What kind of machine will you use to process the images. A multi-core desktop or a cluster with a queueing system? What operating system?
How many fields of view per well do you have?
The brute force approach (likely to choke up CP when preparing the pipeline because of the large number of images) would be to add all of your images to the Images module in “Input modules”, then group them by plate in Groups module. Add CreateBatchFiles at the end of the pipeline and press “Analyze Images”. You’ll get a Batch_data.h5 file that describes the entire analysis. When you run the following command in the command line:
PATH_TO_CP/cellprofiler --get-batch-commands Batch_data.h5
you will get a list of commands to execute the actual analysis:
PATH_TO_CP/cellprofiler -c -r -b -p Batch_data.h5 -f 1 -l 384 -o output_dir
PATH_TO_CP/cellprofiler -c -r -b -p Batch_data.h5 -f 385 -l 768 -o output_dir
where parameters “-f” and “-l” determine the 1st and the last image from the image list; only these will be processed by this command. Each of these “jobs” will create a separate folder with outputs in the “output_dir”. They can be executed independently thus taking advantage of a distributed computing environment (a cluster) or a multi-core desktop.
Another approach would be to prepare your pipeline with LoadData module instead of the 4 modules in “Input modules” section. The LoadData lets you specify a CSV file with the list of your input image files. So you can either prepare such a file with all of your images and make grouping per well, or prepare separate CSVs for every plate and skip grouping if you insist on having separate results file per plate. In the latter option, once you have your pipeline, you can add an option “–data-file” to make the line that executes CP for a particular plate as follows:
PATH_TO_CP/cellprofiler -c -r -b -p your_pipeline.cppipe -o output_dir --data-file image_list_for_a_plate.csv
Of course, if you’re skilled with command line and shell scripting you can automate the entire process.
Some additional info on batch processing.