microbiomeDASim: Simulating longitudinal differential abundance for microbiome data

F1000Research - Tập 8 - Trang 1769
Justin Williams1,2, Héctor Corrada Bravo3, Jennifer Tom1, Joseph N. Paulson1
1Department of Biostatistics, Genentech, Inc, South San Francisco, CA, 94080
2Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, 90095
3Department of Computer Science, University of Maryland, College Park, College Park, MD, 24072

Tóm tắt

An increasing emphasis on understanding the dynamics of microbial communities in various settings has led to the proliferation of longitudinal metagenomic sampling studies. Data from whole metagenomic shotgun sequencing and marker-gene survey studies have characteristics that drive novel statistical methodological development for estimating time intervals of differential abundance. In designing a study and the frequency of collection prior to a study, one may wish to model the ability to detect an effect, e.g., there may be issues with respect to cost, ease of access, etc. Additionally, while every study is unique, it is possible that in certain scenarios one statistical framework may be more appropriate than another. Here, we present a simulation paradigm implemented in the R Bioconductor software package microbiomeDASim available at http://bioconductor.org/packages/microbiomeDASim microbiomeDASim. microbiomeDASim allows investigators to simulate longitudinal differential abundant microbiome features with a variety of known functional forms with flexible parameters to control desired signal-to-noise ratio. We present metrics of success results on one particular method called metaSplines.

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