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Great program so far! We are looking forward to our analysis using AnnoSpat and the spatial module in too-many-cells. I am wondering if it is typical for only one core to be used in the spatial processing? I am running a Docker container of v3.0.1.0 in WSL2 given 50GB of 64GB RAM with an 8 core i7-7700 CPU. The input is ~137,000 cells from CODEX imaging of 23 markers assigned using AnnoSpat:
There are 31 expected cell types and for now each relationship file is taking almost 30min so all combinations will take quite a long time for one sample at this pace. Perhaps there is something I can do to improve?
Thanks!
The text was updated successfully, but these errors were encountered:
Thank you for your interest in our tools! Yes, the speed is not ideal. In my benchmarking I remember the main limiter being based on the sparse matrix library sparse-linear-algebra. I had a branch switching to eigen but at the time that library was missing some necessary functions.
Hello,
Great program so far! We are looking forward to our analysis using AnnoSpat and the spatial module in too-many-cells. I am wondering if it is typical for only one core to be used in the spatial processing? I am running a Docker container of v3.0.1.0 in WSL2 given 50GB of 64GB RAM with an 8 core i7-7700 CPU. The input is ~137,000 cells from CODEX imaging of 23 markers assigned using AnnoSpat:
docker run --memory=55g -v "$HOME:$HOME"
gregoryschwartz/too-many-cells:3.0.1.0 spatial
--matrix-transpose
-z QuantileNorm
-z TfIdfNorm
-m /home/smith6jt/AnnoSpat/measurements.csv
-j /home/smith6jt/AnnoSpat/spatial.csv
-o /home/smith6jt/outputdir/full_marker/tmc
-l /home/smith6jt/outputdir/full_marker/trte_labels_ELM_spleen.csv
--mark "ALL"
There are 31 expected cell types and for now each relationship file is taking almost 30min so all combinations will take quite a long time for one sample at this pace. Perhaps there is something I can do to improve?
Thanks!
The text was updated successfully, but these errors were encountered: