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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Integrated Multi-omics Investigations Reveal the Key Role of Synergistic Microbial Networks in Removing Plasticizer Di-(2-Ethylhexyl) Phthalate from Estuarine Sediments.
Sean Ting-Shyang Wei,Yi Lung Chen,Yu Wei Wu,Tien Yu Wu,Yi Li Lai,Po Hsiang Wang,Po Hsiang Wang,Wael Ismail,Tzong-Huei Lee,Yin-Ru Chiang +9 more
TL;DR: In this paper, the authors employed an integrated meta-omics approach to identify the DEHP degradation pathway and major degraders in this ecosystem and proposed that DEHP biodegradation in estuarine sediments is mainly achieved through synergistic networks between denitrifying proteobacteria.
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Co-occurrence patterns of litter decomposing communities in mangroves indicate a robust community resistant to disturbances
Rodrigo Gouvêa Taketani,Rodrigo Gouvêa Taketani,Marta A. Moitinho,Tim H. Mauchline,Itamar Soares de Melo +4 more
TL;DR: The complex interactions found during litter decomposition in mangroves are studied by applying network analysis to metagenomic data to demonstrate that under different environmental pressures the microbial community associated with the decaying material forms a robust and stable network.
Journal ArticleDOI
A novel normalization and differential abundance test framework for microbiome data.
TL;DR: A novel framework for differential abundance analysis on sparse high-dimensional marker gene microbiome data is developed based on a novel network-based normalization technique and a two stage zero-inflated mixture count regression model (RioNorm2).
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The Composition and Diversity of the Gut Microbiota in Children Is Modifiable by the Household Dogs: Impact of a Canine-Specific Probiotic.
Carlos Gómez-Gallego,Mira Forsgren,Marta Selma-Royo,Merja Nermes,Merja Nermes,Maria Carmen Collado,Maria Carmen Collado,Seppo Salminen,Shea Beasley,Erika Isolauri,Erika Isolauri +10 more
TL;DR: Evidence is provided for a direct effect of home environment and household pets on children microbiota and document that modification of dog microbiota by specific probiotics is reflected in children’s microbiota.
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Nasopharyngeal Microbiota Profiles in Rural Venezuelan Children Are Associated With Respiratory and Gastrointestinal Infections
Lilly M Verhagen,Ismar A. Rivera-Olivero,Ismar A. Rivera-Olivero,Melanie Clerc,Mei Ling J N Chu,Jody van Engelsdorp Gastelaars,Maartje I Kristensen,Guy A. M. Berbers,Peter W M Hermans,Marien I. de Jonge,Jacobus H. de Waard,Jacobus H. de Waard,Debby Bogaert,Debby Bogaert +13 more
TL;DR: Interestingly, nasopharyngeal microbiota composition not only differed in children with an RTI but also in those with a GII, which suggests a reciprocal interplay between the 2 environments.
References
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QIIME allows analysis of high-throughput community sequencing data.
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