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.read more
Citations
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Host genotype and amoxicillin administration affect the incidence of diarrhoea and faecal microbiota of weaned piglets during a natural multiresistant ETEC infection.
Francesca Romana Massacci,Francesca Romana Massacci,Silvia Tofani,Claudio Forte,Micol Bertocchi,Carmela Lovito,Serenella Orsini,Michele Tentellini,Lucia Marchi,Gaetan Lemonnier,Diana Luise,Fany Blanc,Adrien Castinel,Claudia Bevilacqua,Claire Rogel-Gaillard,Giovanni Pezzotti,Jordi Estellé,Paolo Trevisi,Chiara Francesca Magistrali +18 more
TL;DR: Evaluating the effects of the MUC4 and FUT1 genotypes and the administration of amoxicillin through different routes on the presence of diarrhoea and the faecal microbiota composition in piglets naturally infected with ETEC revealed that groupAmoxicillin treatment may produce adverse outcomes on pig health in course of multiresistant ETEC infection.
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References
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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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QIIME allows analysis of high-throughput community sequencing data.
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Metagenomic biomarker discovery and explanation
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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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