Percentage of Usable Data - NaN Errors


Hi there,
We were running CellProfiler on roughly 5,000 cells worth of data and we were not sure what the “success rate” would be. We had used the workflow provided by the Blasi et al. (2016) paper. We noticed a majority of the images created (roughly 55%) were not viable for analysis (CellProfiler generated NaN results for most of the features). Is this a common number of discards, or is there some sort of issue whereby we are discarding too many cells accidentally?

Thanks very much!


That’s definitely not usual! It’s hard to know why in the abstract, but I’d recommend looking at your images/pipeline in test mode and seeing what it’s throwing out and why- that should give you an idea of where to start trying to fix it.