Table 5

Prune results for twelve alignment problems from the Rfam database.

Time

Agree.


Pecan1

_a

_a

Prune w/Pecan

60%

_a

_a

30%

14.6

0.651

15%

5.35

0.649

7%

2.57

0.643


FSA2

13.6

0.792

Prune w/FSA

60%

10.3

0.669

30%

4.30

0.615

15%

2.39

0.636

7%

2.17

0.636


MUSCLE3

3.67

0.709

Prune w/MUSCLE

60%

3.03

0.704

30%

1.23

0.649

15%

1.03

0.672

7%

1.42

0.659


MAFFT4

0.04

0.693


SATé5

93.9

0.753


1 Pecan was run with default parameters.

2 FSA was run with the --exonerate, --anchored, --softmasked, and --fast flags.

3 MUSCLE was run with default parameters.

4 MAFFT was run with --treein option.

5 SATé was run with the -t option but limited to two iterations. We found that more iterations did almost nothing for accuracy.

a The majority of problems were unable to be aligned due to running out of memory.

The run-time and agreement score of Prune alignments of twelve RNA alignment problems from the Rfam database. The average time and agreement over all twelve problems are shown. Pecan, FSA, and MUSCLE were used as the underlying alignment method of Prune. MAFFT and SATé were also tested to provide comparison. We were unable to apply Pecan without using Prune because of memory issues. Using Prune, we were able to use Pecan to solve these alignment problems. Prune achieved a very large speedup with little loss of accuracy. Other alignment methods achieved a large speedup but more accuracy was lost.

Roskin et al. BMC Bioinformatics 2011 12:144   doi:10.1186/1471-2105-12-144

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