to various clinical phenotypes is an important concern in biomedical research. Based on estimated expression levels and/or p-values, over-representation analysis (ORA) methods provide rankings of pathways, but they are tainted because pathways overlap. This crosstalk phenomenon has not been rigorously studied and classical ORA does not take into consideration: (i) that crosstalk effects in cases of overlapping pathways can cause incorrect rankings of pathways, (ii) that crosstalk effects can cause both excess type I errors and type II errors, (iii) that rankings of small pathways are unreliable and (iv) that type I error rates can be inflated due to multiple comparisons of pathways.

Rewriting yeast central carbon metabolism for industrial isoprenoid production.

A bio-based economy has the potential to provide sustainable substitutes for petroleum-based products and new chemical building blocks for advanced materials. We previously engineered Saccharomyces cerevisiae for industrial production of the isoprenoid artemisinic acid for use in antimalarial treatments. Adapting these strains for biosynthesis of other isoprenoids such as β-farnesene (CH), a plant sesquiterpene with versatile industrial applications, is straightforward.

Closed Testing in Pharmaceutical Research: Historical and Recent Developments.

In pharmaceutical research, making multiple statistical inferences is standard practice. Unless adjustments are made for multiple testing, the probability of making erroneous determinations of significance increases with the number of inferences. Closed testing is a flexible and easily explained approach to controlling the overall error rate that has seen wide use in pharmaceutical research, particularly in clinical trials settings.