Source Themes

Semisynthetic Simulation for Microbiome Data Analysis

High-throughput sequencing data lie at the heart of modern microbiome research. Effective analysis of these data requires careful preprocessing, modeling, and interpretation to detect subtle signals and avoid spurious associations. In this review, we …

Microbial network inference for longitudinal microbiome studies with LUPINE

The microbiome is a complex ecosystem of interdependent taxa that has traditionally been studied through cross-sectional studies. However, longitudinal microbiome studies are becoming increasingly popular. These studies enable researchers to infer …

Microbiota DNA isolation, 16S rRNA amplicon sequencing, and bioinformatic analysis for bacterial microbiome profiling of rodent fecal samples

Fecal samples are frequently used to characterize bacterial populations of the gastrointestinal tract. A protocol is provided to profile gut bacterial populations using rodent fecal samples. We describe the optimal procedures for collecting rodent …

Faecal microbiota transplant ameliorates gut dysbiosis and cognitive deficits in Huntington’s disease mice

Huntington’s disease is a neurodegenerative disorder involving psychiatric, cognitive and motor symptoms. Huntington’s disease is caused by a tandem-repeat expansion in the huntingtin gene, which is widely expressed throughout the brain and body, …

Statistical challenges in longitudinal microbiome data analysis

The microbiome is a complex and dynamic community of microorganisms that co-exist interdependently within an ecosystem, and interact with its host or environment. Longitudinal studies can capture temporal variation within the microbiome to gain …

Gene-environment-gut interactions in Huntington's disease mice are associated with environmental modulation of the gut microbiome

Gut dysbiosis in Huntington's disease (HD) has recently been reported using microbiome profiling in R6/1 HD mice and replicated in clinical HD. In HD mice, environmental enrichment (EE) and exercise (EX) were shown to have therapeutic impacts on the …

Inferring extinction date of a species using non‐homogeneous Poisson processes with a change‐point

Bayesian methods have been developed for inferring the true year of extinction of a species from sighting records that have both certain and uncertain sightings. These methods typically make the restrictive assumption that all sighting types (i.e. …

Inferring extinction year using a Bayesian approach

Species sighting records are combined with statistical models to infer whether an endangered species might have become extinct or instead it has just gone unobserved for a lengthy period of time. The challenging part of developing these models lies …

Using survival theory models to quantify extinctions

Extinctions are difficult to observe and typically are inferred from the timing and reliability of field observations and collections. Recent advances in approaches to estimating extinction probability consider the type, timing and certainty of …

Bayesian updating to estimate extinction from sequential observation data

Several new approaches to estimating the probability that a species is extinct have emerged recently. Different foundational assumptions can lead to different interpretations of data and potentially to different conclusions. To explore the …