setwd("C:/sepp/work/fabia/experiments") library(fabia) library(biclust) library(truecluster) library(BicARE) readPlaidResults <- function(filename,n,l,ab="ab",ss="ss",iter="default") { require(biclust) r1 <- readLines(filename) a1 <- strsplit(r1," ") la <- length(a1) p <- as.numeric(a1[[la-4]][1]) if ((p==0)||(la==0)) { L <- matrix(0,n,1) Z <- matrix(0,1,l) p <- 0 } else { L <- matrix(0,n,p) Z <- matrix(0,p,l) j <- 0 r <- 0 for (i in 1:la) { if (!is.na(a1[[i]][1])) { if (a1[[i]][1]=="row") { j <- j+1 r <- 1 } if (a1[[i]][1]=="col") { r <- 2 } if (a1[[i]][1]==as.character(j)) { if(r==1) { L[as.numeric(a1[[i]][2]),j] <- 1 } if(r==2) { Z[j,as.numeric(a1[[i]][2])] <- 1 } } } } } pp<- list() pp[[1]]="plaid" # method pp[[2]]=ab # a=alpha(probe) effects; b= beta(conditions) effects pp[[3]]=ss # seek=ss prefer large, possibly diffuse layers # seek=ms prefer intense, possibly small layers pp[[4]]=iter # how many seeking iterations bicB <- BiclustResult(pp,L,Z,p) return(bicB) } readBicatResults <- function(filename,n,l,method="isa",pre="standardization",tc="2.0",tg="2.0") { require(biclust) r1 <- readLines(filename) a1 <- strsplit(r1," ") la <- length(a1) p <- la/3 if ((p==0)||(la==0)) { L <- matrix(0,n,1) Z <- matrix(0,1,l) p <- 0 } else { L <- matrix(0,n,p) Z <- matrix(0,p,l) for (i in 1:p) { nn <- as.numeric(a1[[3*i-2]][1]) nl <- as.numeric(a1[[3*i-2]][2]) for (k in 1:nn) { L[as.numeric(a1[[3*i-1]][k]),i] <- 1 } for (k in 1:nl) { Z[i,as.numeric(a1[[3*i]][k])] <- 1 } } } pp<- list() pp[[1]]=method # method pp[[2]]=pre # preprocessing: standardization pp[[3]]=tg # gene score threshold pp[[4]]=tc # condition score threshold bicB <- BiclustResult(pp,L,Z,p) return(bicB) } readSambaResults <- function(filename,n,l,pre="standardization",opt="valsp_3ap",over="0.5") { require(biclust) r1 <- readLines(filename) a1 <- strsplit(r1,"\t") la <- length(a1) s <- 1 while ((a1[[s]][1]!="[Bicd]")&&(s<=la)) { s <- s+1 } p <- as.numeric(a1[[s-1]][1])+1 if ((p==0)||(la==0)) { L <- matrix(0,n,1) Z <- matrix(0,1,l) p <- 0 } else { L <- matrix(0,n,p) Z <- matrix(0,p,l) s <- s+1 for (i in s:la) { if (a1[[i]][2]=="1") { L[as.numeric(a1[[i]][3]),(as.numeric(a1[[i]][1])+1)] <- 1 } if (a1[[i]][2]=="0") { Z[(as.numeric(a1[[i]][1])+1),as.numeric(a1[[i]][3])] <- 1 } } } pp<- list() pp[[1]]="samba" # method pp[[2]]=pre # preprocessing: standardization pp[[3]]=opt # options: valsp_3ap pp[[4]]=over # overlap genes 0.1 or 0.5 bicB <- BiclustResult(pp,L,Z,p) return(bicB) } indices<- function (bicA, bicB) { require(truecluster) pA <- bicA@Number pB <- bicB@Number if ((pA>0)&&(pB>0)) { n <- length(bicA@RowxNumber[,1]) l <- length(bicA@NumberxCol[1,]) u <- n*l jamat <- matrix(0,pA,pB) kumat <- matrix(0,pA,pB) ocmat <- matrix(0,pA,pB) somat <- matrix(0,pA,pB) for (i in 1:pA) { bcA <- tcrossprod(bicA@RowxNumber[,i],bicA@NumberxCol[i,]) apos <- bcA > 0 sa <- sum(apos) if (sa > 0.5*u) { bcA[apos] <- 0 sa <- 0 } for (j in 1:pB) { bcB <- tcrossprod(bicB@RowxNumber[,j],bicB@NumberxCol[j,]) bpos <- bcB > 0 sb <- sum(bpos) if (sb > 0.5*u) { bcB[bpos] <- 0 sb <- 0 } bcAB <- bcA + bcB abpos <- bcAB > 0 sab <- sum(abpos) if (sab>0) { jamat[i,j] <- (sa + sb)/sab - 1 somat[i,j] <- 2.0-2.0*sab/(sa+sb) } else { jamat[i,j] <- 0 somat[i,j] <- 0 } if ((sa>0)&&(sb>0)) { kumat[i,j] <- 1.0+0.5*( (sa-sab)/sb + (sb -sab)/sa ) ocmat[i,j] <- (sa+sb-sab)/sqrt(sb*sa) }else { kumat[i,j] <- 0 ocmat[i,j] <- 0 } } } fac <- sqrt(pB*pA) mm <- min(pA,pB) ma <- max(pA,pB) sja <- sum(jamat)/fac sku <- sum(kumat)/fac soc <- sum(ocmat)/fac sso <- sum(somat)/fac indja <- munkres(-jamat,tieorder = FALSE) indku <- munkres(-kumat,tieorder = FALSE) indoc <- munkres(-ocmat,tieorder = FALSE) indso <- munkres(-somat,tieorder = FALSE) rjat <- sum(diag(jamat[indja$row, indja$col])) rkut <- sum(diag(kumat[indku$row, indku$col])) roct <- sum(diag(ocmat[indoc$row, indoc$col])) rsot <- sum(diag(somat[indso$row, indso$col])) rja <- rjat/mm rku <- rkut/mm roc <- roct/mm rso <- rsot/mm rja1 <- rjat/ma rku1 <- rkut/ma roc1 <- roct/ma rso1 <- rsot/ma } else { rja <- 0 rku <- 0 roc <- 0 rso <- 0 rja1 <- 0 rku1 <- 0 roc1 <- 0 rso1 <- 0 sja <- 0 sku <- 0 soc <- 0 sso <- 0 } return(as.vector(c(rja,rku,roc,rso,rja1,rku1,roc1,rso1,sja,sku,soc,sso))) } col_indices<- function (bicA, bicB) { require(truecluster) pA <- bicA@Number pB <- bicB@Number if ((pA>0)&&(pB>0)) { l <- length(bicA@NumberxCol[1,]) u <- l jamat <- matrix(0,pA,pB) kumat <- matrix(0,pA,pB) ocmat <- matrix(0,pA,pB) somat <- matrix(0,pA,pB) for (i in 1:pA) { bcA <- bicA@NumberxCol[i,] apos <- bcA > 0 sa <- sum(apos) if (sa > 0.8*u) { bcA[apos] <- 0 sa <- 0 } for (j in 1:pB) { bcB <- bicB@NumberxCol[j,] bpos <- bcB > 0 sb <- sum(bpos) if (sb > 0.8*u) { bcB[bpos] <- 0 sb <- 0 } bcAB <- bcA + bcB abpos <- bcAB > 0 sab <- sum(abpos) if (sab>0) { jamat[i,j] <- (sa + sb)/sab - 1 somat[i,j] <- 2.0-2.0*sab/(sa+sb) } else { jamat[i,j] <- 0 somat[i,j] <- 0 } if ((sa>0)&&(sb>0)) { kumat[i,j] <- 1.0+0.5*( (sa-sab)/sb + (sb -sab)/sa ) ocmat[i,j] <- (sa+sb-sab)/sqrt(sb*sa) }else { kumat[i,j] <- 0 ocmat[i,j] <- 0 } } } fac <- sqrt(pB*pA) mm <- min(pA,pB) ma <- max(pA,pB) sja <- sum(jamat)/fac sku <- sum(kumat)/fac soc <- sum(ocmat)/fac sso <- sum(somat)/fac indja <- munkres(-jamat,tieorder = FALSE) indku <- munkres(-kumat,tieorder = FALSE) indoc <- munkres(-ocmat,tieorder = FALSE) indso <- munkres(-somat,tieorder = FALSE) rjat <- sum(diag(jamat[indja$row, indja$col])) rkut <- sum(diag(kumat[indku$row, indku$col])) roct <- sum(diag(ocmat[indoc$row, indoc$col])) rsot <- sum(diag(somat[indso$row, indso$col])) rja <- rjat/mm rku <- rkut/mm roc <- roct/mm rso <- rsot/mm rja1 <- rjat/ma rku1 <- rkut/ma roc1 <- roct/ma rso1 <- rsot/ma } else { rja <- 0 rku <- 0 roc <- 0 rso <- 0 rja1 <- 0 rku1 <- 0 roc1 <- 0 rso1 <- 0 sja <- 0 sku <- 0 soc <- 0 sso <- 0 } return(as.vector(c(rja,rku,roc,rso,rja1,rku1,roc1,rso1,sja,sku,soc,sso))) } convertFabia <- function(rFab,n=1000,l=100,minc=5,minr=30,method="fabia",cyc=200,alpha=0.1,spl=1.0,spz=1.0,p=5,sL=0.0,sZ=0.0,La=NULL,Za=NULL,lapla=NULL,Psi=NULL) { require(biclust) p <- length(rFab$bic[,1]) pp <- 0 for (i in 1:p) { if (rFab$bic[i,1]$binp[1]>=minr) { if (rFab$bic[i,1]$binp[2]>=minc) { pp <- pp + 1 } } } if ((p==0)||(pp==0)) { L <- matrix(0,n,1) Z <- matrix(0,1,l) pp <- 0 } else { L <- matrix(0,n,pp) Z <- matrix(0,pp,l) j <- 0 for (i in 1:p) { if (rFab$bic[i,1]$binp[1]>=minr) { if (rFab$bic[i,1]$binp[2]>=minc) { j <- j + 1 for (k in 1:rFab$bic[i,1]$binp[2]) { Z[j,rFab$num[i,2]$numnp[k]] <- 1 } for (k in 1:rFab$bic[i,1]$binp[1]) { L[rFab$num[i,1]$numng[k],j] <- 1 } } } } } lp<- list() lp[[1]]=method lp[[2]]=cyc lp[[3]]=alpha lp[[4]]=spl lp[[5]]=spz lp[[6]]=p lp[[7]]=sL lp[[8]]=sZ lp[[9]]=La lp[[10]]=Za lp[[11]]=lapla lp[[12]]=Psi bicB <- BiclustResult(lp,L,Z,pp) return(bicB) } convertDat <- function(dat,n=1000,l=100) { require(biclust) p <- length(dat$LC) L <- matrix(0,n,p) Z <- matrix(0,p,l) for (i in 1:p) { for (k in 1:length(dat$LC[[i]])) { L[dat$LC[[i]][k],i] <- 1 } for (k in 1:length(dat$ZC[[i]])) { Z[i,dat$ZC[[i]][k]] <- 1 } } lp<- list() lp[[1]]="make_fabi_data" lp[[2]]=n lp[[3]]=l bicB <- BiclustResult(lp,L,Z,p) return(bicB) } #===================================================================== #===================================================================== alpha_fabia = 0.1 alpha_fabias = 0.4 spl=1.0 spz=1.0 cyc=200 p=5 #===================================================================== #===================================================================== data(Breast_A) l <- ncol(XBreast) n <- nrow(XBreast) porg <- 3 La <- matrix(1,n,porg) Za <- matrix(0,porg,l) for (i in 1:porg) { Za[i,which(CBreast==i)] <- 1 } lp<- list() lp[[1]]="breast_data" lp[[2]]=n lp[[3]]=l breast_biclust <- BiclustResult(lp,La,Za,porg) save(breast_biclust,file="exp_breast_Biclust_orig.RData") X <- as.matrix(XBreast) X <- X- rowMeans(X) XX <- (1/ncol(X))*tcrossprod(X) dXX <- 1/sqrt(diag(XX)+0.001*as.vector(rep(1,nrow(X)))) X <- dXX*X resFab <- fabia(X,cyc,alpha_fabia,spl,spz,p) rFab <- extract_bic(resFab$L,resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) rfabia <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="fabia",cyc=cyc,alpha=alpha_fabia,spl=spl,spz=spz,p=p,sL=0.0,sZ=0.0,L=resFab$L,Z=resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) save(rfabia,file="exp_breast_Biclust_fabia.RData") resFab <- fabias(X,cyc,alpha_fabias,spz,p) rFab <- extract_bic(resFab$L,resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) rfabias <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="fabias",cyc=cyc,alpha=alpha_fabias,spl=0,spz=spz,p=5,sL=0.0,sZ=0.0,L=resFab$L,Z=resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) save(rfabias,file="exp_breast_Biclust_fabias.RData") resFab <- fabiap(X,cyc,alpha_fabia,spl,spz,p,alpha_fabias,alpha_fabias) rFab <- extract_bic(resFab$L,resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) rfabiap <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="fabiap",cyc=cyc,alpha=alpha_fabia,spl=spl,spz=spz,p=5,sL=alpha_fabias,sZ=alpha_fabias,L=resFab$L,Z=resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) save(rfabiap,file="exp_breast_Biclust_fabiap.RData") resFab <- mfsc(X,p,alpha_fabias,alpha_fabias) rFab <- extract_bic(resFab$L,resFab$Z) rmfsc <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="mfsc",cyc=0,alpha=0,spl=0,spz=0,p=p,sL=alpha_fabias,sZ=alpha_fabias,L=resFab$L,Z=resFab$Z,lapla=NULL,Psi=NULL) save(rmfsc,file="exp_breast_Biclust_mfsc.RData") rplaid_ss<- readPlaidResults("exp_breast_plaid_ss.res",n,l,ab="ab",ss="ss",iter="default") save(rplaid_ss,file="exp_breast_Biclust_plaid_ss.RData") rplaid_ms<- readPlaidResults("exp_breast_plaid_ms.res",n,l,ab="ab",ss="ms",iter="default") save(rplaid_ms,file="exp_breast_Biclust_plaid_ms.RData") rplaid_ms_5 <- readPlaidResults("exp_breast_plaid_ms_5.res",n,l,ab="ab",ss="ms",iter="5") save(rplaid_ms_5,file="exp_breast_Biclust_plaid_ms_5.RData") rplaid_a_ss<- readPlaidResults("exp_breast_plaid_a_ss.res",n,l,ab="ab",ss="ss",iter="default") save(rplaid_a_ss,file="exp_breast_Biclust_plaid_a_ss.RData") rplaid_a_ms<- readPlaidResults("exp_breast_plaid_a_ms.res",n,l,ab="ab",ss="ms",iter="default") save(rplaid_a_ms,file="exp_breast_Biclust_plaid_a_ms.RData") rplaid_a_ms_5 <- readPlaidResults("exp_breast_plaid_a_ms_5.res",n,l,ab="ab",ss="ms",iter="5") save(rplaid_a_ms_5,file="exp_breast_Biclust_plaid_a_ms_5.RData") risa <- readBicatResults("exp_breast_isa.res",n,l,method="isa",pre="standardization",tc="2.0",tg="2.0") save(risa,file="exp_breast_Biclust_isa.RData") risa_1 <- readBicatResults("exp_breast_isa_1.res",n,l,method="isa",pre="standardization",tc="1.0",tg="1.0") save(risa_1,file="exp_breast_Biclust_isa_1.RData") ropsm <- readBicatResults("exp_breast_opsm.res",n,l,method="opsm",pre="standardization",tc="",tg="") save(ropsm,file="exp_breast_Biclust_opsm.RData") rsamba_01<- readSambaResults("exp_breast_samba_01.res",n,l,pre="standardization",opt="valsp_3ap",over="0.1") save(rsamba_01,file="exp_breast_Biclust_samba_01.RData") rsamba_05 <- readSambaResults("exp_breast_samba_05.res",n,l,pre="standardization",opt="valsp_3ap",over="0.5") save(rsamba_05,file="exp_breast_Biclust_samba_05.RData") XD<-discretize(X) rxmotif <- biclust(XD, method=BCXmotifs(), ns=100, nd=100, sd=5, alpha=0.05, number=5) save(rxmotif,file="exp_breast_Biclust_xmotif.RData") XB <- binarize(X) rbimax <- biclust(XB, method=BCBimax(), minr=30, minc=5, number=5) save(rbimax,file="exp_breast_Biclust_bimax.RData") rcc <- biclust(X, method=BCCC(), delta=0.03, alpha=1.2, number=5) save(rcc,file="exp_breast_Biclust_cc.RData") rplaid_t_ab <- biclust(X, method=BCPlaid(), cluster="b", fit.model = y ~ m + a + b, background = TRUE, row.release = 0.7, col.release = 0.7,shuffle = 3, back.fit = 0, max.layers = 5, iter.startup = 5, iter.layer = 10, verbose = TRUE) save(rplaid_t_ab,file="exp_breast_Biclust_plaid_t_ab.RData") rplaid_t_a <- biclust(X, method=BCPlaid(), cluster="b", fit.model = y ~ m + a, background = TRUE, row.release = 0.7, col.release = 0.7,shuffle = 3, back.fit = 0, max.layers = 5,iter.startup = 5, iter.layer = 10, verbose = TRUE) save(rplaid_t_a,file="exp_breast_Biclust_plaid_t_a.RData") rspec <- biclust(exp(X), method=BCSpectral(), normalization="log", numberOfEigenvalues=6, minr=30, minc=5, withinVar=1) save(rspec,file="exp_breast_Biclust_spec.RData") resfloc <- FLOC(X, k = 5, pGene = 0.1, pSample=0.1, N = 30, M = 5, t = 500) rfloc <- BiclustResult(as.list(resfloc$param),t(resfloc$bicRow),resfloc$bicCol,as.numeric(resfloc$param[1,2])) save(rfloc,file="exp_breast_Biclust_floc.RData") indrfabia<-col_indices(breast_biclust,rfabia) indrfabias<-col_indices(breast_biclust,rfabias) indrfabiap<-col_indices(breast_biclust,rfabiap) indrmfsc<-col_indices(breast_biclust,rmfsc) indrplaid_ss<-col_indices(breast_biclust,rplaid_ss) indrplaid_ms<-col_indices(breast_biclust,rplaid_ms) indrplaid_ms_5<-col_indices(breast_biclust,rplaid_ms_5) indrplaid_a_ss<-col_indices(breast_biclust,rplaid_a_ss) indrplaid_a_ms<-col_indices(breast_biclust,rplaid_a_ms) indrplaid_a_ms_5<-col_indices(breast_biclust,rplaid_a_ms_5) indrisa<-col_indices(breast_biclust,risa) indrisa_1<-col_indices(breast_biclust,risa_1) indropsm<-col_indices(breast_biclust,ropsm) indrsamba_01<-col_indices(breast_biclust,rsamba_01) indrsamba_05<-col_indices(breast_biclust,rsamba_05) indrxmotif<-col_indices(breast_biclust,rxmotif) indrbimax<-col_indices(breast_biclust,rbimax) indrcc<-col_indices(breast_biclust,rcc) indrplaid_t_ab<-col_indices(breast_biclust,rplaid_t_ab) indrplaid_t_a<-col_indices(breast_biclust,rplaid_t_a) indrspec<-col_indices(breast_biclust,rspec) indrfloc<-col_indices(breast_biclust,rfloc) save(indrfabia,indrfabias,indrfabiap,indrmfsc,indrplaid_ss,indrplaid_ms,indrplaid_ms_5,indrplaid_a_ss,indrplaid_a_ms,indrplaid_a_ms_5,indrisa,indrisa_1,indropsm,indrsamba_01,indrsamba_05,indrxmotif,indrbimax,indrcc,indrplaid_t_ab,indrplaid_t_a,indrspec,indrfloc,file="exp_breast_ind_res.RData") write.table(t(as.vector(indrfabia)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =FALSE) write.table(t(as.vector(indrfabias)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrfabiap)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrmfsc)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_ss)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_ms)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_ms_5)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_a_ss)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_a_ms)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_a_ms_5)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrisa)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrisa_1)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indropsm)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrsamba_01)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrsamba_05)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrxmotif)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrbimax)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrcc)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_t_ab)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_t_a)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrspec)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrfloc)), file = "exp_breast_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) #===================================================================== #===================================================================== data(Multi_A) l <- ncol(XMulti) n <- nrow(XMulti) porg <- 4 La <- matrix(1,n,porg) Za <- matrix(0,porg,l) for (i in 1:porg) { Za[i,which(CMulti==i)] <- 1 } lp<- list() lp[[1]]="multi_data" lp[[2]]=n lp[[3]]=l multi_biclust <- BiclustResult(lp,La,Za,porg) save(multi_biclust,file="exp_multi_Biclust_orig.RData") X <- as.matrix(XMulti) X <- X- rowMeans(X) XX <- (1/ncol(X))*tcrossprod(X) dXX <- 1/sqrt(diag(XX)+0.001*as.vector(rep(1,nrow(X)))) X <- dXX*X resFab <- fabia(X,cyc,alpha_fabia,spl,spz,5) rFab <- extract_bic(resFab$L,resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) rfabia <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="fabia",cyc=cyc,alpha=alpha_fabia,spl=spl,spz=spz,p=p,sL=0.0,sZ=0.0,L=resFab$L,Z=resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) save(rfabia,file="exp_multi_Biclust_fabia.RData") resFab <- fabias(X,cyc,alpha_fabias,spz,p) rFab <- extract_bic(resFab$L,resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) rfabias <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="fabias",cyc=cyc,alpha=alpha_fabias,spl=0,spz=spz,p=p,sL=0.0,sZ=0.0,L=resFab$L,Z=resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) save(rfabias,file="exp_multi_Biclust_fabias.RData") resFab <- fabiap(X,cyc,alpha_fabia,spl,spz,p,alpha_fabias,alpha_fabias) rFab <- extract_bic(resFab$L,resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) rfabiap <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="fabiap",cyc=cyc,alpha=alpha_fabia,spl=spl,spz=spz,p=5,sL=alpha_fabias,sZ=alpha_fabias,L=resFab$L,Z=resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) save(rfabiap,file="exp_multi_Biclust_fabiap.RData") resFab <- mfsc(X,p,alpha_fabias,alpha_fabias) rFab <- extract_bic(resFab$L,resFab$Z) rmfsc <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="mfsc",cyc=0,alpha=0,spl=0,spz=0,p=p,sL=alpha_fabias,sZ=alpha_fabias,L=resFab$L,Z=resFab$Z,lapla=NULL,Psi=NULL) save(rmfsc,file="exp_multi_Biclust_mfsc.RData") rplaid_ss<- readPlaidResults("exp_multi_plaid_ss.res",n,l,ab="ab",ss="ss",iter="default") save(rplaid_ss,file="exp_multi_Biclust_plaid_ss.RData") rplaid_ms<- readPlaidResults("exp_multi_plaid_ms.res",n,l,ab="ab",ss="ms",iter="default") save(rplaid_ms,file="exp_multi_Biclust_plaid_ms.RData") rplaid_ms_5 <- readPlaidResults("exp_multi_plaid_ms_5.res",n,l,ab="ab",ss="ms",iter="5") save(rplaid_ms_5,file="exp_multi_Biclust_plaid_ms_5.RData") rplaid_a_ss<- readPlaidResults("exp_multi_plaid_a_ss.res",n,l,ab="ab",ss="ss",iter="default") save(rplaid_a_ss,file="exp_multi_Biclust_plaid_a_ss.RData") rplaid_a_ms<- readPlaidResults("exp_multi_plaid_a_ms.res",n,l,ab="ab",ss="ms",iter="default") save(rplaid_a_ms,file="exp_multi_Biclust_plaid_a_ms.RData") rplaid_a_ms_5 <- readPlaidResults("exp_multi_plaid_a_ms_5.res",n,l,ab="ab",ss="ms",iter="5") save(rplaid_a_ms_5,file="exp_multi_Biclust_plaid_a_ms_5.RData") risa <- readBicatResults("exp_multi_isa.res",n,l,method="isa",pre="standardization",tc="2.0",tg="2.0") save(risa,file="exp_multi_Biclust_isa.RData") risa_1 <- readBicatResults("exp_multi_isa_1.res",n,l,method="isa",pre="standardization",tc="1.0",tg="1.0") save(risa_1,file="exp_multi_Biclust_isa_1.RData") ropsm <- readBicatResults("exp_multi_opsm.res",n,l,method="opsm",pre="standardization",tc="",tg="") save(ropsm,file="exp_multi_Biclust_opsm.RData") rsamba_01<- readSambaResults("exp_multi_samba_01.res",n,l,pre="standardization",opt="valsp_3ap",over="0.1") save(rsamba_01,file="exp_multi_Biclust_samba_01.RData") rsamba_05 <- readSambaResults("exp_multi_samba_05.res",n,l,pre="standardization",opt="valsp_3ap",over="0.5") save(rsamba_05,file="exp_multi_Biclust_samba_05.RData") XD<-discretize(X) rxmotif <- biclust(XD, method=BCXmotifs(), ns=100, nd=100, sd=5, alpha=0.05, number=5) save(rxmotif,file="exp_multi_Biclust_xmotif.RData") XB <- binarize(X) rbimax <- biclust(XB, method=BCBimax(), minr=30, minc=5, number=5) save(rbimax,file="exp_multi_Biclust_bimax.RData") # rcc <- biclust(X, method=BCCC(), delta=0.03, alpha=1.2, number=5) # save(rcc,file="exp_multi_Biclust_cc.RData") rplaid_t_ab <- biclust(X, method=BCPlaid(), cluster="b", fit.model = y ~ m + a + b, background = TRUE, row.release = 0.7, col.release = 0.7,shuffle = 3, back.fit = 0, max.layers = 5, iter.startup = 5, iter.layer = 10, verbose = TRUE) save(rplaid_t_ab,file="exp_multi_Biclust_plaid_t_ab.RData") rplaid_t_a <- biclust(X, method=BCPlaid(), cluster="b", fit.model = y ~ m + a, background = TRUE, row.release = 0.7, col.release = 0.7,shuffle = 3, back.fit = 0, max.layers = 5,iter.startup = 5, iter.layer = 10, verbose = TRUE) save(rplaid_t_a,file="exp_multi_Biclust_plaid_t_a.RData") rspec <- biclust(exp(X), method=BCSpectral(), normalization="log", numberOfEigenvalues=6, minr=30, minc=5, withinVar=1) save(rspec,file="exp_multi_Biclust_spec.RData") # resfloc <- FLOC(X, k = 5, pGene = 0.1, pSample=0.1, N = 30, M = 5, t = 500) # rfloc <- BiclustResult(as.list(resfloc$param),t(resfloc$bicRow),resfloc$bicCol,as.numeric(resfloc$param[1,2])) # save(rfloc,file="exp_multi_Biclust_floc.RData") indrfabia<-col_indices(multi_biclust,rfabia) indrfabias<-col_indices(multi_biclust,rfabias) indrfabiap<-col_indices(multi_biclust,rfabiap) indrmfsc<-col_indices(multi_biclust,rmfsc) indrplaid_ss<-col_indices(multi_biclust,rplaid_ss) indrplaid_ms<-col_indices(multi_biclust,rplaid_ms) indrplaid_ms_5<-col_indices(multi_biclust,rplaid_ms_5) indrplaid_a_ss<-col_indices(multi_biclust,rplaid_a_ss) indrplaid_a_ms<-col_indices(multi_biclust,rplaid_a_ms) indrplaid_a_ms_5<-col_indices(multi_biclust,rplaid_a_ms_5) indrisa<-col_indices(multi_biclust,risa) indrisa_1<-col_indices(multi_biclust,risa_1) indropsm<-col_indices(multi_biclust,ropsm) indrsamba_01<-col_indices(multi_biclust,rsamba_01) indrsamba_05<-col_indices(multi_biclust,rsamba_05) indrxmotif<-col_indices(multi_biclust,rxmotif) indrbimax<-col_indices(multi_biclust,rbimax) # indrcc<-col_indices(multi_biclust,rcc) indrplaid_t_ab<-col_indices(multi_biclust,rplaid_t_ab) indrplaid_t_a<-col_indices(multi_biclust,rplaid_t_a) indrspec<-col_indices(multi_biclust,rspec) # indrfloc<-col_indices(multi_biclust,rfloc) save(indrfabia,indrfabias,indrfabiap,indrmfsc,indrplaid_ss,indrplaid_ms,indrplaid_ms_5,indrplaid_a_ss,indrplaid_a_ms,indrplaid_a_ms_5,indrisa,indrisa_1,indropsm,indrsamba_01,indrsamba_05,indrxmotif,indrbimax,indrcc,indrplaid_t_ab,indrplaid_t_a,indrspec,indrfloc,file="exp_multi_ind_res.RData") write.table(t(as.vector(indrfabia)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =FALSE) write.table(t(as.vector(indrfabias)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrfabiap)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrmfsc)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_ss)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_ms)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_ms_5)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_a_ss)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_a_ms)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_a_ms_5)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrisa)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrisa_1)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indropsm)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrsamba_01)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrsamba_05)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrxmotif)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrbimax)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) # write.table(t(as.vector(indrcc)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_t_ab)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_t_a)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrspec)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) # write.table(t(as.vector(indrfloc)), file = "exp_multi_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) #===================================================================== #===================================================================== data(DLBCL_B) l <- ncol(XDLBCL) n <- nrow(XDLBCL) porg <- 3 La <- matrix(1,n,porg) Za <- matrix(0,porg,l) for (i in 1:porg) { Za[i,which(CDLBCL==i)] <- 1 } lp<- list() lp[[1]]="dlbcl_data" lp[[2]]=n lp[[3]]=l dlbcl_biclust <- BiclustResult(lp,La,Za,porg) save(dlbcl_biclust,file="exp_dlbcl_Biclust_orig.RData") X <- as.matrix(XDLBCL) X <- X- rowMeans(X) XX <- (1/ncol(X))*tcrossprod(X) dXX <- 1/sqrt(diag(XX)+0.001*as.vector(rep(1,nrow(X)))) X <- dXX*X resFab <- fabia(X,cyc,alpha_fabia,spl,spz,p) rFab <- extract_bic(resFab$L,resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) rfabia <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="fabia",cyc=cyc,alpha=alpha_fabia,spl=spl,spz=spz,p=p,sL=0.0,sZ=0.0,L=resFab$L,Z=resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) save(rfabia,file="exp_dlbcl_Biclust_fabia.RData") resFab <- fabias(X,cyc,alpha_fabias,spz,p) rFab <- extract_bic(resFab$L,resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) rfabias <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="fabias",cyc=cyc,alpha=alpha_fabias,spl=0,spz=spz,p=p,sL=0.0,sZ=0.0,L=resFab$L,Z=resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) save(rfabias,file="exp_dlbcl_Biclust_fabias.RData") resFab <- fabiap(X,cyc,alpha_fabia,spl,spz,ww,alpha_fabias,alpha_fabias) rFab <- extract_bic(resFab$L,resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) rfabiap <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="fabiap",cyc=cyc,alpha=alpha_fabia,spl=spl,spz=spz,p=p,sL=alpha_fabias,sZ=alpha_fabias,L=resFab$L,Z=resFab$Z,lapla=resFab$lapla,Psi=resFab$Psi) save(rfabiap,file="exp_dlbcl_Biclust_fabiap.RData") resFab <- mfsc(X,p,alpha_fabias,alpha_fabias) rFab <- extract_bic(resFab$L,resFab$Z) rmfsc <- convertFabia(rFab,n=n,l=l,minc=5,minr=30,method="mfsc",cyc=0,alpha=0,spl=0,spz=0,p=p,sL=alpha_fabias,sZ=alpha_fabias,L=resFab$L,Z=resFab$Z,lapla=NULL,Psi=NULL) save(rmfsc,file="exp_dlbcl_Biclust_mfsc.RData") rplaid_ss<- readPlaidResults("exp_dlbcl_plaid_ss.res",n,l,ab="ab",ss="ss",iter="default") save(rplaid_ss,file="exp_dlbcl_Biclust_plaid_ss.RData") rplaid_ms<- readPlaidResults("exp_dlbcl_plaid_ms.res",n,l,ab="ab",ss="ms",iter="default") save(rplaid_ms,file="exp_dlbcl_Biclust_plaid_ms.RData") rplaid_ms_5 <- readPlaidResults("exp_dlbcl_plaid_ms_5.res",n,l,ab="ab",ss="ms",iter="5") save(rplaid_ms_5,file="exp_dlbcl_Biclust_plaid_ms_5.RData") rplaid_a_ss<- readPlaidResults("exp_dlbcl_plaid_a_ss.res",n,l,ab="ab",ss="ss",iter="default") save(rplaid_a_ss,file="exp_dlbcl_Biclust_plaid_a_ss.RData") rplaid_a_ms<- readPlaidResults("exp_dlbcl_plaid_a_ms.res",n,l,ab="ab",ss="ms",iter="default") save(rplaid_a_ms,file="exp_dlbcl_Biclust_plaid_a_ms.RData") rplaid_a_ms_5 <- readPlaidResults("exp_dlbcl_plaid_a_ms_5.res",n,l,ab="ab",ss="ms",iter="5") save(rplaid_a_ms_5,file="exp_dlbcl_Biclust_plaid_a_ms_5.RData") risa <- readBicatResults("exp_dlbcl_isa.res",n,l,method="isa",pre="standardization",tc="2.0",tg="2.0") save(risa,file="exp_dlbcl_Biclust_isa.RData") risa_1 <- readBicatResults("exp_dlbcl_isa_1.res",n,l,method="isa",pre="standardization",tc="1.0",tg="1.0") save(risa_1,file="exp_dlbcl_Biclust_isa_1.RData") ropsm <- readBicatResults("exp_dlbcl_opsm.res",n,l,method="opsm",pre="standardization",tc="",tg="") save(ropsm,file="exp_dlbcl_Biclust_opsm.RData") rsamba_01 <- readSambaResults("exp_dlbcl_samba_01.res",n,l,pre="standardization",opt="valsp_3ap",over="0.5") save(rsamba_01,file="exp_dlbcl_Biclust_samba_01.RData") rsamba_05 <- readSambaResults("exp_dlbcl_samba_05.res",n,l,pre="standardization",opt="valsp_3ap",over="0.5") save(rsamba_05,file="exp_dlbcl_Biclust_samba_05.RData") XD<-discretize(X) rxmotif <- biclust(XD, method=BCXmotifs(), ns=100, nd=100, sd=5, alpha=0.05, number=5) save(rxmotif,file="exp_dlbcl_Biclust_xmotif.RData") XB <- binarize(X) rbimax <- biclust(XB, method=BCBimax(), minr=30, minc=5, number=5) save(rbimax,file="exp_dlbcl_Biclust_bimax.RData") rcc <- biclust(X, method=BCCC(), delta=0.03, alpha=1.2, number=5) save(rcc,file="exp_dlbcl_Biclust_cc.RData") rplaid_t_ab <- biclust(X, method=BCPlaid(), cluster="b", fit.model = y ~ m + a + b, background = TRUE, row.release = 0.7, col.release = 0.7,shuffle = 3, back.fit = 0, max.layers = 5, iter.startup = 5, iter.layer = 10, verbose = TRUE) save(rplaid_t_ab,file="exp_dlbcl_Biclust_plaid_t_ab.RData") rplaid_t_a <- biclust(X, method=BCPlaid(), cluster="b", fit.model = y ~ m + a, background = TRUE, row.release = 0.7, col.release = 0.7,shuffle = 3, back.fit = 0, max.layers = 5,iter.startup = 5, iter.layer = 10, verbose = TRUE) save(rplaid_t_a,file="exp_dlbcl_Biclust_plaid_t_a.RData") rspec <- biclust(exp(X), method=BCSpectral(), normalization="log", numberOfEigenvalues=6, minr=30, minc=5, withinVar=1) save(rspec,file="exp_dlbcl_Biclust_spec.RData") resfloc <- FLOC(X, k = 5, pGene = 0.1, pSample=0.1, N = 30, M = 5, t = 500) rfloc <- BiclustResult(as.list(resfloc$param),t(resfloc$bicRow),resfloc$bicCol,as.numeric(resfloc$param[1,2])) save(rfloc,file="exp_dlbcl_Biclust_floc.RData") indrfabia<-col_indices(dlbcl_biclust,rfabia) indrfabias<-col_indices(dlbcl_biclust,rfabias) indrfabiap<-col_indices(dlbcl_biclust,rfabiap) indrmfsc<-col_indices(dlbcl_biclust,rmfsc) indrplaid_ss<-col_indices(dlbcl_biclust,rplaid_ss) indrplaid_ms<-col_indices(dlbcl_biclust,rplaid_ms) indrplaid_ms_5<-col_indices(dlbcl_biclust,rplaid_ms_5) indrplaid_a_ss<-col_indices(dlbcl_biclust,rplaid_a_ss) indrplaid_a_ms<-col_indices(dlbcl_biclust,rplaid_a_ms) indrplaid_a_ms_5<-col_indices(dlbcl_biclust,rplaid_a_ms_5) indrisa<-col_indices(dlbcl_biclust,risa) indrisa_1<-col_indices(dlbcl_biclust,risa_1) indropsm<-col_indices(dlbcl_biclust,ropsm) indrsamba_01<-col_indices(dlbcl_biclust,rsamba_01) indrsamba_05<-col_indices(dlbcl_biclust,rsamba_05) indrxmotif<-col_indices(dlbcl_biclust,rxmotif) indrbimax<-col_indices(dlbcl_biclust,rbimax) indrcc<-col_indices(dlbcl_biclust,rcc) indrplaid_t_ab<-col_indices(dlbcl_biclust,rplaid_t_ab) indrplaid_t_a<-col_indices(dlbcl_biclust,rplaid_t_a) indrspec<-col_indices(dlbcl_biclust,rspec) indrfloc<-col_indices(dlbcl_biclust,rfloc) save(indrfabia,indrfabias,indrfabiap,indrmfsc,indrplaid_ss,indrplaid_ms,indrplaid_ms_5,indrplaid_a_ss,indrplaid_a_ms,indrplaid_a_ms_5,indrisa,indrisa_1,indropsm,indrsamba_01,indrsamba_05,indrxmotif,indrbimax,indrcc,indrplaid_t_ab,indrplaid_t_a,indrspec,indrfloc,file="exp_dlbcl_ind_res.RData") write.table(t(as.vector(indrfabia)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =FALSE) write.table(t(as.vector(indrfabias)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrfabiap)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrmfsc)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_ss)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_ms)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_ms_5)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_a_ss)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_a_ms)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_a_ms_5)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrisa)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrisa_1)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indropsm)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrsamba_01)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrsamba_05)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrxmotif)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrbimax)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrcc)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_t_ab)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrplaid_t_a)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrspec)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE) write.table(t(as.vector(indrfloc)), file = "exp_dlbcl_in_res.txt", quote = FALSE, sep = "\t",row.names = FALSE,col.names = FALSE,append =TRUE)