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# file dna/R/test.individual.genes.R
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 or 3 of the License
# (at your option).
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# A copy of the GNU General Public License is available at
# http://www.r-project.org/Licenses/
#
test.individual.genes=function(X1,X2,scores="PLS",distance="abs",
num.permutations=1000,check.networks=TRUE,...){
X1=as.matrix(X1)
X2=as.matrix(X2)
if (check.networks==TRUE){
PairNetworks=new("pairOfNetworks",network1=X1,network2=X2)
CommonNetworks=get.common.networks(PairNetworks)
X1=CommonNetworks$network1
X2=CommonNetworks$network2
}
if (is.function(scores)==TRUE)
R.test.individual.genes(X1,X2,scores,distance,num.permutations,...)
else if (scores=="PLS")
PLSnet.test.individual.genes(X1,X2,distance,num.permutations,...)
else if (scores=="PC")
PCnet.test.individual.genes(X1,X2,distance,num.permutations,...)
else if (scores=="cor")
cornet.test.individual.genes(X1,X2,distance,num.permutations,...)
else if (scores=="RR")
RRnet.test.individual.genes(X1,X2,distance,num.permutations,...)
else
stop("Error: scores invalid!")
}
PLSnet.test.individual.genes=function(X1,X2,distance="abs",
num.permutations=1000,ncom=3,rescale.data=TRUE,symmetrize.scores=TRUE,
rescale.scores=FALSE){
if (distance=="abs")
distancetype=1
else if (distance=="sqr")
distancetype=2
n1=as.integer(nrow(X1))
n2=as.integer(nrow(X2))
p=as.integer(ncol(X1))
gene.names=colnames(X1)
out=.C("tdcindPLS",as.double(X1),as.double(X2),pval=double(p),d=double(p),n1,n2,p,as.integer(ncom),as.integer(num.permutations),as.integer(rescale.data),
as.integer(symmetrize.scores),as.integer(rescale.scores),
as.integer(distancetype))
names(out$pval)=gene.names
names(out$d)=gene.names
new("resultsIndTest",p.values=out$pval,d=out$d)
}
PCnet.test.individual.genes=function(X1,X2,distance="abs",
num.permutations=1000,ncom=3,rescale.data=TRUE,symmetrize.scores=TRUE,
rescale.scores=FALSE){
if (distance=="abs")
distancetype=1
else if (distance=="sqr")
distancetype=2
n1=as.integer(nrow(X1))
n2=as.integer(nrow(X2))
p=as.integer(ncol(X1))
gene.names=colnames(X1)
out=.C("tdcindPC",as.double(X1),as.double(X2),pval=double(p),d=double(p),n1,n2,
p,as.integer(ncom),as.integer(num.permutations),as.integer(rescale.data),
as.integer(symmetrize.scores),as.integer(rescale.scores),
as.integer(distancetype))
names(out$pval)=gene.names
names(out$d)=gene.names
new("resultsIndTest",p.values=out$pval,d=out$d)
}
RRnet.test.individual.genes=function(X1,X2,distance="abs",
num.permutations=1000,lambda=1,rescale.data=TRUE,symmetrize.scores=TRUE,
rescale.scores=FALSE){
if (distance=="abs")
distancetype=1
else if (distance=="sqr")
distancetype=2
n1=as.integer(nrow(X1))
n2=as.integer(nrow(X2))
p=as.integer(ncol(X1))
gene.names=colnames(X1)
out=.C("tdcindRR",as.double(X1),as.double(X2),pval=double(p),d=double(p),n1,n2,
p,as.double(lambda),as.integer(num.permutations),as.integer(rescale.data),
as.integer(symmetrize.scores),as.integer(rescale.scores),
as.integer(distancetype))
names(out$pval)=gene.names
names(out$d)=gene.names
new("resultsIndTest",p.values=out$pval,d=out$d)
}
cornet.test.individual.genes=function(X1,X2,distance="abs",
num.permutations=1000,rescale.scores=FALSE){
if (is.function(distance)==TRUE){
dist.f=distance
}
else if (distance=="abs")
dist.f=function(score1,score2){
abs(score1-score2)
}
else if (distance=="sqr")
dist.f=function(score1,score2){
(score1-score2)^2
}
else
stop("Error: distance invalid!")
s1=cornet(X1,rescale.scores)
s2=cornet(X2,rescale.scores)
n1=nrow(X1)
n2=nrow(X2)
X=rbind(X1,X2)
n=n1+n2
nG=ncol(X)
di=rep(0,nG)
for (g in 1:nG)
di[g]=sum(dist.f(s1[g,],s2[g,]))
di=di/(nG-1)
perm.di=rep(0,nG)
count.ind=rep(0,nG)
cat("Starting permutation test:\n")
for (i in 1:num.permutations){
cat("permutation",i,"out of",num.permutations,"\n")
i1=as.vector(sample(1:n,n1))
perm.X1=X[i1,]
perm.X2=X[-i1,]
perm.s1=cornet(perm.X1,rescale.scores)
perm.s2=cornet(perm.X2,rescale.scores)
for (g in 1:nG)
perm.di[g]=sum(dist.f(perm.s1[g,],perm.s2[g,]))
perm.di=perm.di/(nG-1)
for (g in 1:nG)
if (perm.di[g]>=di[g])
count.ind[g]=count.ind[g]+1
}
p.value.ind=rep(0,nG)
for (g in 1:nG){
p.value.ind[g]=count.ind[g]/num.permutations
}
names(p.value.ind)=colnames(X1)
names(di)=colnames(X1)
new("resultsIndTest",p.values=p.value.ind,d=di)
}
R.test.individual.genes=
function(X1,X2,f,distance="abs",num.permutations=1000,...){
if (is.function(distance)==TRUE){
dist.f=distance
}
else if (distance=="abs")
dist.f=function(score1,score2){
abs(score1-score2)
}
else if (distance=="sqr")
dist.f=function(score1,score2){
(score1-score2)^2
}
else
stop("Error: distance invalid!")
s1=f(X1,...)
s2=f(X2,...)
n1=nrow(X1)
n2=nrow(X2)
X=rbind(X1,X2)
n=n1+n2
nG=ncol(X)
di=rep(0,nG)
for (g in 1:nG)
di[g]=sum(dist.f(s1[g,],s2[g,]))
di=di/(nG-1)
perm.di=rep(0,nG)
count.ind=rep(0,nG)
cat("Starting permutation test:\n")
for (i in 1:num.permutations){
cat("permutation",i,"out of",num.permutations,"\n")
i1=as.vector(sample(1:n,n1))
perm.X1=X[i1,]
perm.X2=X[-i1,]
perm.s1=f(perm.X1,...)
perm.s2=f(perm.X2,...)
for (g in 1:nG)
perm.di[g]=sum(dist.f(perm.s1[g,],perm.s2[g,]))
perm.di=perm.di/(nG-1)
for (g in 1:nG)
if (perm.di[g]>=di[g])
count.ind[g]=count.ind[g]+1
}
p.value.ind=rep(0,nG)
for (g in 1:nG){
p.value.ind[g]=count.ind[g]/num.permutations
}
names(p.value.ind)=colnames(X1)
names(di)=colnames(X1)
new("resultsIndTest",p.values=p.value.ind,d=di)
}
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