I am using the ANCOMBC method (Lin and Peddada, 2020) for microbiome differential abundance analysis. I would like to know what other methods may apply to analyze 16S rRNA gene sequencing data? and what's the benefit using that methods?
I am usually using general-purpose DE libraries such as DESeq2 or limma for my differential abundance analyses. Although it's originally designed for differential expression in transcriptomic data, diff abundance in 16S is essentially the same thing from technical and mathematical point of view.
DESeq2 is a mature pipeline with a bunch of useful vizualizations and a significant diversity of metrics, and it's highly customizable. Not certain if it has any real advantages over ANCOMBC, but it is generally a good idea to use several library/method combinations. This way you can be certain that your results are real and not a weird artifact of this particular pipeline.
Here you can find the comparison of commonly used DA tests.
https://www.nature.com/articles/s41467-022-28034-z
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