I have several samples with very different sampling depths. During the rarefaction step I would either lose about 25% of my samples or I would need to use a sampling depth of 1000 to retain roughly 90% of them. I’m wondering if there is another way to calculate alpha diversity without losing so many samples?
Hi @asmaamorsi,
All Diversity metrics should be generated after applying an even sampling depth so that varying sequencing depths don't affect your diversity.
q2-boots is a new qiime2 plugin that performs rarefaction (samples n times) instead of rarefying (subsampling once). Because q2-boots performs rarefaction, you can get away with a lower sampling depth and more sample retention.
Hi @asmaamorsi and @cherman2,
Can I jump in too?
There are no hard and fast rules around sequencing depth, but tthis is a depth I work with a lot. Is there a reason you think it’s too low for your work? Did you start with a lot more reads and lose some in processing? What is your depth distribution, and what do your rarefaction curves look like?
I personally wouldn’t have an issue with a 1K rarefaction depth as an analyst, supervisor, reviewer, or editor, if due dilligance was done to show it was the happy medium for the data set.
Best,
Justine
I'll just add that combining these two suggestions - using a sampling depth of 1000 with the q2-boots core-metrics command - could be a good way to go (pending the due diligence that @jwdebelius is suggesting).