Identifying rapidly-evolving characters in evolutionary data
**************** TIGER Help: **************** 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
- Python 3.x.
Version 1.04 is made by Guoyi Zhang instead of other original authors. So, please cite this repository.
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.
Zhang G. (2022) TIGER version 1.04. https://github.com/starsareintherose/tiger