2.6 KiB
2.6 KiB
tiger
Identifying rapidly-evolving characters in evolutionary data
Usage
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TIGER Help:
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TIGER: Tree-Independent Generation of Evolutionary Rates
(Developed by Carla Cummins in the lab of James Mc Inerney, NUI Maynooth, Co. Kildare, Ireland)
-Options:
-in Specify input file. File must be in FastA format and must be aligned prior.
Datasets with uneven sequence lengths will return an error.
-v Returns current TIGER version.
-f Changes output formatting options.
-f s: sorts sites depending on their agreement score
-f r: displays rank values rather than bin numbers
-f s,r: displays sorted ranks (*Be sure to put only a "," NO SPACE!)
Default prints bin numbers unsorted.
-b Set the number of bins to be used.
-b <int>: Sites will be placed into <int> number of bins. <int> is a whole number.
Default is 10
-rl A list of the rate at each site may be optionally written to a specified
file.
-rl <file.txt> : writes list of the rates at each site to file.txt.
-ptp Specifies that a PTP test should be run. *Note: this option has a huge
effect on running time!
-z Number of randomisations to be used for the PTP test.
-z <int>: each site will be randomised <int> times. <int> is a whole number.
Default is 100
-p Specify p-value which denotes significance in PTP test.
-p <float>: site will be denoted as significant if p-value is better than <float>.
<float> is a floating point number.
Default is 0.05
-pl Write a list of p-values to a specified file.
-pl <file.txt>: writes list of p-values for each site to file.txt.
-u Specify unknown characters in the alignment. Unknown characters are omitted from
site patterns and so are not considered in the analysis.
-u ?,-,*: defines ?, - and * as unknown characters. (*Be sure to put only a comma
between characters, NO SPACE!!)
Default is ? only
System Requirements
- Python 3.x.
Note
Version 1.04 is made by Guoyi Zhang instead of other original authors. So, please cite this repository.
Citation
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Cummins, C.A. and McInerney, J.O. (2011) A method for inferring the rate of evolution of homologous characters that can potentially improve phylogenetic inference, resolve deep divergence and correct systematic biases. Systematic Biology 60 (6) 833-844. doi: 10.1093/sysbio/syr064.
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Zhang G. (2022) TIGER version 1.04. https://github.com/starsareintherose/tiger