Hi, thank you for incorporating the LDA topic modeling module into scvi. I was curious if folks had suggestions on what would be a good approach to picking the number of topics for topic modeling?
My first thought was to run LDA topic modeling on a range of n_topics from 3-100. And then try and use an unbiased approach to get a ballpark of the number of topics, followed by a more supervised approach by looking at the genes in each topic and assessing if they fit what I knew biologically.
For the unbiased approach, based on the documentation, I thought to use the ELBO and perplexity scores, but I’m unsure how to interpret these values. I also have quite a few cases where they’re NA or Inf and I’m unsure what to make of that.
I was wondering if anyone else had experience with this, and if I’m going about this analysis the correct way?
Thank you!
Kartik