Authors
Donald T McKnight, Roger Huerlimann, Deborah S Bower, Lin Schwarzkopf, Ross A Alford, Kyall R Zenger
Publication date
2019/3
Journal
Methods in Ecology and Evolution
Volume
10
Issue
3
Pages
389-400
Description
- 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 in species evenness, potentially distorting community‐level patterns. Furthermore, the recommended methods use log transformations, which we expect to exaggerate the importance of differences among rare OTUs, while suppressing the importance of differences among common OTUs.
- We tested these theoretical predictions …
Scholar articles
DT McKnight, R Huerlimann, DS Bower, L Schwarzkopf… - Methods in Ecology and Evolution, 2019