CellProfiler is a free open-source software designed to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically.
Allocate an interactive session and run the program. Sample session:
[user@biowulf ~]$ sinteractive -c2 --mem=4g --gres=lscratch:10
salloc.exe: Pending job allocation 11258266
salloc.exe: job 11258266 queued and waiting for resources
salloc.exe: job 11258266 has been allocated resources
salloc.exe: Granted job allocation 11258266
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn0884 are ready for job
srun: error: x11: no local DISPLAY defined, skipping
error: unable to open file /tmp/slurm-spank-x11.11258266.0
slurmstepd: error: x11: unable to read DISPLAY value
[user@cn0884 ~]$ cd /lscratch/$SLURM_JOB_ID
[user@cn0884 11258266]$ module load cellprofiler
[+] Loading cellprofiler 3.1.8 ...
[user@cn0884 11258266]$ cp ${CELLPROFILER_TESTDATA}/* .
[user@cn0884 11258266]$ unzip ExampleHuman.zip
Archive: ExampleHuman.zip
creating: ExampleHuman/
inflating: ExampleHuman/ExampleHuman.cppipe
creating: __MACOSX/
creating: __MACOSX/ExampleHuman/
inflating: __MACOSX/ExampleHuman/._ExampleHuman.cppipe
creating: ExampleHuman/images/
inflating: ExampleHuman/images/AS_09125_050116030001_D03f00d0.tif
creating: __MACOSX/ExampleHuman/images/
inflating: __MACOSX/ExampleHuman/images/._AS_09125_050116030001_D03f00d0.tif
inflating: ExampleHuman/images/AS_09125_050116030001_D03f00d1.tif
inflating: __MACOSX/ExampleHuman/images/._AS_09125_050116030001_D03f00d1.tif
inflating: ExampleHuman/images/AS_09125_050116030001_D03f00d2.tif
inflating: __MACOSX/ExampleHuman/images/._AS_09125_050116030001_D03f00d2.tif
inflating: __MACOSX/ExampleHuman/._images
inflating: ExampleHuman/README.md
inflating: __MACOSX/ExampleHuman/._README.md
inflating: __MACOSX/._ExampleHuman
[user@cn0884 11258266]$ cd ExampleHuman/
[user@cn0884 ExampleHuman]$ cellprofiler -p ExampleHuman.cppipe -c -r -i images/
/usr/local/Anaconda/envs_app/cellprofiler/3.1.8/lib/python2.7/site-packages/cellprofiler/utilities/hdf5_dict.py:539: FutureWarning: Conversion of the second argument of issubdtype from `int` to `np.signedinteger` is deprecated. In future, it will be treated as `np.int64 == np.dtype(int).type`.
np.issubdtype(hdf5_type, int) or
/usr/local/Anaconda/envs_app/cellprofiler/3.1.8/lib/python2.7/site-packages/cellprofiler/utilities/hdf5_dict.py:541: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
hdf5_type_is_float = np.issubdtype(hdf5_type, float)
Times reported are CPU and Wall-clock times for each module
Wed Mar 24 13:33:33 2021: Image # 1, module Images # 1: CPU_time = 0.00 secs, Wall_time = 0.00 secs
Wed Mar 24 13:33:33 2021: Image # 1, module Metadata # 2: CPU_time = 0.00 secs, Wall_time = 0.00 secs
Wed Mar 24 13:33:33 2021: Image # 1, module NamesAndTypes # 3: CPU_time = 1.87 secs, Wall_time = 0.97 secs
Wed Mar 24 13:33:34 2021: Image # 1, module Groups # 4: CPU_time = 0.00 secs, Wall_time = 0.00 secs
/usr/local/Anaconda/envs_app/cellprofiler/3.1.8/lib/python2.7/site-packages/centrosome/cpmorphology.py:4209: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
big_labels[[slice(fe,-fe) for fe in footprint_extent]] = labels
[...snip]
Wed Mar 24 13:33:41 2021: Image # 1, module SaveImages # 13: CPU_time = 0.35 secs, Wall_time = 0.20 secs
Wed Mar 24 13:33:41 2021: Image # 1, module ExportToSpreadsheet # 14: CPU_time = 0.00 secs, Wall_time = 0.00 secs
[user@cn0884 ExampleHuman]$ exit
exit
salloc.exe: Relinquishing job allocation 11258266
salloc.exe: Job allocation 11258266 has been revoked.
[user@biowulf ~]$
Create a batch input file (e.g. cellprofiler.sh). For example:
#!/bin/bash set -e module load cellprofiler cellprofiler -p ExampleHuman.cppipe -c -r -i images/
Submit this job using the Slurm sbatch command.
sbatch [--cpus-per-task=#] [--mem=#] cellprofiler.sh
Create a swarmfile (e.g. cellprofiler.swarm). For example:
cellprofiler -p ExampleHuman1.cppipe -c -r -i images1/ cellprofiler -p ExampleHuman2.cppipe -c -r -i images2/ cellprofiler -p ExampleHuman3.cppipe -c -r -i images3/
Submit this job using the swarm command.
swarm -f cellprofiler.swarm [-g #] [-t #] --module cellprofilerwhere
| -g # | Number of Gigabytes of memory required for each process (1 line in the swarm command file) |
| -t # | Number of threads/CPUs required for each process (1 line in the swarm command file). |
| --module cellprofiler | Loads the cellprofiler module for each subjob in the swarm |