QuKunLab / SpatialBenchmarking

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Ground truth of dataset4 in Figure4 #11

Closed lzygenomics closed 2 years ago

lzygenomics commented 2 years ago

Hi~ @wenruyustc

Thanks for your fancy work ! When I was processing the dataset4, I found that the annotation of scRNA-seq is unpaired with the annotation of spot clusters, so I could not calculate the measurement results~Would you mind sharing your specific alignment method ?

Best, Zhiyuan Liu

wenruyustc commented 2 years ago

Hi~, if you are using Dataset 4 as an example, you can use BLAST_CelltypeDeconvolution.ipynb to simulate the spot and follow BLAST_CelltypeDeconvolution.ipynb to calculate the measurement results

lzygenomics commented 2 years ago

Hi~, if you are using Dataset 4 as an example, you can use BLAST_CelltypeDeconvolution.ipynb to simulate the spot and follow BLAST_CelltypeDeconvolution.ipynb to calculate the measurement results

Thank you very much for your prompt reply! Maybe I didn't make it clear that Dataset 4 I said here refers to the dataset formed by drawing the grid, not the dataset4 in the simulation sets~ It seems that the script "BLAST_CelltypeDeconvolution.ipynb" didn't contain the information about Dataset 4's evaluation~

Thanks again~ Best

wenruyustc commented 2 years ago

Sorry for misunderstanding. In fact, we only used 8 paired cell clusters (Astro, Endo,ExcitatoryL2and3,ExcitatoryL4,ExcitatoryL5and6,Inhibitory,Micro ,Olig) to evaluate the evaluation prediction result. And other cell types, such as Ependymal or Neuroblast, are exclude from the evaluation.

lzygenomics commented 2 years ago

Ok~Thanks for your help!