Hello Hotspot team,
Thank you for developing this method. I had a query regarding potential limitations on the number of cells or genes that Hotspot can handle effectively.
I tried running Hotspot on an AnnData object containing ~131k cells and ~9k highly variable genes, but the hs_results output returned NaN values for all genes. However, when I subsetted the data to 5,000 cells and 5,000 genes, the method worked as expected.
I wanted to ask whether there are any known scalability limitations or recommended upper bounds for the number of cells/genes when using Hotspot, or if there are specific preprocessing steps/settings recommended for larger datasets.
Edit: I think its the cells, I went down to 100 genes and still got NaNs.
Thank you, and I look forward to your response.
Regards,
Aditya Gautam
Hello Hotspot team,
Thank you for developing this method. I had a query regarding potential limitations on the number of cells or genes that Hotspot can handle effectively.
I tried running Hotspot on an AnnData object containing ~131k cells and ~9k highly variable genes, but the hs_results output returned NaN values for all genes. However, when I subsetted the data to 5,000 cells and 5,000 genes, the method worked as expected.
I wanted to ask whether there are any known scalability limitations or recommended upper bounds for the number of cells/genes when using Hotspot, or if there are specific preprocessing steps/settings recommended for larger datasets.
Edit: I think its the cells, I went down to 100 genes and still got NaNs.
Thank you, and I look forward to your response.
Regards,
Aditya Gautam