NAME

       fastml - maximum likelihood ancestral amino-acid sequence reconstruction

SYNOPSIS

       fastml [options]

DESCRIPTION

       FastML is a bioinformatics tool for the reconstruction of ancestral sequences based on the
       phylogenetic relations between homologous sequences. FastML runs several  algorithms  that
       reconstruct  the  ancestral  sequences with emphasis on an accurate reconstruction of both
       indels and characters.  For  character  reconstruction  the  previously  described  FastML
       algorithms  are  used  to  efficiently  infer the most likely ancestral sequences for each
       internal node of the tree. Both joint and the marginal reconstructions are  provided.  For
       indels reconstruction the sequences are first coded according to the indel events detected
       within the multiple sequence alignment (MSA) and then a state-of-the-art likelihood  model
       is  used  to  reconstruct  ancestral  indels  states.  The  results  are the most probable
       sequences, together with posterior probabilities for each  character  and  indel  at  each
       sequence  position for each internal node of the tree. FastML is generic and is applicable
       for any type of molecular sequences (nucleotide, protein, or codon sequences).

OPTIONS

       -h     help

       -s     sequence input file (for example use -s emySequences/eseq.txt)

       -t     tree input file (if tree is not given, a neighbor joining tree is computed).

       -g     Assume among site rate variation model (Gamma) [By default the program
              will assume an homogeneous model. very fast, but less accurate!]

       -m     model name

       -mj    [JTT]

       -ml    LG

       -mr    mtREV (for mitochondrial genomes)

       -md    DAY

       -mw    WAG

       -mc    cpREV (for chloroplasts genomes)

       -ma    Jukes and Cantor (JC) for amino acids

       -mn    Jukes and Cantor (JC) for nucleotides

       -mh    HKY Model for nucleotides

       -mg    nucgtr Model for nucleotides

       -mt    tamura92 Model for nucleotides

       -my    yang M5 codons model

       -me    empirical codon matrix

       Controling the output options:

       -x     tree file output in Newick format [tree.newick.txt]

       -y     tree file output in ANCESTOR format [tree.ancestor.txt]

       -j     joint sequences output file [seq.joint.txt]

       -k     marginal sequences output file [seq.marginal.txt]

       -d     joint probabilities output file [prob.joint.txt]

       -e     marginal probabilities output file [prob.marginal.txt]

       -q     ancestral sequences output format. (-qc = [CLUSTAL], -qf = FASTA,
              -qm = MOLPHY, -qs = MASE, -qp = PHLIYP, -qn = Nexus)

       Advanced options:

       -a     Threshold for computing again marginal probabilities [0.9]

       -b     Do not optimize branch lengths on starting tree
              [by default branches and alpha are ML optimized from the data]

       -c     number of discrete Gamma categories for the gamma distribution [8]

       -f     don't compute Joint reconstruction (good if the branch and  bound  algorithm  takes
              too much time, and the goal is to compute the marginal reconstruction with Gamma).

       -z     The bound used. -zs - bound based on sum. -zm based on max. -zb [both]

       -p     user  alpha  parameter  of the gamma distribution [if alpha is not given, alpha and
              branches will be evaluated from the data (override -b)