Feiqiao B. Yu

To identify biological features that vary concomitantly between immune and microbiome systems, we used a multi-omic approach to integrate data across modalities (Figure S2A). We applied multi-omic factor analysis (MOFA)31 to generate factors composed of coordinated features across modalities that capture distinct biological variation across the cohort.

Main text Rapid advances in single-cell technologies and high-throughput perturbational measurements have motivated renewed efforts to model cell behavior quantitatively. These “virtual cells” are expected to learn the relationship between cell state and function and are intended to predict the consequences of perturbations—such as a gene knockdown or the application of a drug—across cell types and cell contexts.

Abstract Photosynthetic microbial mats in hot springs can provide insights into the diel behaviors of communities in extreme environments. In this habitat, photosynthesis dominates during the day, leading to super-oxic conditions, with a rapid transition to fermentation and anoxia at night. Multiple samples were collected from two springs over several years to generate metagenomic and metatranscriptomic datasets.