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Open AccessJournal ArticleDOI

Differential abundance analysis for microbial marker-gene surveys

TLDR
It is shown that metagenomeSeq outperforms the tools currently used in this field and relies on a novel normalization technique and a statistical model that accounts for undersampling in large-scale marker-gene studies.
Abstract
We introduce a methodology to assess differential abundance in sparse high-throughput microbial marker-gene survey data. Our approach, implemented in the metagenomeSeq Bioconductor package, relies on a novel normalization technique and a statistical model that accounts for undersampling-a common feature of large-scale marker-gene studies. Using simulated data and several published microbiota data sets, we show that metagenomeSeq outperforms the tools currently used in this field.

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Roots and Panicles of the C4 Model Grasses Setaria viridis (L). and S. pumila Host Distinct Bacterial Assemblages With Core Taxa Conserved Across Host Genotypes and Sampling Sites

TL;DR: This work collected wild individuals of both grass species from 20 different locations across Austria and investigated the bacterial assemblages within roots and ripe grain-harboring panicles by 16S rRNA gene-based Illumina sequencing, finding roots hosted more diverse microbiota than panicles.
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Occupancy strongly influences faecal microbial composition of wild lemurs.

TL;DR: The findings showed that among the studied factors occupancy had the strongest influence on intestinal microbiota of congeneric lemur species, which suggests adaptation of microbiota to differences in forest composition, climate variations and correspondingly available diet in different geographical locations of Madagascar.
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Fast and Slow-Growing Management Systems: Characterisation of Broiler Caecal Microbiota Development throughout the Growing Period.

TL;DR: Fast and slow-growing broiler microbiota are in constant development throughout rearing, being relatively stable at 21 days of age, and the most abundant bacteria groups are related to better productive performance and intestinal health.
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Heart Failure Severity Closely Correlates with Intestinal Dysbiosis and Subsequent Metabolomic Alterations

TL;DR: In this article , a mouse model of transverse aortic constriction (TAC) was used to decipher the association between the severity and progression of heart failure and the gut microbiome composition and circulating metabolites.
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Cognitive Function Associated with Gut Microbial Abundance in Sucrose and S-Adenosyl-L-Methionine (SAMe) Metabolic Pathways.

TL;DR: Gut microbe community diversity was similar in AD patients regardless of MCI or dementia status, however, differential analyses probed in lower-level taxa and metabolic pathways suggested that specific gut microbes in Firmicutes and Actinobacteria might involve in cognitive decline.
References
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Journal ArticleDOI

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
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Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy

TL;DR: The RDP Classifier can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes, and the majority of the classification errors appear to be due to anomalies in the current taxonomies.
Journal ArticleDOI

Differential expression analysis for sequence count data.

Simon Anders, +1 more
- 27 Oct 2010 - 
TL;DR: A method based on the negative binomial distribution, with variance and mean linked by local regression, is proposed and an implementation, DESeq, as an R/Bioconductor package is presented.
Journal ArticleDOI

Metagenomic biomarker discovery and explanation

TL;DR: A new method for metagenomic biomarker discovery is described and validates by way of class comparison, tests of biological consistency and effect size estimation to address the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities.
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