Edward Zhao

Thanks for the feedback Leo. I'll try to implement this as an option in the next version.

Hi Mustafa, I don't have a good solution for this unfortunately. We are working on computational improvements but nothing that will help immediately. I will note that the main part...

How many spots is the dataset you are working with? And how many iterations are you using?

Ok, yeah unfortunately the armadillo c++ library has some limitations on the size of matrices. One workaround is to just lower the number of iterations. If you think the results...

It seems like the neighbor finding didn't work in that case. Do you have Visium data? Did you load it in using BayesSpace's `readVisium` function? If not, make sure you...

I'm assuming you are running this on a HPC or other high memory machine. Are you able to allocate more memory to the job?

I don't think I have any other solution unfortunately besides allocating more memory and/or further reducing your # of iterations.

Hi Abby, yes I have seen this happen before in other data as well. In such cases, BayesSpace's model finds better partitions of the data using fewer clusters. The spatial...

Hi Astrid, Unfortunately we didn't set a parameter for this. As a temporary workaround, you can copy the relevant functions (`enhanceFeatures()`, `.enhance_features()`, and `.xgboost_enhance`) in https://github.com/edward130603/BayesSpace/blob/master/R/enhanceFeatures.R and edit the `xgboost()`...

Hi, I'm not too familiar with Seurat. I think it might be best if you ask the Seurat package maintainers first. If they aren't able to help, I can look...