FastML

FastML reconstructs ancestral sequences using maximum likelihood to infer ancestral character states and insertions/deletions (indels) for evolutionary analyses.

Key Features:

• Indel coding: Codes each gap, which may span multiple sites, as binary data.
• Indel reconstruction model: Reconstructs ancestral indel states under a continuous-time Markov process.
• Joint inference: Integrates insertions/deletions (indels) and character state reconstruction within a unified framework.
• Posterior probabilities: Computes posterior probabilities for each character and indel at every sequence position.
• Posterior sampling and k-most likely sequences: Generates a sample of ancestral sequences from the posterior distribution and reports the k-most likely ancestral sequences.
• Evolutionary model support: Supports nucleotide, protein, and codon evolutionary models.
• Graphical outputs: Produces graphical logos of inferred ancestral sequences.

Scientific Applications:

• Ancestral sequence reconstruction: Infers ancestral nucleotide, protein, and codon sequences for evolutionary and comparative analyses.
• Viral evolution studies: Reconstructs ancestral Env protein sequences across HIV-1 subtypes to study viral evolution.

Methodology:

Maximum likelihood ancestral reconstruction using an indel-coding method that encodes gaps as binary data; ancestral indel states reconstructed under a continuous-time Markov process; computation of posterior probabilities per character and indel, sampling from the posterior distribution, and reporting k-most likely ancestral sequences.