A simple to add and very useful feature would be “Deep 2D classification”, inspired by PMID: 32680969. Basically, given a particle set and 2D class averages, the Deep 2D classification job will execute an individual 2D classification for each and every class average and then aggregate the results for selection.
This can be useful for datasets that contain small, low SNR particles that tend to average with noise in the initial steps after particle picking, or to find rare views in regular datasets.
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Hi @RD_Cryo,
Thanks for the literature link and the feature request! We’ve noted this down as something to look into 
(As a PS in case it is helpful, it may be worth looking into the cryosparcm cli to see if parts of this workflow could be done programmatically. For example, one could use create_new_job and enqueue_job to create/queue new select 2D jobs for each of the classes output in a 2D classification to isolate each class and its corresponding particle stack, then subsequently launch 2D classifications on each of the select 2D jobs. Although the result aggregation would still have to be done manually, since select 2D currently doesn’t support ingesting templates/particles from more than one source 2D classification job).
Best,
Michael
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