Shrinkage improves estimation of microbial associations under different normalization methods.

ABSTRACT: Estimation of statistical associations in microbial genomic survey count data is fundamental to microbiome research. Experimental limitations, including count compositionality, low sample sizes and technical variability, obstruct standard application of association measures and require data normalization prior to statistical estimation. Here, we investigate the interplay between data normalization, microbial association estimation and available sample size by leveraging the large-scale American Gut Project (AGP) survey data. We analyze the statistical properties of two prominent linear association estimators, correlation and proportionality, under different sample scenarios and data normalization schemes, including RNA-seq analysis workflows and log-ratio transformations. We show that shri

SUBMITTER: Badri M 

PROVIDER: S-EPMC7745771 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature