Comments (3)
Yes you can use the tool without cell segmentation (you will be able to map and resolve cell types in space but you will not be able to deconvolve).
@ziqlu0722 can you provide us with an example?
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@lewlin
Thanks for the reply!
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Hi @MIAO803, please reference this tutorial for mapping without cell segmentation. The data you need is your sc-RNA, your spatial transcriptomes data and a list of marker genes (In the example, the marker genes is computed following scanpy tutorial.
I'm closing this based on comments above. Feel free to reopen if any further questions.
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Related Issues (20)
- Can we have an API as batch size for the integration method? HOT 3
- No attribute 'pp_adatas' in tangram HOT 2
- Possible to use multiple single cell datasets in Tangram? HOT 3
- Cannot find correspondence of the input data HOT 1
- question about training genes HOT 1
- High mapping score with big KL reg HOT 1
- Recreating Figure 4C from the original publication on the tutorial data
- Question regarding count_cell_annotation HOT 1
- map_cells_to_space "could not determine the shape of object type 'Series'" error HOT 3
- Best practices on 500k+ cells HOT 2
- Error when Installing Tangram on Terra
- deterministic cell-typing of spatial data. HOT 3
- Tangram function cross_val uses deprecated alias function - can be updated? HOT 1
- Filtering low quality genes
- .
- Requirements for the input data HOT 1
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