source: branches/profile/GDEHELP/HELP_WRITTEN/raxml.help

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1RAxML
2
3DESCRIPTION
4
5        RAxML (Randomized Axelerated Maximum Likelihood) is a program for sequential and parallel Maximum
6        Likelihood-based inference of large phylogenetic trees.
7
8        It has originally been derived from fastDNAml which
9        in turn was derived from Joe Felsenteins dnaml which is part of the PHYLIP package.
10
11        Author: Alexandros Stamatakis
12
13                Ecole Polytechnique Federale de Lausanne
14                School of Computer & Communication Sciences
15                Laboratory for Computational Biology and Bioinformatics (LCBB)
16
17                Alexandros.Stamatakis@epfl.ch
18
19        Original documentation can be found at
20        http://icwww.epfl.ch/~stamatak/index-Dateien/countManual7.0.0.php
21
22        Several parts of this documentation have been used here.
23
24PARAMETERS
25
26        Here we only describe the parameters adjustable via the ARB interface.
27
28        Weighting mask
29
30                Specify a weighting mask for the alignment. This increases penalty for
31                mismatches in conservative regions and decreases it in variable regions of
32                the alignment.
33
34                Since RAxML only accepts natural numbers as weights, ARB has to multiply
35                the weights of e.g. POS_VAR_BY_PARSIMONY, such that the smallest weight
36                equals 1.
37
38                As a consequence the likelyhood of the calculated tree is ~ 100000 times higher
39                than w/o weighting mask.
40
41        Base tree / Use as constraint tree / Generate random starting tree
42
43                Specifying a base tree works different depending on several other parameters.
44
45                Generally there are four different possibilities:
46
47                        - If you don't select a base tree (i.e. select '????') RAxML generates
48                          a starting tree using a Maximum Parsimony algorithm
49
50                        - If you additionally set 'Generate random starting tree' to 'Yes'
51                          RAxML generates a completely random starting tree.
52                          On smaller datasets (around
53                          100-200 taxa) it has been observed that this might sometimes yield
54                          topologies of distinct local likelihood maxima which better
55                          correspond to empirical expectations.
56
57                        - If you select a base tree, RAxML adds all species which are marked but
58                          are not in tree to this base tree using Maximum Parsimony.
59                          The resulting tree is then optimized using the selected RAxML algorithm.
60
61                        - If you set 'Use as constraint tree' to 'Yes' the topology of the given
62                          base tree will not be changed, only the position of the added species
63                          will be rearranged.
64
65                Notes:
66
67                        - All species contained in the 'Base tree' have to marked - otherwise
68                          RAxML will stop with an error.
69
70        Nucleotide Substitution Model / Rate Distribution Model / AA Substitution Model
71
72                Please refer to the original documentation for details on Substitution Models
73
74        Number of rate categories (DNA GTRCAT only)
75
76                This option allows you to specify the number of distinct rate categories,
77                into which the individually optimized rates for each individual site are ?thrown?
78                (Default = 25)
79
80        Optimize branches/parameters
81
82                Specifies that RAxML shall optimize branches and model parameters on
83                bootstrapped trees as well as print out the optimized likelihood. Note,
84                that this option only makes sense when used with the GTRMIX or
85                GTRGAMMA models (or the respective AA models)!
86
87        RAxML algorithm
88
89                new rapid hill climbing
90
91                        RAxML will execute the new (as of version 2.2.1) and significantly
92                        faster rapid hill-climbing algorithm
93
94                old hill climbing
95
96                        RAxML will execute the slower old search algorithm of version 2.1.3,
97                        this is essentially just for backward compatibility.
98
99                optimize input tree
100
101                        RAxML will optimize the model parameters and branch lengths of the
102                        selected 'Base tree' under GTRGAMMA
103
104                rapid bootstrap analysis
105
106                        tell RAxML to conduct a rapid Bootstrap analysis and search for the
107                        best-scoring ML tree in one single program run.
108
109                        Uses the seed specified at 'Random seed'
110
111                advanced bootstrap + refinement of BS tree
112
113                        performs a really thorough standard bootstrap. RAxML will refine the
114                        final BS tree under GAMMA and a more exhaustive algorithm.
115
116                add new sequences to input tree (MP)
117
118                        performs just pure stepwise MP addition of new sequences
119                        to an incomplete starting tree.
120
121                        You have to mark all species in tree AND all species which should be
122                        added to the tree.
123
124                        Note: RAxML has a bug in the tree-reader and rejects many
125                        trees as unrooted/multifurcated.
126                        You can to use 'Tree/Beautify Tree' and select the lowest
127                        mode (short branches first) as a workaround.
128
129                randomized tree searches (fixed start tree)
130               
131                        will perform several randomized tree searches (as specified at
132                        'Number of runs'), that always start from one fixed starting tree.
133
134        Random seed
135
136                Used as random seed for 'rapid bootstrap analysis'
137
138        Initial rearrangement setting
139
140                This allows you to specify an initial rearrangement setting for the initial
141                phase of the search algorithm. If you specify e.g. 10 the pruned subtrees will
142                be inserted up to a distance of 10 nodes away from their original pruning point.
143
144                If you don’t specify anything here, a "good" initial rearrangement setting
145                will automatically be determined by RAxML.
146
147        Number of runs
148
149                Enter a number > 1 to run the selected algorithm multiple times.
150                Specifying e.g. '10' will result in 10 generated trees.
151
152        Select ## best trees
153
154                If 'Number of runs' is > 1, this specifies how many of the generated tree
155                shall be imported or merge using consense.
156
157                The trees with the best likelyhood will be selected.
158
159        What to do with selected trees?
160
161                Import into ARB
162
163                        All selected trees will be imported into ARB
164
165                Create consense tree
166
167                        Calls consense on all selected trees and imports
168                        the resulting consense tree into ARB.
169
170
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