On the Analysis of Optical Mapping Data - University of Wisconsin ...

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1.3 Elements of optical mapping
We now describe in more depth elements of a typical optical mapping experiment. We
start with image processing and go on to discuss the structure of optical map data and
the goals and challenges we face in data analysis. We describe two basic computational
tasks, alignment and assembly, that are fundamental in addressing many other problems.
We end with a summary of the analysis of the GM07535 and CHM data sets reported by
Reslewic et al..
1.3.1 Image processing
Intensity profiles: For a typical optical mapping experiment, hundreds of raw images
need to be processed to obtain useful data (Figure 1.2). The first step in this process is to
identify the collections of pixels in an image that together represent a single DNA molecule.
This is a complicated task that falls in the domain of computer vision and will not be
discussed further. The end product of this step is an intensity profile for each molecule
(Figure 1.3) giving the measured fluorescent intensity as a function of distance along the
“backbone”. There are two ways to proceed. We may consider these profiles as our primary
data, and retain the information they contain in subsequent analyses. Alternatively, we may
immediately convert them into putative restriction maps, i.e. to an ordered sequence of
fragment lengths. The second approach is simpler because it separates the problem into two
parts that can be refined independently. Also, many standard techniques in computational
biology apply, with suitable adaptations, in this formulation. The first approach has a certain
appeal, but presents difficult challenges and we do not investigate it further. The rest of this
discussion assumes the second, two-step approach.
Cleavage sites: To convert intensity profiles to restriction maps, one has to first identify
the cleavage sites or cut sites in the map, indicated by ‘dips’ in the intensity profile. The
approaches traditionally used to identify cut sites are largely heuristic, although formal