Help! There is a comet in my computer! 1
Do you have a problem?
Here I will talk about the basic principles of image analysis used in the comet assay. This
should help you spot and solve potential problems in your measurements, avoid
measurement errors, understand the settings available in software packages and the
language used in user manuals, and improve your communication with the software
companies when you run into trouble. The rest of this chapter is crap and you should move
to the next one or quit reading. Now, this is how all the problems began.
Not so long ago, my good friend Prof. Lite Microscope was elegantly standing on the real
desktop in our lab. He lived a happy and respectful life. A fine screwdriver and a drop of
oil fixed all his troubles, although he hardly had any. These days, he is choking under the
weight of digital cameras, ambushed by monitors, keyboards, graphics tables and printers.
An entanglement of cables ties him to his new master, Mr. P.C. Computer. The life of
imprisoned Prof. Microscope has moved to the virtual desktop. Every day he is humiliated
by software crashes, electronic mice, digital bugs, digital worms and digital viruses. The
only one that ever looks down his shiny objectives is Ms. Camera Digital. His newly
acquired, chip-controlled motors are desperately humming. Prof. Microscope suffers, and I
suffer with him. I have no idea what the mean Mr. Computer might be doing to the digital
results of my real experiments. I just sit in the dark for hours on end and click. Not so long
ago, I used to understand my science.
Does this sound familiar to you? Do you actually know how the computer calculates the
parameters of your comet assay? Do you understand the instructions and explanations in
the handbook that came with your comet software? And is it important to know this at all?
Judge for yourself. I bought expensive software from a well-respected company, ran the
computer and started clicking. I noticed straight away a problem with my data – the graphs
that I plotted were somewhat, but not completely, in disagreement with previously
published results from other labs. However, my results had remarkably small standard
errors, so I concluded that the computer was doing a very fine job. I blamed the new
method for staining of the slides that I used, and spent several months trying to perfect my
staining skills. The strangest thing was that whatever I did, my results were always very
similar, and always in disagreement with other labs. In the end I realised that it was not I, it
was the computer that spoiled my results. So I sat down, learned the basics of image
analysis and analysed the software algorithm step by step. In the end I found out that the
software was surely measuring something, but that this something was not at all a
meaningful parameter. The bad news was that the software could not be easily fixed – the
whole measurement procedure was based on erroneous assumptions and at odds with the
laws of physics. The next thing I did was learning how to program the computer for image
analysis.
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