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How to include spatial coordinate data into anndata within scanpy

Hello I am working on 10X visium spatial transcriptome data which was processed in seurat pacakge with image data. For my downstream analysis, I am trying to import seurat normalized data into scanpy. For this I converted seurat object to h5ad using these steps.

SaveH5Seurat(test_object, overwrite = TRUE, filename = "A1")

Convert("A1.h5seurat", dest = "h5ad", overwrite = TRUE)

Next, imported h5ad format file into scanpy :

adata1 = sc.read_h5ad("A1.h5ad")

But it does not contain any spatial and image information.

obs: 'orig.ident', 'nCount_Spatial', 'nFeature_Spatial', 'cell.ids', 'nCount_SCT', 'nFeature_SCT', 'seurat_clusters', var: 'features', 'SCT_features', 'genename' obsm: 'X_pca', 'X_umap' varm: 'PCs' layers: 'SCT'

raise KeyError( KeyError: "Could not find entry in obsm for 'spatial'.\nAvailable keys are: ['X_pca', 'X_umap']."

How can I add image and coordinate information in 'obsm' for spatial information ?

I would appreciate all the suggestion .

Thanks in advance

scanpy visium transcriptome spatial 10x
• 8,197 views • link
updated by Vimala • Vimala • written by Omics data mining Omics data mining

Hi, were you able to figure this out? I found that I couldn't even transfer pca information using Convert, the result only had umap information.

• 0 views • link
written by ccfpwll • ccfpwll

1 answer

I haven't found a direct way to convert the "spatial" information into a h5ad file (in my case, it was lost when I saved the Seurat object to a .h5seurat file). But you can try to save all the information from the VisiumV1 object manually enter image description here

• 0 views • link
written by Aljes • Aljes

I tried to separately include the "spatial" cooridnates and images into adata.

1) Adding tissue coodinates :

c = scanpy.read_h5ad("p.h5ad")

all = pd.read_csv('spatial.csv', delimiter = ',',index_col=0) # " three Colum data
label imagerow imagecol

0 AAACCGGGTAGGTACC-1_1 261.297067 313.946997

1 AAACCGTTCGTCCAGG-1_1 233.577403 348.256620

2 AAACCTCATGAAGTTG-1_1 279.114362 296.827053

del all[all. columns[0]] # removed barcodes 
all = all.to_numpy()
c.obsm["spatial"] = all

2) Reading image ##

import matplotlib.pyplot as plt

import PIL

import numpy as np

from PIL import Image

source_image_path="tissue_hires_image.png"

im = Image.open(source_image_path)


image = numpy.array(im)

image=image

spatial_key = "spatial"

library_id = "A1"

c.uns[spatial_key] = {library_id: {}}

c.uns[spatial_key][library_id]["images"] = {}

c.uns['spatial'][library_id]['images']['hires'] = image.astype(np.float32)

3) Plotting spatial cluster

sq.pl.spatial_scatter(c, color="integrated_snn_res.0.7")

It shows a image to one side. How can I fix this issue ?

enter image description here

I would appreciate all the suggestion.

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written by Omics data mining Omics data mining

If you got this to work, could you please add this as a tutorial. It's very helpful.

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written by firestar firestar

Hi Aljes, Thanks for the code. If we have 2 images/ slices (integrated object), how could i add these images to anndata? Thanks

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written by Vimala • Vimala

Value passed for key 'spatial' is of incorrect shape. Values of obsm must match dimensions (0,) of parent. Value had shape (14335,) while it should have had (19701,).

• 0 views • link
written by Vimala • Vimala

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