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bioRxivBioinformaticsPreprint

GMPR: A novel normalization method for microbiome sequencing data

Li CheniD, Jun CheniD

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Abstract

SummaryNormalization is the first and a critical step in microbiome sequencing (microbiome-Seq) data analysis to account for variable library sizes. Though RNA-Seq based normalization methods have been adapted for microbiome-Seq data, they fail to consider the unique characteristics of microbiome-Seq data, which contain a vast number of zeros due to the physical absence or undersampling of the microbes. Normalization methods that specifically address the zeroinflation remain largely undeveloped. Here we propose GMPR - a simple but effective normalization method - for zeroinflated sequencing data such as microbiome-Seq data. Simulation studies and analyses of 38 real gut microbiome datasets from 16S rRNA gene amplicon sequencing demonstrated the superior performance of the proposed method.\n\nAvailability and Implementation GMPR is implemented in R andavailable at https://github.com/jchen1981/GMPR\n\nSupplementary InformationSupplementary data are available at Bioinformatics online.\n\nContactChen.Jun2@mayo.edu

Citations
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