Firstly, how to generate Seurat object?

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object <- CreateSeuratObject(counts=simSRT1@simCounts,assay="Spatial")
object@images$image <- new(Class="SlideSeq",assay="Spatial",key="image_",
coordinates=as.data.frame(as.matrix(simSRT1@simcolData)))
object@images$image@coordinates$x <- as.numeric(object@images$image@coordinates$x)
object@images$image@coordinates$y <- as.numeric(object@images$image@coordinates$y)

Also, Seurat has offered convenient argument to generate seurat object?

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expression <- Read10X(data.dir = datadir)
object <- CreateSeuratObject(counts = expression)

Secondly, how to create Scanpy object?

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counts="/pathowh01/disk1/liqian/01deconvolution/05SRTsim/00data/01.SRTsim_counts.csv"
location="/pathowh01/disk1/liqian/01deconvolution/05SRTsim/00data/01.SRTsim_position.csv"
df = pd.read_csv(counts,sep="\t",index_col=0)
obs = pd.DataFrame(index=df.columns)
obs['sample'] = df.columns
var_names = df.index
var = pd.DataFrame(index=var_names)
var["gene_ids"] = var.index
X = df.T.values
adata = anndata.AnnData(X, obs=obs, var=var,dtype='int32')
adata.var_names_make_unique() 
loc = pd.read_csv(location,sep="\t",index_col=0)
adata.obs["group"] = loc["group"]
adata.obs["foldchange"] = loc["foldchange"]
adata.obsm["spatial"] = loc[["x","y"]].to_numpy()
adata
adata.write("/pathowh01/disk1/liqian/01deconvolution/05SRTsim/00data/01.SRTsim.h5ad")

This code is a little boring as Scanpy has offered different kinds of arguments to finish the process of constructing anndata object.

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adata = sc.read_10x_mtx(datafolder)

If we would like to create ST object based on Scanpy, this is the code:

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adata = sc.read_visium(datafolder, count_file=h5)

And we should offer files like this :

Reference