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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Carcass mass has little influence on the structure of gravesoil microbial communities.
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The microbiome of the human lower airways: a next generation sequencing perspective.
Velma T. E. Aho,Pedro A. B. Pereira,Tari Haahtela,Ruby Pawankar,Petri Auvinen,Kaisa Koskinen +5 more
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Gender-Specific Associations Between Saliva Microbiota and Body Size
Sajan C. Raju,Sonja Lagström,Pekka Ellonen,Willem M. de Vos,Willem M. de Vos,Johan G. Eriksson,Johan G. Eriksson,Elisabete Weiderpass,Trine B. Rounge +8 more
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Direct-fed microbial supplementation influences the bacteria community composition of the gastrointestinal tract of pre- and post-weaned calves
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Rumen microbiome in dairy calves fed copper and grape-pomace dietary supplementations: Composition and predicted functional profile.
Filippo Biscarini,Fiorentina Palazzo,Federica Castellani,Giulia Masetti,Lisa Grotta,Angelo Cichelli,Giuseppe Martino +6 more
TL;DR: Results showed that feed supplementations did alter the rumen microbiome of calves, and Methanogenic taxa also responded to the feed supplementation, and methane metabolism in theRumen was the second most different pathway (up-regulated byFeed supplementations) between experimental groups.
References
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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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QIIME allows analysis of high-throughput community sequencing data.
J. Gregory Caporaso,Justin Kuczynski,Jesse Stombaugh,Kyle Bittinger,Frederic D. Bushman,Elizabeth K. Costello,Noah Fierer,Antonio Gonzalez Peña,Julia K. Goodrich,Jeffrey I. Gordon,Gavin A. Huttley,Scott T. Kelley,Dan Knights,Jeremy E. Koenig,Ruth E. Ley,Catherine A. Lozupone,Daniel McDonald,Brian D. Muegge,Meg Pirrung,Jens Reeder,Joel Sevinsky,Peter J. Turnbaugh,William A. Walters,Jeremy Widmann,Tanya Yatsunenko,Jesse R. Zaneveld,Rob Knight,Rob Knight +27 more
TL;DR: An overview of the analysis pipeline and links to raw data and processed output from the runs with and without denoising are provided.
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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.
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Differential expression analysis for sequence count data.
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Journal ArticleDOI
Metagenomic biomarker discovery and explanation
Nicola Segata,Jacques Izard,Jacques Izard,Levi Waldron,Dirk Gevers,Larisa Miropolsky,Wendy S. Garrett,Curtis Huttenhower +7 more
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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