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KeyError: 'umap_cell_embeddings' #16
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Thanks for reporting this bug!
I am CCing the main developers of the tool, I am sure they can help you
with this matter.
…On Mon, Oct 18, 2021 at 2:01 PM kenneditodd ***@***.***> wrote:
I am trying to do singlecellVR starting from a seurat object. I have tried
with my own data and the pbmc example dataset shown. I can convert to .loom
just fine. I get a KeyError: 'umap_cell_embeddings' when i run scvr from my
conda environment.
command: scvr -f seurat3d_10xpbmc.loom -t seurat -a annotations.txt -g
genes.txt -o seurat_report
Standard output is shown below. How do i fix this problem?
- Single cell VR preprocessing -
Version 1.1
Converting 'seurat' analysis result ...
reading in loom file ...
OMP: Info #271: omp_set_nested routine deprecated, please use
omp_set_max_active_levels instead.
Traceback (most recent call last):
File "/Users/m214960/miniconda3/envs/scvr/bin/scvr", line 8, in
sys.exit(main())
File
"/Users/m214960/miniconda3/envs/scvr/lib/python3.9/site-packages/scvr/command_line.py",
line 93, in main
scvr.output_seurat_cells(adata,ann_list,gene_list=gene_list,reportdir=output)
File
"/Users/m214960/miniconda3/envs/scvr/lib/python3.9/site-packages/scvr/converters.py",
line 194, in output_seurat_cells
assert (adata.obsm['umap_cell_embeddings'].shape[1]>=3),
File
"/Users/m214960/miniconda3/envs/scvr/lib/python3.9/site-packages/anndata/_core/aligned_mapping.py",
line 148, in *getitem*
return self._data[key]
KeyError: 'umap_cell_embeddings'
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|
Hi @kenneditodd, sorry you're having trouble with the converter. Currently, I'm not able to reproduce the error you're encountering, as running
|
Hello @davidfstein thanks for the quick reply! Okay I created a new conda environment exactly like you mentioned. Here is the output from conda list.
I have ran this two ways. First, I used all the provided input from the dropbox and I can now replicate that portion. Second, I converted the pbmc seurat object to a loom file myself using the methodology show here.
Here is my R session info
Again when I try to run the scvr command I get this output.
|
Thanks for that info @kenneditodd ! I believe this issue is being caused by changes in the |
Hi @kenneditodd, As mentioned by @davidfstein, this issue is caused by the incompatibility problem when upgrading Seurat 3.x to Seurat 4.0.x. We have resolved the problem now, please take a look at the new Jupiter notebook (https://github.com/qinqian/singlecellvr/blob/master/examples/seurat4_pbmc3k.ipynb), the idea is to use SeuratDisk to export the data into h5ad file. The corresponding scvr API has been updated as well by Best, |
@qinqian @davidfstein I can't get it to work with Seurat 4.x. This was my R chunk.
R output
I created my conda environment like this
Ran this command
This was my error
Are you able to send a yaml file so i can make sure I have the same conda environment? |
We didn't update the scvr on the pypi, could you please Best, |
@qinqian
Let me know if I did anything wrong or misunderstood. |
Please delete scvr in your directory first and then setup the new script. As the |
I am trying to do singlecellVR starting from a seurat object. I have tried with my own data and the pbmc example dataset shown. I can convert to .loom just fine. I get a KeyError: 'umap_cell_embeddings' when i run scvr from my conda environment.
command:
scvr -f seurat3d_10xpbmc.loom -t seurat -a annotations.txt -g genes.txt -o seurat_report
Standard output is shown below. How do i fix this problem?
The text was updated successfully, but these errors were encountered: