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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Investigating microbial associations from sequencing survey data with co-correspondence analysis
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The microbiome of common bedding materials before and after use on commercial dairy farms
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Proceedings ArticleDOI
A comparison study of statistical methods for the analysis metagenome data
TL;DR: This work systematically investigates the properties of statistical methods for MWAS and compares their performances using simulation data generated from Human Microbiome Project data, finding metagenomeSeq methods showed higher power than ANCOM in the power comparison study.
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The oral microbiome in relation to pancreatic cancer risk in African Americans.
Jessica L. Petrick,Jeremy E. Wilkinson,Dominique S. Michaud,Qiuyin Cai,Hanna Gerlovin,Lisa B. Signorello,Brian M. Wolpin,Edward A. Ruiz-Narváez,Jirong Long,Yaohua Yang,W. Evan Johnson,Xiao-Ou Shu,Curtis Huttenhower,Curtis Huttenhower,Julie R. Palmer +14 more
TL;DR: In this paper, the authors investigated the oral microbiome in relation to pancreatic cancer risk among 122 African-American patients and 354 controls and found no associations with alpha or beta diversity, and no individual microbial taxa were differentially abundant between cases and control.
References
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