Data from: Methods for normalizing microbiome data: an ecological perspective

Donald T. McKnight, Roger Huerlimann, Deborah S. Bower, Lin Schwarzkopf, Ross A. Alford & Kyall R. Zenger
1. Microbiome sequencing data often need to be normalized due to differences in read depths, and recommendations for microbiome analyses generally warn against using proportions or rarefying to normalize data and instead advocate alternatives, such as upper quartile, CSS, edgeR-TMM, or DESeq-VS. Those recommendations are, however, based on studies that focused on differential abundance testing and variance standardization, rather than community-level comparisons (i.e., beta diversity), Also, standardizing the within-sample variance across samples may suppress differences...
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