**10**wrote:

On Waste Not, Want Not: Why Rarefying Microbiome Data Is Inadmissible's figure 1: https://journals.plos.org/ploscompbiol/article/comment?id=10.1371/annotation/043bcfb2-1583-41a8-9497-807232f001f4

Am I the only one to think that Fig 1 actually shows the oppsite conclusion?

The stat is significant due to larger sampling effect on sample B. After adjusting the sampling effect, we no longer have the false positive.

On the other word, if random sampling is inadmissible, what if I sequenced sample B twice. One time I got 50, 50, and the other time I got 5000, 5000. How should I interpret the totally differnt stat outcome if random sampling is not applied?

It is true that with more reads, we have larger statistic power.

But how should we deal with the uneven stat power among samples with different depth?

Comparison between two depth seqenced samples will have a larger statistic power than that between two shallow samples. Is our conclusion based on the uneven depth justified, if we cannot fix the "fase negative" by sequencing again?

10The authors argue one could use edgeR or DESeq2 (which account for differences in library sizes) to analyse microbiome data:

Of course one can sequence again to balance all library sizes to an appropriate sequencing depth, but this costs time and money. Using more powerful analysis methods is cheaper and faster.

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