Use longitudinal plugin analysis microbiota change over time

[Joey51 (Junyan Chen)]

Hello all,
Let me first describe the background of my experiment.
I study the microbiota in insects. One of my projects is to sequence the insect bacteria at different ages. The problem is everytime I have to sacrifice the insect to get the DNA for sequencing. I was wondering if I can use the longitudinal volatility function to trace the group change during the ages?

I found that there are a lot of different longitudinal functions available, do you have any recommended longitudinal function to analyze the microbiota change over time for those samples need to be sacrificed every sampling?

Thanks ahead!

[5cr34m (Nikonov_Sergey)]

Useful (perhaps) links

A Survey of Statistical Methods for Microbiome Data Analysis

Frontiers | A Survey of Statistical Methods for Microbiome Data Analysis

BiomeHorizon: Visualizing Microbiome Time Series Data in R

https://journals.asm.org/doi/10.1128/msystems.01380-21

Regards,
SN

[colinbrislawn (Colin J Brislawn)]

The problem is everytime I have to sacrifice the insect to get the DNA for sequencing.

I feel your pain. We had to use destructive sampling to get timeseries samples for this project.

The argument we made to reviewer three was that

1. there's no better way to get this data
2. we carefully designed the lab experiment so that these samples could be considered biological replicates, even though they are physically different samples

We then treated the data as if it were from repeated-measures sampling. For this you could use longitudinal linear-mixed-effects or
longitudinal volatility.

Also consider first-distances with --p-baseline, which does not necessarily assume repeated-measures sampling at all!

[Joey51 (Junyan Chen)]

Hello Colin,
Thank you for your reply.

[Joey51 (Junyan Chen)]

Thank you very much!