Skip to content

HTTPS clone URL

Subversion checkout URL

You can clone with HTTPS or Subversion.

Download ZIP
tree: 658796dd11
943 lines (893 sloc) 19.015 kb
##
## Copyright 2009 Botond Sipos
## See the package description for licensing information.
##
## cpREV
##
##########################################################################/**
#
# @RdocClass cpREV
#
# @title "The cpREV empirical amino acid substitution model"
#
# \description{
#
#
# @classhierarchy
# }
#
# \references{
# Adachi, J., P. J. Waddell, W. Martin, and M. Hasegawa (2000) Plastid
# genome phylogeny and a model of amino acid substitution for proteins
# encoded by chloroplast DNA - Journal of Molecular Evolution 50:348--358
# DOI: 10.1007/s002399910038 \url{http://bit.ly/bnBVLm}
# }
#
# @synopsis
#
# \arguments{
# \item{equ.dist}{Equilibrium distribution.}
# \item{...}{Not used.}
# }
#
# \section{Fields and Methods}{
# @allmethods
# }
#
# \examples{
# # create substitution model object
# p<-cpREV()
# # get object summary
# summary(p)
# # display a bubble plot
# plot(p)
#
# # The following code demonstrates how to use
# # the process in a simulation.
#
# # create a sequence, attach process p
# s<-AminoAcidSequence(length=10,processes=list(list(p)) )
# # sample states
# sampleStates(s)
# # make the first three positions invariable
# setRateMultipliers(s,p,0,1:3)
# # get rate multipliers
# getRateMultipliers(s,p)
# # create a simulation object
# sim<-PhyloSim(root.seq=s,phylo=rcoal(2))
# # run simulation
# Simulate(sim)
# # print alignment
# sim$alignment
# }
#
# @author
#
# \seealso{
# AminoAcidSubst GeneralSubstitution UNREST
# }
#
#*/###########################################################################
setConstructorS3(
"cpREV",
function(
equ.dist=NA,
...
){
this<-AminoAcidSubst$newAAMatrix(
name="cpREV",
paml.file="cpREV.dat",
equ.dist=equ.dist
);
return(this);
},
enforceRCC=FALSE
);
##
## PAM
##
##########################################################################/**
#
# @RdocClass PAM
#
# @title "The PAM empirical amino acid substitution model"
#
# \description{
#
#
# @classhierarchy
# }
#
# \references{
# Dayhoff, M. O.; Schwartz, R. M.; Orcutt, B. C. (1978). "A model of evolutionary change in proteins" -
# Atlas of Protein Sequence and Structure 5 (3):345-352
#
# }
#
# @synopsis
#
# \arguments{
# \item{equ.dist}{Equilibrium distribution.}
# \item{...}{Not used.}
# }
#
# \section{Fields and Methods}{
# @allmethods
# }
#
# \examples{
# # create substitution model object
# p<-PAM()
# # get object summary
# summary(p)
# # display a bubble plot
# plot(p)
#
# # The following code demonstrates how to use
# # the process in a simulation.
#
# # create a sequence, attach process p
# s<-AminoAcidSequence(length=10,processes=list(list(p)) )
# # sample states
# sampleStates(s)
# # make the first three positions invariable
# setRateMultipliers(s,p,0,1:3)
# # get rate multipliers
# getRateMultipliers(s,p)
# # create a simulation object
# sim<-PhyloSim(root.seq=s,phylo=rcoal(2))
# # run simulation
# Simulate(sim)
# # print alignment
# sim$alignment
# }
#
# @author
#
# \seealso{
# AminoAcidSubst GeneralSubstitution UNREST
# }
#
#*/###########################################################################
setConstructorS3(
"PAM",
function(
equ.dist=NA,
...
){
this<-AminoAcidSubst$newAAMatrix(
name="PAM",
paml.file="dayhoff.dat",
equ.dist=equ.dist
);
return(this);
},
enforceRCC=FALSE
);
##
## PAM-dcmut
##
##########################################################################/**
#
# @RdocClass PAM.dcmut
#
# @title "The PAM.dcmut empirical amino acid substitution model"
#
# \description{
#
#
# @classhierarchy
# }
#
# \references{
# Kosiol, C, and Goldman, N (2005) Different versions of the Dayhoff rate matrix -
# Molecular Biology and Evolution 22:193-199 \url{http://dx.doi.org/10.1093/molbev/msi005}
# }
#
# @synopsis
#
# \arguments{
# \item{equ.dist}{Equilibrium distribution.}
# \item{...}{Not used.}
# }
#
# \section{Fields and Methods}{
# @allmethods
# }
#
# \examples{
# # create substitution model object
# p<-PAM.dcmut()
# # get object summary
# summary(p)
# # display a bubble plot
# plot(p)
#
# # The following code demonstrates how to use
# # the process in a simulation.
#
# # create a sequence, attach process p
# s<-AminoAcidSequence(length=10,processes=list(list(p)) )
# # sample states
# sampleStates(s)
# # make the first three invariable
# setRateMultipliers(s,p,0,1:3)
# # get rate multipliers
# getRateMultipliers(s,p)
# # create a simulation object
# sim<-PhyloSim(root.seq=s,phylo=rcoal(2))
# # run simulation
# Simulate(sim)
# # print alignment
# sim$alignment
# }
#
# @author
#
# \seealso{
# AminoAcidSubst GeneralSubstitution UNREST
# }
#
#*/###########################################################################
setConstructorS3(
"PAM.dcmut",
function(
equ.dist=NA,
...
){
this<-AminoAcidSubst$newAAMatrix(
name="PAM.dcmut",
paml.file="dayhoff-dcmut.dat",
equ.dist=equ.dist
);
return(this);
},
enforceRCC=FALSE
);
##
## JTT
##
##########################################################################/**
#
# @RdocClass JTT
#
# @title "The JTT empirical amino acid substitution model"
#
# \description{
#
#
# @classhierarchy
# }
#
# \references{
# Jones, D. T., W. R. Taylor, and J. M. Thornton (1992) The rapid generation of mutation data matrices
# from protein sequences. CABIOS 8:275-282 \url{http://dx.doi.org/10.1093/bioinformatics/8.3.275}
# }
#
# @synopsis
#
# \arguments{
# \item{equ.dist}{Equilibrium distribution.}
# \item{...}{Not used.}
# }
#
# \section{Fields and Methods}{
# @allmethods
# }
#
# \examples{
# # create substitution model object
# p<-JTT()
# # get object summary
# summary(p)
# # display a bubble plot
# plot(p)
#
# # The following code demonstrates how to use
# # the process in a simulation.
#
# # create a sequence, attach process p
# s<-AminoAcidSequence(length=10,processes=list(list(p)) )
# # sample states
# sampleStates(s)
# # make the first three positions invariable
# setRateMultipliers(s,p,0,1:3)
# # get rate multipliers
# getRateMultipliers(s,p)
# # create a simulation object
# sim<-PhyloSim(root.seq=s,phylo=rcoal(2))
# # run simulation
# Simulate(sim)
# # print alignment
# sim$alignment
# }
#
# @author
#
# \seealso{
# AminoAcidSubst GeneralSubstitution UNREST
# }
#
#*/###########################################################################
setConstructorS3(
"JTT",
function(
equ.dist=NA,
...
){
this<-AminoAcidSubst$newAAMatrix(
name="JTT",
paml.file="jones.dat",
equ.dist=equ.dist
);
return(this);
},
enforceRCC=FALSE
);
##
## JTT.dcmut
##
##########################################################################/**
#
# @RdocClass JTT.dcmut
#
# @title "The JTT.dcmut empirical amino acid substitution model"
#
# \description{
#
#
# @classhierarchy
# }
#
# \references{
# Kosiol, C, and Goldman, N (2005) Different versions of the Dayhoff rate matrix -
# Molecular Biology and Evolution 22:193-199 \url{http://dx.doi.org/10.1093/molbev/msi005}
#
# Jones, D. T., W. R. Taylor, and J. M. Thornton (1992) The rapid generation of mutation data matrices
# from protein sequences. CABIOS 8:275-282 \url{http://dx.doi.org/10.1093/bioinformatics/8.3.275}
# }
#
# @synopsis
#
# \arguments{
# \item{equ.dist}{Equilibrium distribution.}
# \item{...}{Not used.}
# }
#
# \section{Fields and Methods}{
# @allmethods
# }
#
# \examples{
# # create substitution model object
# p<-JTT.dcmut()
# # get object summary
# summary(p)
# # display a bubble plot
# plot(p)
#
# # The following code demonstrates how to use
# # the process in a simulation.
#
# # create a sequence, attach process p
# s<-AminoAcidSequence(length=10,processes=list(list(p)) )
# # sample states
# sampleStates(s)
# # make the first threee positions invariable
# setRateMultipliers(s,p,0,1:3)
# # get rate multipliers
# getRateMultipliers(s,p)
# # create a simulation object
# sim<-PhyloSim(root.seq=s,phylo=rcoal(2))
# # run simulation
# Simulate(sim)
# # print alignment
# sim$alignment
# }
#
# @author
#
# \seealso{
# AminoAcidSubst GeneralSubstitution UNREST
# }
#
#*/###########################################################################
setConstructorS3(
"JTT.dcmut",
function(
equ.dist=NA,
...
){
this<-AminoAcidSubst$newAAMatrix(
name="JTT.dcmut",
paml.file="jones-dcmut.dat",
equ.dist=equ.dist
);
return(this);
},
enforceRCC=FALSE
);
##
## LG
##
##########################################################################/**
#
# @RdocClass LG
#
# @title "The LG empirical amino acid substitution model"
#
# \description{
#
#
# @classhierarchy
# }
#
# \references{
# Le, S. Q., and O. Gascuel (2008) An improved general amino acid replacement matrix -
# Mol. Biol. Evol. 25:1307-1320 \url{http://dx.doi.org/10.1093/molbev/msn067}
# }
#
# @synopsis
#
# \arguments{
# \item{equ.dist}{Equilibrium distribution.}
# \item{...}{Not used.}
# }
#
# \section{Fields and Methods}{
# @allmethods
# }
#
# \examples{
# # create substitution model object
# p<-LG()
# # get object summary
# summary(p)
# # display a bubble plot
# plot(p)
#
# # The following code demonstrates how to use
# # the process in a simulation.
#
# # create a sequence, attach process p
# s<-AminoAcidSequence(length=10,processes=list(list(p)) )
# # sample states
# sampleStates(s)
# # make the first three positions invariable
# setRateMultipliers(s,p,0,1:3)
# # get rate multipliers
# getRateMultipliers(s,p)
# # create a simulation object
# sim<-PhyloSim(root.seq=s,phylo=rcoal(2))
# # run simulation
# Simulate(sim)
# # print alignment
# sim$alignment
# }
#
# @author
#
# \seealso{
# AminoAcidSubst GeneralSubstitution UNREST
# }
#
#*/###########################################################################
setConstructorS3(
"LG",
function(
equ.dist=NA,
...
){
this<-AminoAcidSubst$newAAMatrix(
name="LG",
paml.file="lg.dat",
equ.dist=equ.dist
);
return(this);
},
enforceRCC=FALSE
);
##
## mtArt
##
##########################################################################/**
#
# @RdocClass mtArt
#
# @title "The mtArt empirical amino acid substitution model"
#
# \description{
#
#
# @classhierarchy
# }
#
# \references{
# Abascal, F., D. Posada, and R. Zardoya (2007) MtArt: A new Model of
# amino acid replacement for Arthropoda - Mol. Biol. Evol. 24:1-5 \url{http://dx.doi.org/10.1093/molbev/msl136}
#
# }
#
# @synopsis
#
# \arguments{
# \item{equ.dist}{Equilibrium distribution.}
# \item{...}{Not used.}
# }
#
# \section{Fields and Methods}{
# @allmethods
# }
#
# \examples{
# # create substitution model object
# p<-mtArt()
# # get object summary
# summary(p)
# # display a bubble plot
# plot(p)
#
# # The following code demonstrates how to use
# # the process in a simulation.
#
# # create a sequence, attach process p
# s<-AminoAcidSequence(length=10,processes=list(list(p)) )
# # sample states
# sampleStates(s)
# # make the first three positions invariable
# setRateMultipliers(s,p,0,1:3)
# # get rate multipliers
# getRateMultipliers(s,p)
# # create a simulation object
# sim<-PhyloSim(root.seq=s,phylo=rcoal(2))
# # run simulation
# Simulate(sim)
# # print alignment
# sim$alignment
# }
#
# @author
#
# \seealso{
# AminoAcidSubst GeneralSubstitution UNREST
# }
#
#*/###########################################################################
setConstructorS3(
"mtArt",
function(
equ.dist=NA,
...
){
this<-AminoAcidSubst$newAAMatrix(
name="mtArt",
paml.file="mtArt.dat",
equ.dist=equ.dist
);
return(this);
},
enforceRCC=FALSE
);
##
## mtMam
##
##########################################################################/**
#
# @RdocClass mtMam
#
# @title "The mtMam empirical amino acid substitution model"
#
# \description{
#
#
# @classhierarchy
# }
#
# \references{
# Yang, Z., R. Nielsen, and M. Hasegawa (1998) Models of amino acid
# substitution and applications to Mitochondrial protein evolution,
# Molecular Biology and Evolution 15:1600-1611 \url{http://bit.ly/by4NMb}
# }
#
# @synopsis
#
# \arguments{
# \item{equ.dist}{Equilibrium distribution.}
# \item{...}{Not used.}
# }
#
# \section{Fields and Methods}{
# @allmethods
# }
#
# \examples{
# # create substitution model object
# p<-mtMam()
# # get object summary
# summary(p)
# # display a bubble plot
# plot(p)
#
# # The following code demonstrates how to use
# # the process in a simulation.
#
# # create a sequence, attach process p
# s<-AminoAcidSequence(length=10,processes=list(list(p)) )
# # sample states
# sampleStates(s)
# # make the first three positions invariable
# setRateMultipliers(s,p,0,1:3)
# # get rate multipliers
# getRateMultipliers(s,p)
# # create a simulation object
# sim<-PhyloSim(root.seq=s,phylo=rcoal(2))
# # run simulation
# Simulate(sim)
# # print alignment
# sim$alignment
# }
#
# @author
#
# \seealso{
# AminoAcidSubst GeneralSubstitution UNREST
# }
#
#*/###########################################################################
setConstructorS3(
"mtMam",
function(
equ.dist=NA,
...
){
this<-AminoAcidSubst$newAAMatrix(
name="mtMam",
paml.file="mtmam.dat",
equ.dist=equ.dist
);
return(this);
},
enforceRCC=FALSE
);
##
## mtREV24
##
##########################################################################/**
#
# @RdocClass mtREV24
#
# @title "The mtREV24 empirical amino acid substitution model"
#
# \description{
#
#
# @classhierarchy
# }
#
# \references{
# Adachi, J. and Hasegawa, M. (1996) MOLPHY version 2.3: programs for
# molecular phylogenetics based on maximum likelihood. Computer Science
# Monographs of Institute of Statistical Mathematics 28:1-150
# }
#
# @synopsis
#
# \arguments{
# \item{equ.dist}{Equilibrium distribution.}
# \item{...}{Not used.}
# }
#
# \section{Fields and Methods}{
# @allmethods
# }
#
# \examples{
# # create substitution model object
# p<-mtREV24()
# # get object summary
# summary(p)
# # display a bubble plot
# plot(p)
#
# # The following code demonstrates how to use
# # the process in a simulation.
#
# # create a sequence, attach process p
# s<-AminoAcidSequence(length=10,processes=list(list(p)) )
# # sample states
# sampleStates(s)
# # make the first three positions invariable
# setRateMultipliers(s,p,0,1:3)
# # get rate multipliers
# getRateMultipliers(s,p)
# # create a simulation object
# sim<-PhyloSim(root.seq=s,phylo=rcoal(2))
# # run simulation
# Simulate(sim)
# # print alignment
# sim$alignment
# }
#
# @author
#
# \seealso{
# AminoAcidSubst GeneralSubstitution UNREST
# }
#
#*/###########################################################################
setConstructorS3(
"mtREV24",
function(
equ.dist=NA,
...
){
this<-AminoAcidSubst$newAAMatrix(
name="mtREV24",
paml.file="mtREV24.dat",
equ.dist=equ.dist
);
return(this);
},
enforceRCC=FALSE
);
##
## MtZoa
##
##########################################################################/**
#
# @RdocClass MtZoa
#
# @title "The MtZoa empirical amino acid substitution model"
#
# \description{
#
#
# @classhierarchy
# }
#
# \references{
# Rota-Stabelli, O., Z. Yang, and M. Telford. (2009) MtZoa: a general mitochondrial amino acid
# substitutions model for animal evolutionary studies. Mol. Phyl. Evol 52(1):268-72 \url{http://bit.ly/bjZfKi}
# }
#
# @synopsis
#
# \arguments{
# \item{equ.dist}{Equilibrium distribution.}
# \item{...}{Not used.}
# }
#
# \section{Fields and Methods}{
# @allmethods
# }
#
# \examples{
# # create substitution model object
# p<-MtZoa()
# # get object summary
# summary(p)
# # display a bubble plot
# plot(p)
#
# # The following code demonstrates how to use
# # the process in a simulation.
#
# # create a sequence, attach process p
# s<-AminoAcidSequence(length=10,processes=list(list(p)) )
# # sample states
# sampleStates(s)
# # make the first three positions invariable
# setRateMultipliers(s,p,0,1:3)
# # get rate multipliers
# getRateMultipliers(s,p)
# # create a simulation object
# sim<-PhyloSim(root.seq=s,phylo=rcoal(2))
# # run simulation
# Simulate(sim)
# # print alignment
# sim$alignment
# }
#
# @author
#
# \seealso{
# AminoAcidSubst GeneralSubstitution UNREST
# }
#
#*/###########################################################################
setConstructorS3(
"MtZoa",
function(
equ.dist=NA,
...
){
this<-AminoAcidSubst$newAAMatrix(
name="MtZoa",
paml.file="MtZoa.dat",
equ.dist=equ.dist
);
return(this);
},
enforceRCC=FALSE
);
##
## WAG
##
##########################################################################/**
#
# @RdocClass WAG
#
# @title "The WAG empirical amino acid substitution model"
#
# \description{
#
#
# @classhierarchy
# }
#
# \references{
# Whelan, S. and N. Goldman (2001) A general empirical model of
# protein evolution derived from multiple protein families using a maximum likelihood
# approach - Molecular Biology and Evolution 18:691-699 \url{http://bit.ly/dpTKAd}
# }
#
# @synopsis
#
# \arguments{
# \item{equ.dist}{Equilibrium distribution.}
# \item{...}{Not used.}
# }
#
# \section{Fields and Methods}{
# @allmethods
# }
#
# \examples{
# # create substitution model object
# p<-WAG()
# # get object summary
# summary(p)
# # display a bubble plot
# plot(p)
#
# # The following code demonstrates how to use
# # the process in a simulation.
#
# # create a sequence, attach process p
# s<-AminoAcidSequence(length=10,processes=list(list(p)) )
# # sample states
# sampleStates(s)
# # make the first three positions invariable
# setRateMultipliers(s,p,0,1:3)
# # get rate multipliers
# getRateMultipliers(s,p)
# # create a simulation object
# sim<-PhyloSim(root.seq=s,phylo=rcoal(2))
# # run simulation
# Simulate(sim)
# # print alignment
# sim$alignment
# }
#
# @author
#
# \seealso{
# AminoAcidSubst GeneralSubstitution UNREST
# }
#
#*/###########################################################################
setConstructorS3(
"WAG",
function(
equ.dist=NA,
...
){
this<-AminoAcidSubst$newAAMatrix(
name="WAG",
paml.file="wag.dat",
equ.dist=equ.dist
);
return(this);
},
enforceRCC=FALSE
);
Jump to Line
Something went wrong with that request. Please try again.