As our knowledge of biological processes advances, we are increasingly aware that cells
actively position sub-cellular organelles and other constituents to control a wide range of
biological processes. Many studies quantify the position and motion of, for example,
fluorescently labeled proteins, protein aggregates, mRNA particles or virus particles. Both
differential interference contrast (DIC) and fluorescence microscopy can visualize vesicles,
nuclei or other small organelles moving inside cells. While such studies are increasingly
important, there has been no complete analysis of the different tracking methods in use,
especially from the practical point of view. Here we investigate these methods and clarify how
well different algorithms work and also which factors play a role in assessing how accurately
the position of an object can be determined. Specifically, we consider how ultimate
performance is affected by magnification, by camera type (analog versus digital), by recording
medium (VHS and SVHS tape versus direct tracking from camera), by image compression, by
type of imaging used (fluorescence versus DIC images) and by a variety of sources of noise.
We show that most methods are capable of nanometer scale accuracy under realistic
conditions; tracking accuracy decreases with increasing noise. Surprisingly, accuracy is found
to be insensitive to the numerical aperture, but, as expected, it scales with magnification, with
higher magnification yielding improved accuracy (within limits of signal-to-noise). When
noise is present at reasonable levels, the effect of image compression is in most cases small.
Finally, we provide a free, robust implementation of a tracking algorithm that is easily
downloaded and installed.