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ZJUFanLab / bulk2space

a spatial deconvolution method based on deep learning frameworks, which converts bulk transcriptomes into spatially resolved single-cell expression profiles
GNU General Public License v3.0
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Question: Scalability #12

Open ccruizm opened 1 year ago

ccruizm commented 1 year ago

Good day,

I am eager to test this excellent tool on our data. I have seen in the tutorial and demo data that the vignette uses only one bulk RNA sample as well as an ST experiment.

Is it possible to scale up and process several bulk RNA samples and ST experiments in one go? and for the inferred single-cell data derived from the bulk, can we have those integrated across multiple biological replicates, as if they were truly scRNA-seq data?

Thanks in advance!

SpaTrek commented 1 year ago

Very good question! I believe the scalability or batch function could be a potential value of Bulk2Space. We encourage experts from all over the world to use the tool, contribute to its spread, and create branches to achieve more functions. Your request is more like a branch of the Bulk2Space, such as Bulk2SpaceBatch. If you are interested, you can try to accelerate the calculation speed, add more useful functions, and fit in customized senceniors by making a branch of Bulk2Space. For us, first, the algorithm is not so fast when the SC or ST references is big. Second, the parameters need to be adjusted accordingly in each use. Thus, we don't want to scale up the process currently.

ccruizm commented 1 year ago

Thanks for your reply! I will try it and let you know about any solution I come up with!

I read in previous questions (https://github.com/ZJUFanLab/bulk2space/issues/1) that we could use the tools without any ST data. However, when I looked at the tutorial handbook to decompose bulk transcriptomics data into single-cell transcriptomics data, it still required adding input_st_data_path and input_st_meta_path. I tried leaving those arguments empty, but it gave an error. What is the correct way to deconvolve bulk RNA data into single-cell without ST information?

Appreciate your help!

xiang-cy commented 1 year ago

Thanks for your reply! I will try it and let you know about any solution I come up with!

I read in previous questions (#1) that we could use the tools without any ST data. However, when I looked at the tutorial handbook to decompose bulk transcriptomics data into single-cell transcriptomics data, it still required adding input_st_data_path and input_st_meta_path. I tried leaving those arguments empty, but it gave an error. What is the correct way to deconvolve bulk RNA data into single-cell without ST information?

Appreciate your help!

hello, I met the same problem as u u solve it now and can u share any solution with me? Appreciate your reply.

ajandria commented 9 months ago

Bumping this as still unresolved yet declared as possible