Quality assurance (QA) protocols can and should be used to proactively detect low-level spiking and other artifacts early so that these problems can be remedied before becoming more debilitating and adding significant overhead to the image analysis workflow. However, one generally needs corrupted data sets to test the accuracy of the novel algorithm. This prevents researchers from taking a proactive stance of establishing these QA protocols before corruption of data sets occurs. Here, we detail a simple method to generate spikes reliably and reproducibly to generate corrupted data that can be used to test and debug any new QA algorithms.
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