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. 2009 May 29;5(5):e1000392. doi: 10.1371/journal.pcbi.1000392

Table 11. Timing comparison of FSA and other methods on 16S sequences.

Program 100 200 300 400 500 seqs
ClustalW 1,194 s 4,147 s 9,110 s 16,187 s 27,755 s
DIALIGN 4,346 s 19,449 s 49,388 s (fail) (fail)
FSA –fast 1,513 s 3754 s 5,641 s 9,767 s 15,683 s
FSA –fast –noindel2 –refinement 0 638 s 1,495 s 2,467 s 3,604 s 5,154 s
MAFFT 31 s 105 s 243 s 442 s 54 s
MUSCLE 351 s 1,235 s 1,516 s 4,384 s 7,552 s
ProbConsRNA 16,319 s (fail) (fail) (fail) (fail)
T-Coffee 1,362 s 3,666 s 7,880 s 15,254 s 22,085 s
SeqAn::T-Coffee 3,024 s (fail) (fail) (fail) (fail)

Comparison of runtimes of FSA and other alignment methods when aligning 16S ribosomal sequences. MAFFT was faster than any other method by an order of magnitude; the next-fastest programs were MUSCLE and FSA. FSA can be made substantially faster by using a 3-state, rather than the default 5-state, HMM (with little loss of accuracy; see Table 8) and disabling iterative refinement. MAFFT was run with the –auto option, which presumably triggered a faster alignment mode on the 500 sequence dataset than was used for the datasets with fewer sequences. The designation “(fail)” means that a programs failed to align a dataset (generally due to out-of-memory errors). Timing results are from computers with 2.40 GHz CPUs and 2 GB of RAM. 16S sequences were obtained as a random slice of prokMSA from Greengenes [65] and had an average length of 1,450 nt.