Description Usage Arguments Details Value Author(s) References See Also Examples
This function implements the TKF92 model to estimate the pairwise distance from protein sequences. An additional simple model of regional heterogeneity of substitution rates is used.
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fasta |
A named list of sequences in vector of characters format.
|
mu |
A numeric value between 0 and 1 or NULL.
It is the death rate per normal link in TKF92 model.
When it is NULL, a joint estimation of |
r |
A numeric value between 0 and 1 or NULL.
It is the success probability of the geometric distribution
for modeling the fragment length in TKF92 model.
When it is NULL, a joint estimation of |
Ps |
A numeric value between 0 and 1 or NULL.
It is the equilibrium frequency of slow fragments.
Hence the equilibrium frequency of fast fragements is Pf= 1- Ps.
When it is NULL, a joint estimation of |
Kf |
A numeric value larger than 1 or NULL.
It is the ratio of substitutions rates between fast fragments and slow fragments.
When it is NULL, a joint estimation of |
distance |
A numeric value: the PAM distance between two protein sequences. When it is given, TKF92HGPair only calculates the negative log-likelihood. |
expectedLength |
A numeric object: the expected length of input protein sequences. By default, the average sequence length, 362, from OMA browser is used. |
substModel |
A numeric matrix: the mutation probability from one AA to another AA at PAM distance 1. The order of AA in the matrix should be identical to AACharacterSet. |
substModelBF |
A vector of numeric: the backrgound frequency of AAs. The order of AA in the vector should also be identical to AACharacterSet. |
seq1, seq2 |
A vector of character: the sequences of two proteins to compare. |
Currently this implementation only supports the normal 20 AAs. Missing or Ambiguous characters are not supported.
This is a very simple model of substitution rate heterogeneity. This model assumes that there are only two varieties of fragments: one with relatively fast substitution rates and the other with slow substitution rates. This model also assumes the fragment size distribution of these two fragments is identical.
A list of matrices are returned: the matrix of estimated distances, the matrix of estimated distance variances, the matrix of negative log-likelihood between the sequences.
Ge Tan
Thorne, J.L., Kishino, H., and Felsenstein, J. (1992). Inching toward reality: an improved likelihood model of sequence evolution. J. Mol. Evol. 34, 3-16.
Gonnet, G.H., Cohen, M.A., and Benner, S.A. (1992). Exhaustive matching of the entire protein sequence database. Science 256, 1443-1445.
AACharacterSet
,
GONNET
, GONNETBF
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## This example is not tested due to running time > 5s
data(GONNET)
data(GONNETBF)
library(seqinr)
fasta <- read.fasta(file.path(system.file("extdata", package="TKF"),
"pair1.fasta"),
seqtype="AA", set.attributes=FALSE)
## 1D estimation: only distance
TKF92HG(fasta, mu=5.920655e-04, r=0.8, Ps=1, Kf=1.2,
substModel=GONNET, substModelBF=GONNETBF)
## 2D estimation: joint estimation of distance, mu and r
TKF92HG(fasta, substModel=GONNET, substModelBF=GONNETBF)
## only apply to a pair of sequences
seq1 <- fasta[[1]]
seq2 <- fasta[[2]]
TKF92HGPair(seq1, seq2, mu=5.920655e-04, r=0.8, Ps=1, Kf=1.2,
substModel=GONNET, substModelBF=GONNETBF)
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