sdata object has no cellpose or baysor boundaries #64
Comments
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Hello @altunbulakli, Indeed Sopa should run baysor, but in your case it seems it didn't. Can you show me the full log? You should have a text file called |
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Hey Quentin, Thank you very much for your help! 1 |
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Actually, it looks as expected (it just a list of patches IDs). Each ID corresponds to the name of a directory inside Also, have you tried the toy example? Do you have the same issue? |
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Sorry for the late reply. I wanted to make sure that Baysor was installed correctly and Cellpose was working outside of the Snakemake pipeline: However, both the Baysor only config, Cellpose only config and the Toy Example command give a similar error: (sopa) C:\Users\altun\Documents\sopa\workflow>snakemake --config sdata_path=tuto.zarr --configfile=config/toy/uniform_cellpose.yaml --cores 1 --use-conda aggregate 1 Select jobs to execute... [Thu May 30 11:52:45 2024] Activating conda environment: sopa [Thu May 30 11:52:55 2024] Activating conda environment: sopa [Thu May 30 11:53:01 2024] Activating conda environment: sopa |
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And here are my logs for a Baysor only config file snakemake run: (sopa) C:\Users\altun\Documents\sopa\workflow>snakemake --config data_path=C:/Users/altun/Desktop/Xenium_analysis_May_2024/xenium_run/TC_070 --configfile=config/xenium/baysor_new.yaml --cores 1 --use-conda aggregate 1 Select jobs to execute... [Thu May 30 11:57:56 2024] Activating conda environment: sopa [Thu May 30 11:58:49 2024] Activating conda environment: sopa [Thu May 30 11:59:12 2024] Activating conda environment: sopa |
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At the end of this run, we have a C:\Users\altun\Desktop\Xenium_analysis_May_2024\xenium_run\TC_070.zarr.sopa_cache\baysor_boundaries Here is one of the folder's contents |
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Weirdly enough, it seems that snakemake uses an incorrect path. Indeed, in your logs I see I don't understand why this happens, and all the other paths look correct, for instance Just to make sure this is related to Snakemake, can you try to use the CLI as in this tutorial? |
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Yes! I was able to follow the CLI tutorial, and it seems to segment the cells, resolve them and aggregate them successfully. So it seems like the Snakemake pipeline that i have (I didnt modify the Snakefile so far) seems to have an error. (sopa) C:\Users\altun\Documents\sopa\workflow>sopa read . --sdata-path tuto.zarr --technology uniform (sopa) C:\Users\altun\Documents\sopa\workflow>sopa patchify image tuto.zarr --patch-width-pixel 1500 --patch-overlap-pixel 50 (sopa) C:\Users\altun\Documents\sopa\workflow>sopa segmentation cellpose tuto.zarr --channels DAPI --diameter 35 --min-area 2000 --patch-index 0 (sopa) C:\Users\altun\Documents\sopa\workflow>sopa segmentation cellpose tuto.zarr --channels DAPI --diameter 35 --min-area 2000 --patch-index 1 (sopa) C:\Users\altun\Documents\sopa\workflow>sopa segmentation cellpose tuto.zarr --channels DAPI --diameter 35 --min-area 2000 --patch-index 2 (sopa) C:\Users\altun\Documents\sopa\workflow>sopa segmentation cellpose tuto.zarr --channels DAPI --diameter 35 --min-area 2000 --patch-index 3 (sopa) C:\Users\altun\Documents\sopa\workflow>sopa resolve cellpose tuto.zarr (sopa) C:\Users\altun\Documents\sopa\workflow>sopa aggregate tuto.zarr --gene-column genes --average-intensities --min-transcripts 10 (sopa) C:\Users\altun\Documents\sopa\workflow>sopa report tuto.zarr report.html (sopa) C:\Users\altun\Documents\sopa\workflow>sopa explorer write tuto.zarr --gene-column genes |
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Good to hear that the CLI works. Same for the report, I just changed the file encoding, should be fixed in the next release of sopa. I will let you know when it's released! |
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I just released |
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Dear @quentinblampey and @altunbulakli, I am receiving a similar error while trying to process a subset dataset. Details: It loads the image, but at checkpoint patchify_cellpose it fails claiming that The snakefile remains unchanged from sopa repo. Happy to provide more details if needed :) config.yamlStackTrace(snakemake) C:\Users\jnimoca\Desktop\SOPA\sopa>snakemake --config data_path="C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.tif" --configfile="C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\ometif.yaml" --cores 10 --use-conda
SpatialData object path set to default: C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr
To change this behavior, provide `--config sdata_path=...` when running the snakemake pipeline
Building DAG of jobs...
Provided cores: 10
Rules claiming more threads will be scaled down.
Job stats:
job count
----------------- -------
aggregate 1
all 1
explorer 1
image_write 1
patchify_cellpose 1
report 1
resolve_cellpose 1
to_spatialdata 1
total 8
Select jobs to execute...
[Thu Jul 25 15:05:35 2024]
rule to_spatialdata:
input: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.tif
output: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.zarr/.zgroup
jobid: 4
reason: Missing output files: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.zarr/.zgroup
resources: tmpdir=C:\Users\jnimoca\AppData\Local\Temp\4, mem_mb=128000, mem_mib=122071
Activating conda environment: sopa
[WARNING] (sopa.io.standardize) No transcripts found. Some tools from sopa will not be available.
[INFO] (sopa.io.standardize) Writing the following spatialdata object to C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr:
SpatialData object
└── Images
└── 'image': DataTree[cyx] (15, 8000, 8000), (15, 4000, 4000), (15, 2000, 2000), (15, 1000, 1000), (15, 500, 500)
with coordinate systems:
▸ 'global', with elements:
image (Images)
INFO The Zarr backing store has been changed from None the new file path: C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr
[Thu Jul 25 15:07:44 2024]
Finished job 4.
1 of 8 steps (12%) done
Select jobs to execute...
[Thu Jul 25 15:07:44 2024]
rule image_write:
input: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.zarr/.zgroup
output: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.explorer/morphology.ome.tif
jobid: 6
reason: Missing output files: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.explorer/morphology.ome.tif; Input files updated by another job: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.zarr/.zgroup
resources: tmpdir=C:\Users\jnimoca\AppData\Local\Temp\4, mem_mb=64000, mem_mib=61036, partition=longq
Activating conda environment: sopa
[Thu Jul 25 15:07:44 2024]
checkpoint patchify_cellpose:
input: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.zarr/.zgroup
output: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.zarr/.sopa_cache/patches_file_image, C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.zarr/.sopa_cache/patches
jobid: 3
reason: Missing output files: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.zarr/.sopa_cache/patches_file_image; Input files updated by another job: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.zarr/.zgroup
resources: tmpdir=C:\Users\jnimoca\AppData\Local\Temp\4
DAG of jobs will be updated after completion.
Activating conda environment: sopa
[WARNING] (sopa._sdata) sdata object has no valid segmentation boundary. Consider running Sopa segmentation first.
[INFO] (sopa.patches.patches) 25 patches were saved in sdata['sopa_patches']
[INFO] (sopa.io.explorer.images) Writing multiscale image with procedure=semi-lazy (load in memory when possible)
[INFO] (sopa.io.explorer.images) (Loading image of shape (15, 8000, 8000)) in memory
Touching output file C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.zarr/.sopa_cache/patches.
[Thu Jul 25 15:07:56 2024]
Finished job 3.
2 of 8 steps (25%) done
MissingInputException in rule resolve_cellpose in file C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\Snakefile, line 154:
Missing input files for rule resolve_cellpose:
output: C:/Users/jnimoca/Desktop/SOPA/sopa/workflow/data/991_subset.ome.zarr/.sopa_cache/cellpose_boundaries_done
affected files:
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\10.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\15.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\22.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\20.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\6.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\19.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\8.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\16.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\13.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\24.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\0.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\14.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\3.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\21.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\18.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\1.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\2.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\11.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\9.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\4.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\5.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\23.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\12.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\7.parquet
C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.zarr\.sopa_cache\cellpose_boundaries\17.parquet
[INFO] (sopa.io.explorer.images) > Image of shape (15, 8000, 8000)
[INFO] (sopa.io.explorer.images) > Image of shape (15, 4000, 4000)
[INFO] (sopa.io.explorer.images) > Image of shape (15, 2000, 2000)
[INFO] (sopa.io.explorer.images) > Image of shape (15, 1000, 1000)
[INFO] (sopa.io.explorer.images) > Image of shape (15, 500, 500)
[INFO] (sopa.io.explorer.images) > Image of shape (15, 250, 250)
[INFO] (sopa.io.explorer.converter) Saved files in the following directory: C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.explorer
[INFO] (sopa.io.explorer.converter) You can open the experiment with 'open C:\Users\jnimoca\Desktop\SOPA\sopa\workflow\data\991_subset.ome.explorer\experiment.xenium'sopa mamba list(sopa) C:\Users\jnimoca\Desktop\SOPA\sopa>mamba list
# packages in environment at C:\Users\jnimoca\AppData\Local\miniforge3\envs\sopa:
#
# Name Version Build Channel
aicsimageio 4.14.0 pypi_0 pypi
aiobotocore 2.11.2 pypi_0 pypi
aiohttp 3.9.5 pypi_0 pypi
aioitertools 0.11.0 pypi_0 pypi
aiosignal 1.3.1 pypi_0 pypi
anndata 0.10.8 pypi_0 pypi
annotated-types 0.7.0 pypi_0 pypi
array-api-compat 1.7.1 pypi_0 pypi
asciitree 0.3.3 pypi_0 pypi
async-timeout 4.0.3 pypi_0 pypi
attrs 23.2.0 pypi_0 pypi
botocore 1.34.19 pypi_0 pypi
bzip2 1.0.8 h2466b09_7 conda-forge
ca-certificates 2024.7.4 h56e8100_0 conda-forge
cellpose 3.0.10 pypi_0 pypi
certifi 2024.7.4 pypi_0 pypi
charset-normalizer 3.3.2 pypi_0 pypi
click 8.1.7 pypi_0 pypi
cloudpickle 3.0.0 pypi_0 pypi
colorama 0.4.6 pypi_0 pypi
colorcet 3.1.0 pypi_0 pypi
contourpy 1.2.1 pypi_0 pypi
cycler 0.12.1 pypi_0 pypi
dask 2024.7.1 pypi_0 pypi
dask-expr 1.1.9 pypi_0 pypi
dask-image 2024.5.3 pypi_0 pypi
datashader 0.16.3 pypi_0 pypi
distributed 2024.7.1 pypi_0 pypi
elementpath 4.4.0 pypi_0 pypi
exceptiongroup 1.2.2 pypi_0 pypi
fasteners 0.19 pypi_0 pypi
fastremap 1.15.0 pypi_0 pypi
fcsparser 0.2.8 pypi_0 pypi
filelock 3.15.4 pypi_0 pypi
flake8 7.1.0 pypi_0 pypi
fonttools 4.53.1 pypi_0 pypi
frozenlist 1.4.1 pypi_0 pypi
fsspec 2023.6.0 pypi_0 pypi
geopandas 1.0.1 pypi_0 pypi
h5py 3.11.0 pypi_0 pypi
idna 3.7 pypi_0 pypi
imagecodecs 2024.6.1 pypi_0 pypi
imageio 2.34.2 pypi_0 pypi
importlib-metadata 8.0.0 pypi_0 pypi
intel-openmp 2021.4.0 pypi_0 pypi
jinja2 3.1.4 pypi_0 pypi
jmespath 1.0.1 pypi_0 pypi
joblib 1.4.2 pypi_0 pypi
kiwisolver 1.4.5 pypi_0 pypi
lamin-utils 0.13.2 pypi_0 pypi
lazy-loader 0.4 pypi_0 pypi
legacy-api-wrap 1.4 pypi_0 pypi
libffi 3.4.2 h8ffe710_5 conda-forge
libsqlite 3.46.0 h2466b09_0 conda-forge
libzlib 1.3.1 h2466b09_1 conda-forge
llvmlite 0.43.0 pypi_0 pypi
locket 1.0.0 pypi_0 pypi
lxml 4.9.4 pypi_0 pypi
markdown-it-py 3.0.0 pypi_0 pypi
markupsafe 2.1.5 pypi_0 pypi
matplotlib 3.9.1 pypi_0 pypi
mccabe 0.7.0 pypi_0 pypi
mdurl 0.1.2 pypi_0 pypi
mkl 2021.4.0 pypi_0 pypi
mpmath 1.3.0 pypi_0 pypi
msgpack 1.0.8 pypi_0 pypi
multidict 6.0.5 pypi_0 pypi
multipledispatch 1.0.0 pypi_0 pypi
multiscale-spatial-image 1.0.0 pypi_0 pypi
natsort 8.4.0 pypi_0 pypi
networkx 3.3 pypi_0 pypi
numba 0.60.0 pypi_0 pypi
numcodecs 0.13.0 pypi_0 pypi
numpy 1.26.4 pypi_0 pypi
ome-types 0.5.1.post1 pypi_0 pypi
ome-zarr 0.9.0 pypi_0 pypi
opencv-python 4.10.0.84 pypi_0 pypi
opencv-python-headless 4.10.0.84 pypi_0 pypi
openssl 3.3.1 h2466b09_2 conda-forge
packaging 24.1 pypi_0 pypi
pandas 2.2.2 pypi_0 pypi
param 2.1.1 pypi_0 pypi
partd 1.4.2 pypi_0 pypi
patsy 0.5.6 pypi_0 pypi
pillow 10.4.0 pypi_0 pypi
pims 0.7 pypi_0 pypi
pip 24.0 pyhd8ed1ab_0 conda-forge
platformdirs 4.2.2 pypi_0 pypi
pooch 1.8.2 pypi_0 pypi
psutil 6.0.0 pypi_0 pypi
pyarrow 17.0.0 pypi_0 pypi
pycodestyle 2.12.0 pypi_0 pypi
pyct 0.5.0 pypi_0 pypi
pydantic 2.8.2 pypi_0 pypi
pydantic-compat 0.1.2 pypi_0 pypi
pydantic-core 2.20.1 pypi_0 pypi
pyflakes 3.2.0 pypi_0 pypi
pygments 2.18.0 pypi_0 pypi
pynndescent 0.5.13 pypi_0 pypi
pyogrio 0.9.0 pypi_0 pypi
pyparsing 3.1.2 pypi_0 pypi
pyproj 3.6.1 pypi_0 pypi
python 3.10.0 hcf16a7b_3_cpython conda-forge
python-dateutil 2.9.0.post0 pypi_0 pypi
pytz 2024.1 pypi_0 pypi
pyyaml 6.0.1 pypi_0 pypi
readfcs 1.1.8 pypi_0 pypi
requests 2.32.3 pypi_0 pypi
resource-backed-dask-array 0.1.0 pypi_0 pypi
rich 13.7.1 pypi_0 pypi
roifile 2024.5.24 pypi_0 pypi
s3fs 0.6.0 pypi_0 pypi
scanpy 1.10.2 pypi_0 pypi
scikit-image 0.24.0 pypi_0 pypi
scikit-learn 1.5.1 pypi_0 pypi
scipy 1.14.0 pypi_0 pypi
seaborn 0.13.2 pypi_0 pypi
session-info 1.0.0 pypi_0 pypi
setuptools 71.0.4 pyhd8ed1ab_0 conda-forge
shapely 2.0.5 pypi_0 pypi
shellingham 1.5.4 pypi_0 pypi
six 1.16.0 pypi_0 pypi
slicerator 1.1.0 pypi_0 pypi
sopa 1.1.1 pypi_0 pypi
sortedcontainers 2.4.0 pypi_0 pypi
spatial-image 1.1.0 pypi_0 pypi
spatialdata 0.2.1 pypi_0 pypi
spatialdata-io 0.1.3.post0 pypi_0 pypi
sqlite 3.46.0 h2466b09_0 conda-forge
statsmodels 0.14.2 pypi_0 pypi
stdlib-list 0.10.0 pypi_0 pypi
sympy 1.13.1 pypi_0 pypi
tbb 2021.13.0 pypi_0 pypi
tblib 3.0.0 pypi_0 pypi
threadpoolctl 3.5.0 pypi_0 pypi
tifffile 2023.2.28 pypi_0 pypi
tk 8.6.13 h5226925_1 conda-forge
toolz 0.12.1 pypi_0 pypi
torch 2.3.1 pypi_0 pypi
tornado 6.4.1 pypi_0 pypi
tqdm 4.66.4 pypi_0 pypi
typer 0.12.3 pypi_0 pypi
typing-extensions 4.12.2 pypi_0 pypi
tzdata 2024.1 pypi_0 pypi
ucrt 10.0.22621.0 h57928b3_0 conda-forge
umap-learn 0.5.6 pypi_0 pypi
urllib3 2.0.7 pypi_0 pypi
vc 14.3 h8a93ad2_20 conda-forge
vc14_runtime 14.40.33810 ha82c5b3_20 conda-forge
vs2015_runtime 14.40.33810 h3bf8584_20 conda-forge
wheel 0.43.0 pyhd8ed1ab_1 conda-forge
wrapt 1.16.0 pypi_0 pypi
xarray 2024.6.0 pypi_0 pypi
xarray-dataclasses 1.8.0 pypi_0 pypi
xarray-datatree 0.0.14 pypi_0 pypi
xarray-schema 0.0.3 pypi_0 pypi
xarray-spatial 0.4.0 pypi_0 pypi
xmlschema 3.3.1 pypi_0 pypi
xsdata 24.3.1 pypi_0 pypi
xz 5.2.6 h8d14728_0 conda-forge
yarl 1.9.4 pypi_0 pypi
zarr 2.15.0 pypi_0 pypi
zict 3.0.0 pypi_0 pypi
zipp 3.19.2 pypi_0 pypisnakemake mamba list(snakemake) C:\Users\jnimoca\Desktop\SOPA\sopa>mamba list
# packages in environment at C:\Users\jnimoca\AppData\Local\miniforge3\envs\snakemake:
#
# Name Version Build Channel
aioeasywebdav 2.4.0 pyha770c72_0 conda-forge
aiohttp 3.9.5 py310h8d17308_0 conda-forge
aiosignal 1.3.1 pyhd8ed1ab_0 conda-forge
amply 0.1.6 pyhd8ed1ab_0 conda-forge
appdirs 1.4.4 pyh9f0ad1d_0 conda-forge
async-timeout 4.0.3 pyhd8ed1ab_0 conda-forge
attmap 0.13.2 pyhd8ed1ab_0 conda-forge
attrs 23.2.0 pyh71513ae_0 conda-forge
bcrypt 4.2.0 py310hc226416_0 conda-forge
boto3 1.34.148 pyhd8ed1ab_0 conda-forge
botocore 1.34.148 pyge310_1234567_0 conda-forge
brotli-python 1.1.0 py310h00ffb61_1 conda-forge
bzip2 1.0.8 h2466b09_7 conda-forge
c-ares 1.32.3 h2466b09_0 conda-forge
ca-certificates 2024.7.4 h56e8100_0 conda-forge
cachetools 5.4.0 pyhd8ed1ab_0 conda-forge
certifi 2024.7.4 pyhd8ed1ab_0 conda-forge
cffi 1.16.0 py310h8d17308_0 conda-forge
charset-normalizer 3.3.2 pyhd8ed1ab_0 conda-forge
colorama 0.4.6 pyhd8ed1ab_0 conda-forge
configargparse 1.7 pyhd8ed1ab_0 conda-forge
connection_pool 0.0.3 pyhd3deb0d_0 conda-forge
cryptography 42.0.8 py310h25a5809_0 conda-forge
datrie 0.8.2 py310h8d17308_7 conda-forge
defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge
docutils 0.21.2 pyhd8ed1ab_0 conda-forge
dpath 2.2.0 pyha770c72_0 conda-forge
dropbox 12.0.2 pyhd8ed1ab_0 conda-forge
eido 0.2.2 pyhd8ed1ab_0 conda-forge
exceptiongroup 1.2.2 pyhd8ed1ab_0 conda-forge
filechunkio 1.8 py_2 conda-forge
frozenlist 1.4.1 py310h8d17308_0 conda-forge
ftputil 5.1.0 pyhd8ed1ab_0 conda-forge
gitdb 4.0.11 pyhd8ed1ab_0 conda-forge
gitpython 3.1.43 pyhd8ed1ab_0 conda-forge
glpk 5.0 h8ffe710_0 conda-forge
google-api-core 2.19.1 pyhd8ed1ab_0 conda-forge
google-api-python-client 2.137.0 pyhd8ed1ab_0 conda-forge
google-auth 2.32.0 pyhff2d567_0 conda-forge
google-auth-httplib2 0.2.0 pyhd8ed1ab_0 conda-forge
google-cloud-core 2.4.1 pyhd8ed1ab_0 conda-forge
google-cloud-storage 2.18.0 pyhff2d567_0 conda-forge
google-crc32c 1.1.2 py310ha7be474_5 conda-forge
google-resumable-media 2.7.0 pyhd8ed1ab_0 conda-forge
googleapis-common-protos 1.63.2 pyhd8ed1ab_0 conda-forge
grpcio 1.62.2 py310hb84602e_0 conda-forge
h2 4.1.0 pyhd8ed1ab_0 conda-forge
hpack 4.0.0 pyh9f0ad1d_0 conda-forge
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humanfriendly 10.0 py310h5588dad_5 conda-forge
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iniconfig 2.0.0 pyhd8ed1ab_0 conda-forge
intel-openmp 2024.2.0 h57928b3_980 conda-forge
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jmespath 1.0.1 pyhd8ed1ab_0 conda-forge
jsonschema 4.23.0 pyhd8ed1ab_0 conda-forge
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libabseil 20240116.2 cxx17_he0c23c2_1 conda-forge
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libprotobuf 4.25.3 h503648d_0 conda-forge
libre2-11 2023.09.01 hf8d8778_2 conda-forge
libsqlite 3.46.0 h2466b09_0 conda-forge
libxml2 2.12.7 h0f24e4e_4 conda-forge
libzlib 1.3.1 h2466b09_1 conda-forge
logmuse 0.2.6 pyh8c360ce_0 conda-forge
markdown-it-py 3.0.0 pyhd8ed1ab_0 conda-forge
markupsafe 2.1.5 py310h8d17308_0 conda-forge
mdurl 0.1.2 pyhd8ed1ab_0 conda-forge
mkl 2024.1.0 h66d3029_694 conda-forge
multidict 6.0.5 py310h8d17308_0 conda-forge
nbformat 5.10.4 pyhd8ed1ab_0 conda-forge
numpy 2.0.0 py310h1ec8c79_0 conda-forge
oauth2client 4.1.3 py_0 conda-forge
openssl 3.3.1 h2466b09_2 conda-forge
packaging 24.1 pyhd8ed1ab_0 conda-forge
pandas 2.2.2 py310hb4db72f_1 conda-forge
paramiko 3.4.0 pyhd8ed1ab_0 conda-forge
peppy 0.40.4 pyhd8ed1ab_0 conda-forge
pip 24.0 pyhd8ed1ab_0 conda-forge
pkgutil-resolve-name 1.3.10 pyhd8ed1ab_1 conda-forge
plac 1.4.3 pyhd8ed1ab_0 conda-forge
platformdirs 4.2.2 pyhd8ed1ab_0 conda-forge
pluggy 1.5.0 pyhd8ed1ab_0 conda-forge
ply 3.11 pyhd8ed1ab_2 conda-forge
prettytable 3.10.2 pyhd8ed1ab_0 conda-forge
proto-plus 1.23.0 pyhd8ed1ab_0 conda-forge
protobuf 4.25.3 py310hf536535_0 conda-forge
psutil 6.0.0 py310ha8f682b_0 conda-forge
pthreads-win32 2.9.1 hfa6e2cd_3 conda-forge
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pycparser 2.22 pyhd8ed1ab_0 conda-forge
pygments 2.18.0 pyhd8ed1ab_0 conda-forge
pynacl 1.5.0 py310h635b8f1_3 conda-forge
pyopenssl 24.2.1 pyhd8ed1ab_0 conda-forge
pyparsing 3.1.2 pyhd8ed1ab_0 conda-forge
pyreadline3 3.4.1 py310h5588dad_3 conda-forge
pysftp 0.2.9 py_1 conda-forge
pysocks 1.7.1 pyh0701188_6 conda-forge
pytest 8.3.1 pyhd8ed1ab_0 conda-forge
python 3.10.0 hcf16a7b_3_cpython conda-forge
python-dateutil 2.9.0 pyhd8ed1ab_0 conda-forge
python-fastjsonschema 2.20.0 pyhd8ed1ab_0 conda-forge
python-irodsclient 2.0.1 pyhd8ed1ab_0 conda-forge
python-tzdata 2024.1 pyhd8ed1ab_0 conda-forge
python_abi 3.10 4_cp310 conda-forge
pytz 2024.1 pyhd8ed1ab_0 conda-forge
pyu2f 0.1.5 pyhd8ed1ab_0 conda-forge
pywin32 306 py310h00ffb61_2 conda-forge
pyyaml 6.0.1 py310h8d17308_1 conda-forge
re2 2023.09.01 hd3b24a8_2 conda-forge
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requests 2.32.3 pyhd8ed1ab_0 conda-forge
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rich 13.7.1 pyhd8ed1ab_0 conda-forge
rpds-py 0.19.1 py310hc226416_0 conda-forge
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six 1.16.0 pyh6c4a22f_0 conda-forge
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smmap 5.0.0 pyhd8ed1ab_0 conda-forge
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sqlite 3.46.0 h2466b09_0 conda-forge
stone 3.3.2 pyhd8ed1ab_0 conda-forge
stopit 1.1.2 py_0 conda-forge
tabulate 0.9.0 pyhd8ed1ab_1 conda-forge
tbb 2021.12.0 hc790b64_3 conda-forge
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tomli 2.0.1 pyhd8ed1ab_0 conda-forge
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typing_extensions 4.12.2 pyha770c72_0 conda-forge
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vc 14.3 h8a93ad2_20 conda-forge
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veracitools 0.1.3 py_0 conda-forge
vs2015_runtime 14.40.33810 h3bf8584_20 conda-forge
wcwidth 0.2.13 pyhd8ed1ab_0 conda-forge
wheel 0.43.0 pyhd8ed1ab_1 conda-forge
win_inet_pton 1.1.0 pyhd8ed1ab_6 conda-forge
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xz 5.2.6 h8d14728_0 conda-forge
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zipp 3.19.2 pyhd8ed1ab_0 conda-forge
zstandard 0.23.0 py310he5e10e1_0 conda-forge
zstd 1.5.6 h0ea2cb4_0 conda-forge |
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Hello @josenimo, Can you check if the "missing" files are really missing? If the file exists, then snakemake is not detecting it for some reasons. I suspect it has something to do with how paths are handled in Windows. Two questions to check if my assumptions are correct:
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Hey @quentinblampey , Update:
Happy to provide more details to help solve Windows issues. |
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Ok thanks for the details. I think it's an issue related to snakemake, which doesn't trigger the rules that create the input needed for the When I have access to a windows laptop (i.e. not before late august), I'll check this and try to solve this! Meanwhile, the CLI and the API should work fine on windows :) |
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snakemake version 7.32.4 |
Hello to the SOPA creators.
I am quite a beginner to Python and the Command Line Interface. I have attempted to run the Ready made Snakemake pipeline for Xenium data (with the Baysor cell segmentation feature)
However, i get the following warning and the error in the resolve_baysor section of the pipeline:
[WARNING] (sopa._sdata) sdata object has no cellpose boundaries and no baysor boundaries. Consider running segmentation first.
and the error:
Finished job 3.
3 of 8 steps (38%) done
MissingInputException in rule resolve_baysor in file C:\Windows\System32\sopa\workflow\Snakefile, line 125:
Missing input files for rule resolve_baysor:
output: C:/xenium_run/TC_070.zarr/.sopa_cache/baysor_boundaries_done, C:/xenium_run/TC_070.zarr/.sopa_cache/table
affected files:
I was thinking that the Snakemake pipeline would run Baysor segmentation automatically.
I also get a similar error when i try a Cellpose only config file or a Baysor.only config file.
What could be the solution here? I have installed both the cellpose package (as part of the sopa installation) and the Baysor package according to their instructions.
Thank you very much for your help :)
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