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The other distinctive feature of ALF is its user-friendly yet powerful web interface.We illustrate the utility of ALF with two possible applications: 1) we reanalyze data from a study of selection after globin gene duplication and test the statistical significance of the original conclusions and 2) we demonstrate that LGT can dramatically decrease the accuracy of two well-established orthology inference methods.
The user can provide a starting (ancestral) genome or have one generated randomly.
PAML evolver (Yang 1997), Seq-Gen (Rambaut and Grassly 1997), and its extensions PSeq-Gen (Grassly et al.
1997) and CS-PSeq-Gen(Tufféry 2002) were among the first popular programs that allowed synthetic evolution of a DNA (or protein) sequence along a given tree.
Because of the inherently unknown nature of these past events, model and method validation and comparison is notoriously difficult.
Computer programs that simulate evolution in silico provide viable test beds to understand and characterize new models and methods.
They include support for several models of nucleotide substitution as well as site-specific rate heterogeneity. Another program, SISSI (Gesell and Haeseler 2006), simulates site-specific interactions.
None of these programs support insertions and deletions (indels). Although most programs typicallyuse biologically very simple indel simulation, some programsalso incorporate more advanced models for indel formation and distribution: SIMPROT (Pang et al.
We then summarize various control experiments conducted to ensure ALFs correctness.
Finally, we present applications of ALF to two bioinformatics problems: First, we reanalyze data from a study of selection after globin gene duplication and test the statistical significance of the original conclusions; second, we demonstrate that LGT can dramatically decrease the accuracy of two well-established orthology inference methods.
Since simulations rely on simplifying models, they necessarily lack realism.
Nevertheless, they provide a way—often the only way—to investigate and test evolutionary models, algorithms, and implementations under controlled conditions.
The output consists of the simulated genomes, multiple sequence alignments, and gene trees of all gene families, all ancestral sequences, the true species tree including LGTs, and for each pair of genomes the sets of orthologous, paralogous, and xenologous sequences.