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

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1.4 Outline
Optical mapping is a fast, low-cost, single-molecule system for producing whole genome
restriction maps. Its potential applications for studies of normal and disease biology are
manifold, but computational and statistical challenges created by large genomes must be
met in order for optical mapping to achieve this potential. Existing algorithms have been
effective on optical map data from small genomes. These algorithms do not easily extend
to the much larger data sets that are now being collected from larger genomes, and we are
as yet unable to completely mine the wealth of information contained in them. In part, this
is due to unavoidable computational bottlenecks. However, new avenues of analysis have
opened up with the availability of more and more sequence information. In the following
chapters, we present some new ideas on how to deal with optical map data. These ideas share
a common theme in that they all take advantage of the availability of in silico reference maps
derived from sequence. They do not, by any means, resolve all outstanding questions, but
hopefully they contribute to the understanding of optical map data and provide a reference
for future work in this area. In Chapter 2, we discuss stochastic models for optical map
errors and present some new approaches to parameter estimation in that setting. In Chapter
3, we propose a new method to determine significance of alignments of optical maps to a
reference, which is an important prerequisite in many analyses. In Chapter 4, we use these
alignments as the basis for an assembly-free method to detect copy number polymorphisms.
Especially in cancer biology, the ability to detect gains and losses of DNA is critical, as
frequently deleted sites may harbor tumor suppressor genes, and frequently amplified regions
may harbor oncogenes.