[D] How to choose dimensions for latent space ?

Hi, I want to make a clustering on bioinformatics data.
I have a matrix of 129 samples and 3000 features (OTUs).
I was thinking as a preprocessing step to reduce the dimensions of this Matrix and see if I can make a better clustering. I thought of using Autorencoders and get the latent representation of the data and then apply probably k-means and see the results.
How can I choose the latent space dimensions ? I have read some papers …

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