An Improved Genetic Algorithm for DNA Sequencing - Penn State ...

6 EXPERIMENTAL RESULTS 29
The second set of test data we used was generated by the spectrum generator
algorithm using the three genomes obtained from the GenBank [13]
referenced in Table 2. Table 3 lists all spectrum error combinations, positive
and negative, that were used to test the algorithm. For each of the three
genomes we tested the GA using 10 different sequences of each length in the
set {100, 200, 300, 400, 500, 1000, 2000}. That is, for each genome we tested
the algorithm using 70 different sequences. From each of these sequences we
used spectra with fragments of length 10 and 20. For each fragment length,
13 different combinations of positive and negative errors were used, ranging
from 0 to 20% errors as shown in Table 3. Hence, we tested all three genomes
using a total of 3 × 70 × 2 × 13 = 5, 460 spectra.
We have also generated a similar set of spectra with fragments of length
50. The algorithm was tested on all spectra of three different lengths: 10, 20,
and 50. We observe that the longer the fragments are, the better the results
are. In fact, with a fragment length of 50, our algorithm almost always found
the optimal answers, and thus, we do not include the data for fragments of
length 50 here. We used different fragment lengths since in practice different
hybridization techniques may require different fragment lengths. Normally,
the hybridization rate is better if the fragment length is longer. However, for
in situ hybridization, a small fragment length is required [21].
As in the case of the first data set, we use the Smith-Waterman sequence
alignment algorithm to determine the quality of the solutions returned by the
algorithm. We used an implementation of the Smith-Waterman algorithm
provided by Jie Li of Iowa State University [19]. Figures 12 and 13 show the
performance and running time of our algorithm on the second set of data. In
Figure 12, the graph shows the match percentage for spectra with fragment
length 10. The x-axis shows the various error combinations in the input spectrum.
The notation -a+b indicates spectra with a% negative error and %b
positive error. Thirteen different error combinations were used to verify the
performance of the new algorithm. These error combinations were selected
because of many reasons. Previous researches in the same area used similar
values for testing. We also wanted to provide error combinations that are