Open YuxiZhang-0113 opened 2 months ago
Hi, "I often use metadata from objects processed with Seurat or stLearn and integrate this metadata into a processed CellScopes object for visualization. Sometimes, the metadata I have does not cover all the spots in the CellScopes object, leading to mismatches." You can try this:
subset_obj = cs.subset_objec(cs_obj; cells = a_vector_of_cell_ids)
"I also attempted to convert Seurat's visium object to a CellScopes object using cs.from_seurat. However, this approach does not allow me to use cs.add_visium_img to add the original Tiff file. The error I received is:" Can you use this line below and see if it works for you? I have updated the tutorial for this part.
visium = cs.add_visium_img(visium; img_path ="/mnt/sdb/breast_cancer_visium/CytAssist_FFPE_Human_Breast_Cancer_tissue_image_8bit.tif")
Hi,
I've been testing CellScopes with various spatial transcriptomics datasets and find its capabilities very impressive. However, I encountered an issue when trying to subset CellScopes objects.
I often use metadata from objects processed with Seurat or stLearn and integrate this metadata into a processed CellScopes object for visualization. Sometimes, the metadata I have does not cover all the spots in the CellScopes object, leading to mismatches.
I also attempted to convert Seurat's visium object to a CellScopes object using cs.from_seurat. However, this approach does not allow me to use cs.add_visium_img to add the original Tiff file. The error I received is:
Therefore, I would appreciate any guidance on how to subset CellScopes objects for various spatial transcriptomics and single-cell data.
Thank you for your assistance!
Best regards