On the Analysis of Optical Mapping Data - University of Wisconsin ...
On the Analysis of Optical Mapping Data - University of Wisconsin ...
On the Analysis of Optical Mapping Data - University of Wisconsin ...
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ON THE ANALYSIS OF OPTICAL MAPPING DATA<br />
Deepayan Sarkar<br />
Under <strong>the</strong> supervision <strong>of</strong> Pr<strong>of</strong>essor Michael A. Newton<br />
At <strong>the</strong> <strong>University</strong> <strong>of</strong> <strong>Wisconsin</strong>-Madison<br />
Whole genome analysis <strong>of</strong> variation is becoming possible with improved biotechnology,<br />
and this is anticipated to have pr<strong>of</strong>ound implications for biology and medicine. Ideally,<br />
one would like to record a sampled genome at <strong>the</strong> nucleotide level, but this goal remains<br />
beyond our reach in spite <strong>of</strong> <strong>the</strong> fact that we now have a finished reference copy for several<br />
species. Using well-defined genomic markers, physical maps represent a genome at a lower<br />
resolution than nucleotide sequence. In particular, optical mapping produces physical maps<br />
based on coordinates <strong>of</strong> recognition sites <strong>of</strong> specific restriction enzymes. <strong>Optical</strong> mapping is<br />
well developed for small (e.g. microbial) genomes, and recent advances have enabled optical<br />
mapping <strong>of</strong> mammalian-sized genomes as well. This development, however, raises important<br />
new computational and statistical questions. The availability <strong>of</strong> reference genomes has been<br />
instrumental in <strong>the</strong> development <strong>of</strong> methods based on optical mapping to detect withinspecies<br />
variation, by serving as <strong>the</strong> basis for comparison with a sampled genome. Reference<br />
copies also open up o<strong>the</strong>r, less obvious, possibilities that impact <strong>the</strong> understanding and<br />
statistical analysis <strong>of</strong> optical mapping data. In this <strong>the</strong>sis we explore some such possibilities,<br />
particularly in <strong>the</strong> context <strong>of</strong> large genomes. In particular, we address parameter estimation<br />
in optical map models, <strong>the</strong> assessment <strong>of</strong> significance <strong>of</strong> optical map alignments, and <strong>the</strong> use<br />
<strong>of</strong> optical map data to detect copy number alterations.<br />
Michael A. Newton