Hello,

Could you kindly provide more information on how to infer missing genes within the spatial data? Where is the transport Matrix?

Thanks,
Amina

@arezourahimi I am using DOT and I noticed you don't specify which technology you mean for low and high resolution for choosing btwrun.DOT.highresolutionandrun.DOT.lowresolution functions. Would be useful to add them which is already in preprint:
High resolution (e.g.,smFISH, MERFISH, ISS, Xenium)
Low resolution (e.g.,Visium, Slide-seq)

Hello,

I appreciate DOT, the results are interesting.
I have a question about MERFISH dataset you used, you mentioned in your paper that there are 75 samples but I found only 64 slices in the processed data which are shown here https://download.brainimagelibrary.org/cf/1c/cf1c1a431ef8d021/processed_data/cell_labels.csv

Could you clarify this?

Thanks!
Amina

Hi,

Thank you for this package. It looks great and I'm really looking forward to using it!

I'm struggling a little with setting up my srt object with an anndata input. I load the anndata from a h5ad file

and then try

dot.srt <- setup.srt(srt_data=ex_anndata$X, srt_coords=ex_anndata$obsm["spatial"])
My ex_anndata$X seems to be a matrix

and my coordinates from ex_anndata$obsm["spatial"] are the same length as my matrix

Please could I check if there's something I'm missing?

I can load from a standard xenium output using the Seurat LoadXenium() function but I've changed the segmentation and saved to a xenium experiment format with sopa, and then Seurat is having trouble with the cell_feature_matrix.zarr.zip files which is why I've gone the h5ad anndata route.

Thank you,

Best wishes,
Emily

When DOT does highly variable gene selection for setup.ref() it throws the following error:

Error in order(vg$vst.variance.standardized, decreasing = TRUE) : 
  argument 1 is not a vector
Calls: setup.ref -> order

This is due to the fact that they have refactored the output of FindVariableFeatures and how it is stored in the Seurat object.

I have fixed it for my scripts by doing:

if (seurat_obj %>% nrow() > max_genes){
    vg <- Seurat::FindVariableFeatures(seurat_obj, selection.method = "vst") %>% HVFInfo()
    vg <- rownames(vg)[order(vg$variance.standardized,  decreasing = TRUE)[1:max_genes]]
    seurat_obj <- seurat_obj[vg, ]
}

before running setup.ref()