Applying a time-reversible nucleotide model

We display the available set of nucleotide substitution models.

from cogent3 import available_models

available_models("nucleotide")

Specify a model using 'Abbreviation' (case sensitive).

Model Type	Abbreviation	Description
nucleotide	JC69	Jukes and Cantor's 1969 model
nucleotide	K80	Kimura 1980
nucleotide	F81	Felsenstein's 1981 model
nucleotide	HKY85	Hasegawa, Kishino and Yanamo 1985 model
nucleotide	TN93	Tamura and Nei 1993 model
nucleotide	GTR	General Time Reversible nucleotide substitution model.
nucleotide	ssGN	strand-symmetric general Markov nucleotide (non-stationary, non-reversible). Kaehler, 2017, Journal of Theoretical Biology 420: 144–51
nucleotide	GN	General Markov Nucleotide (non-stationary, non-reversible). Kaehler, Yap, Zhang, Huttley, 2015, Sys Biol 64 (2): 281–93
nucleotide	BH	Barry and Hartigan Discrete Time substitution model Barry and Hartigan 1987. Biometrics 43: 261–76.
nucleotide	DT	Discrete Time substitution model (non-stationary, non-reversible). motif_length=2 makes this a dinucleotide model, motif_length=3 a trinucleotide model.

10 rows x 3 columns

Using the GTR model

We specify the general time-reversible model (Lanave et al) by its abbreviation. By default, this model does not optimise the codon frequencies but uses the average estimated from the alignment. We configure the model to optimise the root motif probabilities.

from cogent3.app import io, evo

loader = io.load_aligned(format="fasta", moltype="dna")
aln = loader("../data/primate_brca1.fasta")
model = evo.model("GTR",
                  tree="../data/primate_brca1.tree",
                  sm_args=dict(optimise_motif_probs=True))
result = model(aln)
result

GTR

key	lnL	nfp	DLC	unique_Q
	-6992.5741	19	True

result.lf

GTR

log-likelihood = -6992.5741

number of free parameters = 19

Global params

A/C	A/G	A/T	C/G	C/T
1.2296	5.2478	0.9472	2.3389	5.9666

Edge params

edge	parent	length
Galago	root	0.1727
HowlerMon	root	0.0448
Rhesus	edge.3	0.0215
Orangutan	edge.2	0.0077
Gorilla	edge.1	0.0025
Human	edge.0	0.0060
Chimpanzee	edge.0	0.0028
edge.0	edge.1	0.0000
edge.1	edge.2	0.0034
edge.2	edge.3	0.0119
edge.3	root	0.0076

Motif params

A	C	G	T
0.3792	0.1719	0.2066	0.2423