Single cell expression and chromatin accessibility of the Toxoplasma gondii lytic cycle identifies AP2XII-8 as an essential ribosome regulon driver.

Sequential lytic cycles driven by cascading transcriptional waves underlie pathogenesis in the apicomplexan parasite Toxoplasma gondii. This parasite's unique division by internal budding, short cell cycle, and jumbled up classically defined cell cycle stages have restrained in-depth transcriptional program analysis. Here, unbiased transcriptome and chromatin accessibility maps throughout the lytic cell cycle are established at the single-cell level.

Elucidating Cancer Subtypes by Using the Relationship between DNA Methylation and Gene Expression.

Advancements in the field of next generation sequencing (NGS) have generated vast amounts of data for the same set of subjects. The challenge that arises is how to combine and reconcile results from different omics studies, such as epigenome and transcriptome, to improve the classification of disease subtypes. In this study, we introduce sCClust (sparse canonical correlation analysis with clustering), a technique to combine high-dimensional omics data using sparse canonical correlation analysis (sCCA), such that the correlation between datasets is maximized.

Robust phenotype prediction from gene expression data using differential shrinkage of co-regulated genes.

Discovery of robust diagnostic or prognostic biomarkers is a key to optimizing therapeutic benefit for select patient cohorts - an idea commonly referred to as precision medicine. Most discovery studies to derive such markers from high-dimensional transcriptomics datasets are weakly powered with sample sizes in the tens of patients. Therefore, highly regularized statistical approaches are essential to making generalizable predictions.

A general benevolence dimension that links neural, psychological, economic, and life-span data on altruistic tendencies.

[Correction Notice: An Erratum for this article was reported in Vol 145(10) of (see record 2016-46925-004). In the article, there was an error in the Task, Stimuli, and Procedures section. In the 1st sentence in the 6th paragraph, “Following the scanning phase, participants completed self-report questionnaires meant to reflected the Prosocial Disposition construct: the agreeableness scale from the Big F, which includes empathic concern and perspective-taking, and a scale of personality descriptive adjectives related to altruistic behavior (Wood, Nye, & Saucier, 2010).

A hierarchical model for simultaneous detection and estimation in multi-subject fMRI studies.

In this paper we introduce a new hierarchical model for the simultaneous detection of brain activation and estimation of the shape of the hemodynamic response in multi-subject fMRI studies. The proposed approach circumvents a major stumbling block in standard multi-subject fMRI data analysis, in that it both allows the shape of the hemodynamic response function to vary across region and subjects, while still providing a straightforward way to estimate population-level activation. An efficient estimation algorithm is presented, as is an inferential framework that allows for not only tests of activation, but also tests for deviations from some canonical shape.