Rapid identification of sequence evolution models
Project description
modelmatcher: Rapid identification of evolutionary models
This tool reads multiple sequence alignments and determines a suitable sequence evolution model for your phylogenetic analysis.
Usage
Example usage:
$ modelmatcher inputfile.fasta
The input file is a multiple sequence alignmnent in one of these common formats:
- FASTA
- Clustal
- NEXUS
- PHYLIP
- STOCKHOLM
The output is a list of models, in order of fit to data, and their modelmatcher score. The base model (such as JTT, WAG, LG, etc) is predicted, as well as whether one should adapt to the alignments amino acid composition (i.e., JTT+F, WAG+F, etc).
If you want to automatically feed the prediction from modelmatcher
to a phylogenetic inference software, consider using
the -of
option:
iqtree -s infile.phy -m $(modelmatcher -of iqtree infile.phy)
The dollar-parenthesis is a subcommand and the output is a single model name. Only models accepted by the given application (here: IQTREE) are output.
Options
Optional options:
-h, --help show this help message and exit
-f {guess,fasta,clustal,nexus,phylip,stockholm}, --format {guess,fasta,clustal,nexus,phylip,stockholm}
Specify what sequence type to assume. Be specific if
the file is not recognized automatically. When reading
from stdin, the format is always guessed to be FASTA.
Default: guess
-m filename, --model filename
Add the model given in the file to the comparisons.
-nf, --no-F-testing Do not try +F models, i.e., do not test with amino
acid frequencies estimated from the MSA.
-s int, --sample-size int
For alignments with many sequences, decide on an upper
bound of sequence pairs to use from the MSA. The
computational complexity grows quadratically in the
number of sequences, so a choice of 5000 bounds the
growth for MSAs with more than 100 sequence.
-of {tabular,json,iqtree,raxml,phyml,mrbayes}, --output_format {tabular,json,iqtree,raxml,phyml,mrbayes}
Choose output format. Tabular format is default. JSON
is for convenient later parsing, with some additional
meta-data added. For one-line output convenient for
immediate use by inference tools, consider raxml and
similar choices. Note that the PhyML and MrBayes
options are restricted to their implemented models.
Although PhyML supports the +F models (using the "-f
e" option), this is not reflected in the output from
"modelmatcher -of phyml ..." at this time.
--list-models Output a list of models implemented in modelmatcher,
then exit.
--verbose Output progress information
--version
See the section "Output" below for some more examples.
Input formats
Input format is detected automatically from the following list, but can also be requested specifically.
- FASTA
- Phylip
- Nexus
- Clustal
- Stockholm
Output
The default output is given as a simple text table, or in JSON format for easy parsing by other scripts, ranking possible models in preference order. For example, the command above may yield a table looking like:
WAG 7.972
VT 8.238
BLOSUM62 8.478
JTT 8.864
JTT-DCMUT 8.917
LG 9.984
DCMUT 10.467
Dayhoff 10.495
FLU 11.211
HIVb 12.853
RtREV 14.048
cpREV 14.186
HIVw 17.338
MtZoa 18.476
MtMAM 21.453
mtArt 21.741
MtREV 22.059
Each model is given with its modelmatcher score.
Alternatively, the same analysis can look like:
$ modelmatcher --json inputfile.fasta
{"n_observations": 863692, "infile": "inputfile.fasta", "n_seqs": 66, "model_ranking": [["WAG", 7.972410383355675], ["VT", 8.238362164888876], ["BLOSUM62", 8.478000205922985], ["JTT", 8.863578165338444], ["JTT-DCMUT", 8.917496451351846], ["LG", 9.983874357603963], ["DCMUT", 10.466872509785343], ["Dayhoff", 10.49522598111376], ["FLU", 11.21137482805874], ["HIVb", 12.852877789672046], ["RtREV", 14.047539707772572], ["cpREV", 14.18648653904322], ["HIVw", 17.338193829402], ["MtZoa", 18.475515151949153], ["MtMAM", 21.452528293860837], ["mtArt", 21.740741039472418], ["MtREV", 22.058622800684176]]}
Install
Recommended installation is:
pip install --upgrade pip
pip install modelmatcher
Project details
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