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powmic: an R package for power assessment in microbiome case–control studies

Li Chen

2020Bioinformatics10 citationsDOI

Abstract

SUMMARY: Power analysis is essential to decide the sample size of metagenomic sequencing experiments in a case-control study for identifying differentially abundant (DA) microbes. However, the complexity of microbial data characteristics, such as excessive zeros, over-dispersion, compositionality, intrinsically microbial correlations and variable sequencing depths, makes the power analysis particularly challenging because the analytical form is usually unavailable. Here, we develop a simulation-based power assessment strategy and R package powmic, which considers the complexity of microbial data characteristics. A real data example demonstrates the usage of powmic. AVAILABILITY AND IMPLEMENTATION: powmic R package and online tutorial are available at https://github.com/lichen-lab/powmic. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Topics & Concepts

R packageComputer scienceMetagenomicsMicrobiomeSoftware packageData miningVariable (mathematics)SoftwareData scienceComputational biologyBioinformaticsBiologyProgramming languageMathematicsGeneBiochemistryMathematical analysisGut microbiota and healthMicrobial Community Ecology and PhysiologyMetabolomics and Mass Spectrometry Studies
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