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Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases
TLDR
It is demonstrated that periods of disease activity were also marked by increases in temporal variability, with characteristic taxonomic, functional, and biochemical shifts, and integrative analysis identified microbial, biochemical, and host factors central to this dysregulation.
Gut microbiome structure and metabolic activity in inflammatory bowel disease
TLDR
Using metabolomics and shotgun metagenomics on stool samples from individuals with and without inflammatory bowel disease, metabolites, microbial species and genes associated with disease were identified and validated in an independent cohort, providing an improved understanding of perturbations of the microbiome–metabolome interface in IBD.
Negative binomial mixed models for analyzing microbiome count data
TLDR
A flexible and efficient IWLS (Iterative Weighted Least Squares) algorithm is developed to fit the proposed negative binomial mixed models (NBMMs) for detecting the association between the microbiome and host environmental/clinical factors for correlated microbiome count data.
Multivariable Association Discovery in Population-scale Meta-omics Studies
TLDR
An optimized combination of novel and established methodology to assess multivariable association of microbial community features with complex metadata in population-scale observational studies and reveals that MaAsLin 2’s linear model preserves statistical power in the presence of repeated measures and multiple covariates, while accounting for the nuances of meta-omics features and controlling false discovery.
Predictive metabolomic profiling of microbial communities using amplicon or metagenomic sequences
TLDR
A computational approach to predict potentially unobserved metabolites in new microbial communities, given a model trained on paired metabolomes and metagenomes from the environment of interest is described.
A New Bayesian Lasso.
TLDR
This paper considers a fully Bayesian treatment that leads to a new Gibbs sampler with tractable full conditional posterior distributions and shows that the new algorithm has good mixing property and performs comparably to the existing Bayesian method in terms of both prediction accuracy and variable selection.
Global chemical effects of the microbiome include new bile-acid conjugations
TLDR
It is found that the microbiota affects the chemistry of all organs, including amino acid conjugations of host bile acids that were used to produce phenylalanocholic acid, tyrosocholic acid and leucocholic Acid, which have not previously been characterized despite extensive research on bile-acid chemistry.
Metatranscriptome of human fecal microbial communities in a cohort of adult men
TLDR
An initial characterization of human faecal microbial ecology into core, subject-specific, microorganism-specific and temporally variable transcription is provided, and a metatranscriptomic 'core' universally transcribed over time and across participants is identified, often by different microorganisms.
Bayesian bridge regression
TLDR
This study proposes bridge regression from a Bayesian perspective, and shows that the proposed method performs as well as or better than published methods while offering the advantage of posterior inference.
ZERO-INFLATED NEGATIVE BINOMIAL REGRESSION FOR DIFFERENTIAL ABUNDANCE TESTING IN MICROBIOME STUDIES
TLDR
Application to two real datasets indicate that the proposed Zero-inflated Negative Binomial regression for identifying differentially abundant taxa between two or more populations is capable of detecting biologically meaningful taxa, consistent with previous studies.
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