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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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Citations
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Journal ArticleDOI

Analysis of microbial compositions: a review of normalization and differential abundance analysis.

TL;DR: Some recent methods for differential abundance analysis are reviewed and described and their strengths and weaknesses are described.
Journal ArticleDOI

Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics

TL;DR: It is shown that sample size, effect size, and gene abundance greatly affect the performance of all methods, and several of the methods also show non-optimal model assumptions and biased false discovery rate estimates, which can result in too large numbers of false positives.
Journal ArticleDOI

Contributions of the maternal oral and gut microbiome to placental microbial colonization in overweight and obese pregnant women

TL;DR: It is demonstrated that the placental microbiome exhibits a higher resemblance and phylogenetic proximity with the pregnant oral microbiome, suggesting that placental colonization may have multiple niche sources.
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The Core and Seasonal Microbiota of Raw Bovine Milk in Tanker Trucks and the Impact of Transfer to a Milk Processing Facility

TL;DR: Raw bovine milk samples from 899 tanker trucks arriving at two dairy processors in San Joaquin Valley of California during three seasons were analyzed by community 16S rRNA gene sequencing, revealing highly diverse bacterial populations, which exhibited seasonal differences.
Journal ArticleDOI

Apple endophytic microbiota of different rootstock/scion combinations suggests a genotype-specific influence.

TL;DR: The similarity of the microbiota in samples with a similar pedigree suggests the possibility of some level of co-evolution or selection as proposed by the “holobiont” concept in which metaorganisms have co-Evolved.
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.
Journal ArticleDOI

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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