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 |