Table 2 |
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|
More results on synthetic yeast-like data. Same as Table 1, except that the sequences have five embedded motifs (drawn from weight matrices that had 80% "polarisation"); this better mimics real data and also improves the performance of all programs. |
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|
q = 0.35 |
q = 0.45 |
q = 0.55 |
q = 0.65 |
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|
|
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|
5 embedded WM's |
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|
|
|||||||||||||||||
|
Ns |
Prog |
N+ |
N- |
Sen |
Er |
N+ |
N- |
Sen |
Er |
N+ |
N- |
Sen |
Er |
N+ |
N- |
Sen |
Er |
|
|
|||||||||||||||||
|
3 |
sigma+ |
0 |
0 |
0.00 |
N/A |
0 |
0 |
0.00 |
N/A |
13266 |
0 |
0.44 |
0.00 |
29352 |
0 |
0.98 |
0.00 |
|
sigma- |
0 |
0 |
0.00 |
N/A |
456 |
0 |
0.02 |
0.00 |
19028 |
0 |
0.63 |
0.00 |
29274 |
0 |
0.98 |
0.00 |
|
|
dialign |
78 |
0 |
0.03 |
0.00 |
60 |
0 |
0.02 |
0.00 |
2639 |
0 |
0.09 |
0.00 |
11383 |
40 |
0.38 |
0.00 |
|
|
alignm |
3067 |
506 |
0.10 |
0.14 |
11389 |
2153 |
0.38 |
0.16 |
24496 |
1217 |
0.82 |
0.05 |
28687 |
305 |
0.96 |
0.01 |
|
|
clustalw |
20814 |
9186 |
0.69 |
0.31 |
26730 |
3270 |
0.89 |
0.11 |
29341 |
659 |
0.98 |
0.02 |
29878 |
122 |
1.00 |
0.00 |
|
|
mlagan |
17160 |
12840 |
0.57 |
0.43 |
26930 |
3070 |
0.90 |
0.10 |
29716 |
284 |
0.99 |
0.01 |
30000 |
0 |
1.00 |
0.00 |
|
|
tcoffee |
10421 |
19579 |
0.35 |
0.65 |
20548 |
9452 |
0.68 |
0.32 |
28129 |
1871 |
0.94 |
0.06 |
29887 |
113 |
1.00 |
0.00 |
|
|
6 |
sigma+ |
0 |
0 |
0.00 |
N/A |
1625 |
0 |
0.03 |
0.00 |
36055 |
28 |
0.60 |
0.00 |
58596 |
0 |
0.98 |
0.00 |
|
sigma- |
452 |
42 |
0.01 |
0.09 |
5984 |
0 |
0.10 |
0.00 |
47264 |
26 |
0.79 |
0.00 |
58876 |
0 |
0.98 |
0.00 |
|
|
dialign |
510 |
144 |
0.01 |
0.22 |
1719 |
74 |
0.03 |
0.04 |
10250 |
0 |
0.17 |
0.00 |
33979 |
0 |
0.57 |
0.00 |
|
|
alignm |
3893 |
181 |
0.06 |
0.04 |
28300 |
1363 |
0.47 |
0.05 |
54487 |
1077 |
0.91 |
0.02 |
59496 |
170 |
0.99 |
0.00 |
|
|
clustalw |
42116 |
17884 |
0.70 |
0.30 |
53797 |
6203 |
0.90 |
0.10 |
58316 |
1684 |
0.97 |
0.03 |
59613 |
387 |
0.99 |
0.01 |
|
|
mlagan |
29458 |
30542 |
0.49 |
0.51 |
53833 |
6167 |
0.90 |
0.10 |
59427 |
573 |
0.99 |
0.01 |
60000 |
0 |
1.00 |
0.00 |
|
|
tcoffee |
25878 |
34122 |
0.43 |
0.57 |
47767 |
12233 |
0.80 |
0.20 |
58708 |
1292 |
0.98 |
0.02 |
59975 |
25 |
1.00 |
0.00 |
|
|
9 |
sigma+ |
40 |
30 |
0.00 |
0.43 |
2300 |
0 |
0.03 |
0.00 |
56847 |
20 |
0.63 |
0.00 |
87436 |
0 |
0.97 |
0.00 |
|
sigma- |
322 |
30 |
0.00 |
0.09 |
5805 |
0 |
0.06 |
0.00 |
69821 |
120 |
0.78 |
0.00 |
88775 |
0 |
0.99 |
0.00 |
|
|
dialign |
450 |
80 |
0.01 |
0.15 |
2844 |
106 |
0.03 |
0.04 |
20179 |
0 |
0.22 |
0.00 |
59400 |
0 |
0.66 |
0.00 |
|
|
alignm |
10165 |
652 |
0.11 |
0.06 |
60374 |
2420 |
0.67 |
0.04 |
85011 |
933 |
0.94 |
0.01 |
89651 |
201 |
1.00 |
0.00 |
|
|
clustalw |
62461 |
27539 |
0.69 |
0.31 |
83233 |
6767 |
0.92 |
0.08 |
86738 |
3262 |
0.96 |
0.04 |
89167 |
833 |
0.99 |
0.01 |
|
|
mlagan |
33857 |
56143 |
0.38 |
0.62 |
81225 |
8775 |
0.90 |
0.10 |
88869 |
1131 |
0.99 |
0.01 |
90000 |
0 |
1.00 |
0.00 |
|
|
tcoffee |
43416 |
46584 |
0.48 |
0.52 |
76928 |
13072 |
0.85 |
0.15 |
89240 |
760 |
0.99 |
0.01 |
89990 |
10 |
1.00 |
0.00 |
|
|
|
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|
Siddharthan BMC Bioinformatics 2006 7:143 doi:10.1186/1471-2105-7-143 |
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