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

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3.3.3 Simulation
Given a generative model, such as the one described in Chapter 2, we can simulate optical
maps and align them using the test developed above. Since we know the origin of these maps,
we can estimate the true sensitivity and specificity. Such models are of limited use since they
do not capture all the sources of noise in real data, nor do they reflect the fluctuations in
parameter values that occur in the course of a real experiment. Nonetheless, simulation is
a valuable diagnostic tool. We applied the regression test derived above with a nominal
specificity of 99.9% to 50,000 maps simulated from the human reference. 73.42% of correct
alignments were declared as significant, 0.39% had at least one spurious alignment declared
to be significant in addition to the correct one and 0.27% had only spurious significant
alignments. It should be noted that some incorrect alignments are likely to be legitimate
due to repeat structures in the genome.
3.3.4 Improving assembly
Alignments of optical maps to a reference is an important component of the iterative assembly
scheme described in Section 1.3.5. Previously, a constant cutoff (determined heuristically)
has been used to assess significance with the SOMA score. Figure 3.2 clearly suggests
that this can be improved. By replacing the constant cutoff with the rules derived above and
comparing the results, we can get quantitative validation of our methods indirectly through
assembly. Figure 3.6 compares the results of using various significance strategies, including
the previously used cutoff and two regression cutoffs with different nominal specificities.
Chromosome 2 was assembled using the CHM data set (Section 1.2), which was not used in
determining the significance rules. A simple measure of success is the contig rate, i.e., the
proportion of maps passing the alignment step that are eventually included in the assembly.
By this measure, the new strategy clearly performs better. It is less clear how to compare
the quality of the resulting alignments, but the few measures we use in Figure 3.6 also favor
the new significance strategy.