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R/parallelSignatureFinder.R
In geneSignatureFinder: A Gene-signatures finder tools
Defines functions
parallelSignatureFinder
parallelSignatureFinder <-
function(cpuCluster, startingGene,
logFileName = "",
coeffMissingAllowed = 0.75,
subsetToUse = 1:ncol(geData), zero = NULL) {
mmessage = FALSE
n <- nrow(geData)
m <- ncol(geData)
toExplore <- rep(FALSE, m)
toExplore[subsetToUse] <- TRUE
toExplore[startingGene] <- FALSE
# logFileName <- paste(logFileName, "SignatureFinderLog.txt", sep = "")
# cat(paste("Working on ", sum(toExplore), " genes observed on ", n, " samples.\n", sep = ""), file = logFileName, append = FALSE)
# cat(paste("Starting on ", ttime <- Sys.time(), "\n", sep = ""), file = logFileName, append = TRUE)
# cat(paste("Starting signature: ", paste(colnames(geData)[startingGene], collapse = ", "), ";\n", sep = ""), file = logFileName, append = TRUE)
message(paste("\n\nWorking on ", sum(toExplore), " genes observed on ", n, " samples.", sep = ""))
message(paste("Starting on ", ttime <- Sys.time(), sep = ""))
message(paste("Starting signature: ", paste(colnames(geData)[startingGene], collapse = ", " ), ";", sep = ""))
aClassify <- rep(NA, n)
ssignature <- startingGene
runs <- 0
result <- list()
result$signatureName <- (colnames(geData)[startingGene])[1]
result$startingSignature <- colnames(geData)[startingGene]
result$coeffMissingAllowed <- coeffMissingAllowed
####### aggiunto il 14/10/2013
result$zero <- zero
######## da rivedere; si attiva nel caso lo startingGene sia una sequenza
if(length(ssignature) > 1)
notMissing <- apply(!is.na(geData[, ssignature]), 1, sum) else
notMissing <- !is.na(geData[, ssignature])
notMissing <- notMissing > 0
#clusters <- classify(geData[notMissing, ssignature])$clusters
clusters <- classify(geData[, ssignature])$clusters
####### modificato il 14/10/2013; qua si verifichera' un errore se ci sono missing
####### perche' stData non risultera' allineata con i missing
clusters <- goodAndPoorClassification(clusters)
runningDistance <- survdiff(stData[notMissing] ~ clusters[notMissing])$chisq
result$startingTValue <- runningDistance
result$startingPValue <- 1 - pchisq(runningDistance, df = 1)
####### modificato il 14/10/2013;
#tmpClassification <- rep(NA, n)
#tmpClassification[notMissing] <- clusters
#result$startingClassification <- as.factor(tmpClassification)
#levels(result$startingClassification) <- c("good", "poor")
result$startingClassification <- clusters
#cat(paste("tValue = ", runningDistance, " (", result$startingPValue, ")\n", sep = ""), file = logFileName, append = TRUE)
message(paste("tValue = ", runningDistance, " (", result$startingPValue, ")\n", sep = ""))
####################### end: da rivedere
tmpTime <- Sys.time()
exitFromMain <- FALSE
repeat {#### MAIN LOOP #######################
if(mmessage) message(runs+1, " MAIN LOOP: ", exitFromMain)
if(exitFromMain) break
runs <- runs + 1
distances <- rep(0, m) #variato
nnrow = sum(toExplore)###<-
signatureToExplore <- matrix(ssignature,
ncol = length(ssignature),
nrow = nnrow,
byrow = TRUE)
signatureToExplore <- cbind(which(toExplore), signatureToExplore)
if(nnrow == 1) {###<-
distances[toExplore] <- tValueFun(signatureToExplore) ###<-
exitFromMain <- TRUE###<-
} else###<-
distances[toExplore] <- parApply(cpuCluster, signatureToExplore, 1, tValueFun, ###<-
coeffMissingAllowed = coeffMissingAllowed)###<-
#howManyCandidates <- sum(distances > runningDistance)
#message("sum(distances > runningDistance) = ", howManyCandidates)
#foundNewGene <- FALSE
exitFromInner <- FALSE
repeat {### INNER LOOP ##########################
if(mmessage) message("MAIN = ", runs, ", INNER LOOP: ", exitFromInner, " time: ", round(Sys.time() - tmpTime, 2))
if(exitFromInner) break
maxDistance <- max(distances) #variato
if(maxDistance >= runningDistance) { #variato
if(mmessage) message("if(maxDistance >= runningDistance), time: ", round(Sys.time() - tmpTime, 2))
candidate <- which(distances == maxDistance)
if(length(candidate) == 1) {
if(mmessage) message(" if(length(candidate) == 1), time: ", round(Sys.time() - tmpTime, 2), " ", candidate)
# qua si controlla se l'aggiunta dei candidati porta a gruppi degeneri
notMissing <- apply(!is.na(geData[, c(ssignature, candidate)]), 1, sum)
notMissing <- notMissing > floor(length(c(ssignature, candidate))^coeffMissingAllowed)
clusters <- classify(geData[notMissing, c(ssignature, candidate)])$clusters
checkOne <- (min(table(clusters)) > floor(0.1 * n))
# qua si controlla che le curve di sopravvivenza non si incrocino
sf0 <- survfit(stData[clusters == 1] ~ 1)$surv
sf1 <- survfit(stData[clusters == 2] ~ 1)$surv
checkTwo <- sum(fivenum(sf0) > fivenum(sf1))
checkTwo <- ((checkTwo == 0) | (checkTwo == 5))
#############################
#################################################################################
if(is.null(zero)) checks <- checkOne & checkTwo else {
mean1 <- mean(geData[clusters == 1, candidate])
mean2 <- mean(geData[clusters == 2, candidate])
checkThree <- (mean1- zero) * (mean2- zero) < 0
checks <- checkOne & checkTwo & checkThree
}
if(checks) {
if(mmessage) message("if(checks), time: ", round(Sys.time() - tmpTime, 2))
ssignature <- c(ssignature, candidate)
toExplore[ssignature] <- FALSE
runningDistance <- maxDistance
tmp <- paste("... improved signature: ",
paste(colnames(geData)[ssignature], collapse = ", "),
";\ntValue = ", runningDistance, " (",
1 - pchisq(runningDistance, df = 1), ")\n", sep = "")
message(tmp)
exitFromInner <- TRUE
} # end of if(checkOne & checkTwo & checkThree) {
} else { # if(length(candidate) == 1)
if(mmessage) message(" if(length(candidate) == 1) else, time: ", round(Sys.time() - tmpTime, 2))
if(length(candidate) > 0.01*m) {
if(mmessage) message(" if(length(candidate) > 0.01*m)")
exitFromInner <- TRUE
exitFromMain <- TRUE
break
}
tmpCandidate <- parallelFindBest(cpuCluster, runningDistance, ssignature, candidate)
if(length(tmpCandidate) > 0) {
if(mmessage) message("if(length(tmpCandidate) > 0), ", length(tmpCandidate), ", time: ", round(Sys.time() - tmpTime, 2))
tmp <- survdiff(stData ~ classify(geData[, c(ssignature, tmpCandidate)])$clusters)$chisq
if(tmp > runningDistance) {
if(mmessage) message(" if(tmp > runningDistance), time: ", round(Sys.time() - tmpTime, 2))
# controlli inseriti il 14/10/2013
################################################################################
clusters <- classify(geData[notMissing, c(ssignature, tmpCandidate)])$clusters
checkOne <- (min(table(clusters)) > floor(0.1 * n))
# qua si controlla che le curve di sopravvivenza non si incrocino
sf0 <- survfit(stData[clusters == 1] ~ 1)$surv
sf1 <- survfit(stData[clusters == 2] ~ 1)$surv
checkTwo <- sum(fivenum(sf0) > fivenum(sf1))
checkTwo <- ((checkTwo == 0) | (checkTwo == 5))
#############################
#################################################################################
if(is.null(zero)) checks <- checkOne & checkTwo else {
mean1 <- mean(geData[clusters == 1, tmpCandidate])
mean2 <- mean(geData[clusters == 2, tmpCandidate])
checkThree <- (mean1- zero) * (mean2- zero) < 0
checks <- checkOne & checkTwo & checkThree
}
if(checks) {
if(mmessage) message("if(checks), time: ", round(Sys.time() - tmpTime, 2))
#################################
candidate <- tmpCandidate
ssignature <- c(ssignature, candidate)
runningDistance <- tmp
toExplore[ssignature] <- FALSE
tmp <- paste("... improved signature: ",
paste(colnames(geData)[ssignature], collapse = ", "),
";\ntValue = ", runningDistance, " (",
1 - pchisq(runningDistance, df = 1), ")\n", sep = "")
message(tmp)
exitFromInner <- TRUE
} else {
if(mmessage) message("if(checks) else, time: ", round(Sys.time() - tmpTime, 2))
#toExplore[tmpCandidate] <- FALSE
distances[tmpCandidate] <- 0 #variato
}
#######################
} # end of if(tmp > runningDistance)
} # end of if(length(tmpCandidate) > 0)
} # end of if(length(candidate) == 1) else ...
distances[candidate] <- 0 #variato
} else { # if(maxDistance >= runningDistance)
exitFromInner <- TRUE
exitFromMain <- TRUE
} # end of if(maxDistance >= runningDistance) else
} ### END of INNER LOOP ###########
if(mmessage) message("END of INNER LOOP, time: ", round(Sys.time() - tmpTime, 2))
} ### END of MAIN LOOP ###########
if(mmessage) message("END of MAIN LOOP, time: ", round(Sys.time() - tmpTime, 2))
if(length(ssignature) > 1) {
notMissing <- apply(!is.na(geData[, ssignature]), 1, sum)
notMissing <- notMissing > floor(length(ssignature)^coeffMissingAllowed)
} else {
notMissing <- !is.na(geData[, ssignature]) + 0
notMissing <- notMissing > 0
}
clusters <- rep(NA, n)
clusters[notMissing] <- classify(geData[notMissing, ssignature])$clusters
clusters <- goodAndPoorClassification(clusters) # 08/04/2012
# tmp1 <- min(survfit(stData[clusters[notMissing] == 1]~ 1)$surv)
# tmp2 <- min(survfit(stData[clusters[notMissing] == 2]~ 1)$surv)
# if(tmp1 > tmp2) {
# clusters[notMissing][clusters[notMissing] == 1] <- 0
# clusters[notMissing][clusters[notMissing] == 2] <- 1
# } else clusters[notMissing][clusters[notMissing] == 2] <- 0
K <- length(ssignature)
result$signature <- colnames(geData)[ssignature]
result$tValue <- survdiff(stData[notMissing] ~ clusters[notMissing])$chisq
result$pValue <- 1-pchisq(result$tValue, df = 1)
result$signatureIDs <- ssignature
names(result$signatureIDs) <- result$signature
result$classification <- clusters#08/04/2012
#result$classification <- as.factor(clusters)
#levels(result$classification) <- c("good", "poor")
#cat(paste("\n\nfinal signature: ", paste(colnames(geData)[ssignature], collapse = " "), sep = ""), file = logFileName, append = TRUE)
#cat(paste("\ntValue = ", runningDistance, " (", 1 - pchisq(runningDistance, df = 1), ")\n", sep = ""), file = logFileName, append = TRUE)
#cat(paste("\nlength of the signature = ", length(ssignature), sep = ""), file = logFileName, append = TRUE)
#cat(paste("\nnumber of joint missing values = ", sum(!notMissing), " (", 100*round(sum(!notMissing)/n,2), "%)", sep = ""), file = logFileName, append = TRUE)
#cat(paste("\n\nEnd of computation at ", t2 <- Sys.time(), "; elapsed time: ", t2 - ttime, ".", sep = ""), file = logFileName, append = TRUE)
message(paste("final signature: ", paste(colnames(geData)[ssignature], collapse = " "), sep = ""))
message(paste("tValue = ", runningDistance, " (", 1 - pchisq(runningDistance, df = 1), ")\n", sep = ""))
message(paste("length of the signature = ", length(ssignature), sep = ""))
message(paste("number of joint missing values = ", sum(!notMissing), " (", 100*round(sum(!notMissing)/n,2), "%)", sep = ""))
message(paste("End of computation at ", t2 <- Sys.time(), "; elapsed time: ", t2 - ttime, ".\n\n", sep = ""))
return(result)
}
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geneSignatureFinder documentation built on May 2, 2019, 2:32 p.m.
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Defines functions parallelSignatureFinder
parallelSignatureFinder <-
function(cpuCluster, startingGene,
logFileName = "",
coeffMissingAllowed = 0.75,
subsetToUse = 1:ncol(geData), zero = NULL) {
mmessage = FALSE
n <- nrow(geData)
m <- ncol(geData)
toExplore <- rep(FALSE, m)
toExplore[subsetToUse] <- TRUE
toExplore[startingGene] <- FALSE
# logFileName <- paste(logFileName, "SignatureFinderLog.txt", sep = "")
# cat(paste("Working on ", sum(toExplore), " genes observed on ", n, " samples.\n", sep = ""), file = logFileName, append = FALSE)
# cat(paste("Starting on ", ttime <- Sys.time(), "\n", sep = ""), file = logFileName, append = TRUE)
# cat(paste("Starting signature: ", paste(colnames(geData)[startingGene], collapse = ", "), ";\n", sep = ""), file = logFileName, append = TRUE)
message(paste("\n\nWorking on ", sum(toExplore), " genes observed on ", n, " samples.", sep = ""))
message(paste("Starting on ", ttime <- Sys.time(), sep = ""))
message(paste("Starting signature: ", paste(colnames(geData)[startingGene], collapse = ", " ), ";", sep = ""))
aClassify <- rep(NA, n)
ssignature <- startingGene
runs <- 0
result <- list()
result$signatureName <- (colnames(geData)[startingGene])[1]
result$startingSignature <- colnames(geData)[startingGene]
result$coeffMissingAllowed <- coeffMissingAllowed
####### aggiunto il 14/10/2013
result$zero <- zero
######## da rivedere; si attiva nel caso lo startingGene sia una sequenza
if(length(ssignature) > 1)
notMissing <- apply(!is.na(geData[, ssignature]), 1, sum) else
notMissing <- !is.na(geData[, ssignature])
notMissing <- notMissing > 0
#clusters <- classify(geData[notMissing, ssignature])$clusters
clusters <- classify(geData[, ssignature])$clusters
####### modificato il 14/10/2013; qua si verifichera' un errore se ci sono missing
####### perche' stData non risultera' allineata con i missing
clusters <- goodAndPoorClassification(clusters)
runningDistance <- survdiff(stData[notMissing] ~ clusters[notMissing])$chisq
result$startingTValue <- runningDistance
result$startingPValue <- 1 - pchisq(runningDistance, df = 1)
####### modificato il 14/10/2013;
#tmpClassification <- rep(NA, n)
#tmpClassification[notMissing] <- clusters
#result$startingClassification <- as.factor(tmpClassification)
#levels(result$startingClassification) <- c("good", "poor")
result$startingClassification <- clusters
#cat(paste("tValue = ", runningDistance, " (", result$startingPValue, ")\n", sep = ""), file = logFileName, append = TRUE)
message(paste("tValue = ", runningDistance, " (", result$startingPValue, ")\n", sep = ""))
####################### end: da rivedere
tmpTime <- Sys.time()
exitFromMain <- FALSE
repeat {#### MAIN LOOP #######################
if(mmessage) message(runs+1, " MAIN LOOP: ", exitFromMain)
if(exitFromMain) break
runs <- runs + 1
distances <- rep(0, m) #variato
nnrow = sum(toExplore)###<-
signatureToExplore <- matrix(ssignature,
ncol = length(ssignature),
nrow = nnrow,
byrow = TRUE)
signatureToExplore <- cbind(which(toExplore), signatureToExplore)
if(nnrow == 1) {###<-
distances[toExplore] <- tValueFun(signatureToExplore) ###<-
exitFromMain <- TRUE###<-
} else###<-
distances[toExplore] <- parApply(cpuCluster, signatureToExplore, 1, tValueFun, ###<-
coeffMissingAllowed = coeffMissingAllowed)###<-
#howManyCandidates <- sum(distances > runningDistance)
#message("sum(distances > runningDistance) = ", howManyCandidates)
#foundNewGene <- FALSE
exitFromInner <- FALSE
repeat {### INNER LOOP ##########################
if(mmessage) message("MAIN = ", runs, ", INNER LOOP: ", exitFromInner, " time: ", round(Sys.time() - tmpTime, 2))
if(exitFromInner) break
maxDistance <- max(distances) #variato
if(maxDistance >= runningDistance) { #variato
if(mmessage) message("if(maxDistance >= runningDistance), time: ", round(Sys.time() - tmpTime, 2))
candidate <- which(distances == maxDistance)
if(length(candidate) == 1) {
if(mmessage) message(" if(length(candidate) == 1), time: ", round(Sys.time() - tmpTime, 2), " ", candidate)
# qua si controlla se l'aggiunta dei candidati porta a gruppi degeneri
notMissing <- apply(!is.na(geData[, c(ssignature, candidate)]), 1, sum)
notMissing <- notMissing > floor(length(c(ssignature, candidate))^coeffMissingAllowed)
clusters <- classify(geData[notMissing, c(ssignature, candidate)])$clusters
checkOne <- (min(table(clusters)) > floor(0.1 * n))
# qua si controlla che le curve di sopravvivenza non si incrocino
sf0 <- survfit(stData[clusters == 1] ~ 1)$surv
sf1 <- survfit(stData[clusters == 2] ~ 1)$surv
checkTwo <- sum(fivenum(sf0) > fivenum(sf1))
checkTwo <- ((checkTwo == 0) | (checkTwo == 5))
#############################
#################################################################################
if(is.null(zero)) checks <- checkOne & checkTwo else {
mean1 <- mean(geData[clusters == 1, candidate])
mean2 <- mean(geData[clusters == 2, candidate])
checkThree <- (mean1- zero) * (mean2- zero) < 0
checks <- checkOne & checkTwo & checkThree
}
if(checks) {
if(mmessage) message("if(checks), time: ", round(Sys.time() - tmpTime, 2))
ssignature <- c(ssignature, candidate)
toExplore[ssignature] <- FALSE
runningDistance <- maxDistance
tmp <- paste("... improved signature: ",
paste(colnames(geData)[ssignature], collapse = ", "),
";\ntValue = ", runningDistance, " (",
1 - pchisq(runningDistance, df = 1), ")\n", sep = "")
message(tmp)
exitFromInner <- TRUE
} # end of if(checkOne & checkTwo & checkThree) {
} else { # if(length(candidate) == 1)
if(mmessage) message(" if(length(candidate) == 1) else, time: ", round(Sys.time() - tmpTime, 2))
if(length(candidate) > 0.01*m) {
if(mmessage) message(" if(length(candidate) > 0.01*m)")
exitFromInner <- TRUE
exitFromMain <- TRUE
break
}
tmpCandidate <- parallelFindBest(cpuCluster, runningDistance, ssignature, candidate)
if(length(tmpCandidate) > 0) {
if(mmessage) message("if(length(tmpCandidate) > 0), ", length(tmpCandidate), ", time: ", round(Sys.time() - tmpTime, 2))
tmp <- survdiff(stData ~ classify(geData[, c(ssignature, tmpCandidate)])$clusters)$chisq
if(tmp > runningDistance) {
if(mmessage) message(" if(tmp > runningDistance), time: ", round(Sys.time() - tmpTime, 2))
# controlli inseriti il 14/10/2013
################################################################################
clusters <- classify(geData[notMissing, c(ssignature, tmpCandidate)])$clusters
checkOne <- (min(table(clusters)) > floor(0.1 * n))
# qua si controlla che le curve di sopravvivenza non si incrocino
sf0 <- survfit(stData[clusters == 1] ~ 1)$surv
sf1 <- survfit(stData[clusters == 2] ~ 1)$surv
checkTwo <- sum(fivenum(sf0) > fivenum(sf1))
checkTwo <- ((checkTwo == 0) | (checkTwo == 5))
#############################
#################################################################################
if(is.null(zero)) checks <- checkOne & checkTwo else {
mean1 <- mean(geData[clusters == 1, tmpCandidate])
mean2 <- mean(geData[clusters == 2, tmpCandidate])
checkThree <- (mean1- zero) * (mean2- zero) < 0
checks <- checkOne & checkTwo & checkThree
}
if(checks) {
if(mmessage) message("if(checks), time: ", round(Sys.time() - tmpTime, 2))
#################################
candidate <- tmpCandidate
ssignature <- c(ssignature, candidate)
runningDistance <- tmp
toExplore[ssignature] <- FALSE
tmp <- paste("... improved signature: ",
paste(colnames(geData)[ssignature], collapse = ", "),
";\ntValue = ", runningDistance, " (",
1 - pchisq(runningDistance, df = 1), ")\n", sep = "")
message(tmp)
exitFromInner <- TRUE
} else {
if(mmessage) message("if(checks) else, time: ", round(Sys.time() - tmpTime, 2))
#toExplore[tmpCandidate] <- FALSE
distances[tmpCandidate] <- 0 #variato
}
#######################
} # end of if(tmp > runningDistance)
} # end of if(length(tmpCandidate) > 0)
} # end of if(length(candidate) == 1) else ...
distances[candidate] <- 0 #variato
} else { # if(maxDistance >= runningDistance)
exitFromInner <- TRUE
exitFromMain <- TRUE
} # end of if(maxDistance >= runningDistance) else
} ### END of INNER LOOP ###########
if(mmessage) message("END of INNER LOOP, time: ", round(Sys.time() - tmpTime, 2))
} ### END of MAIN LOOP ###########
if(mmessage) message("END of MAIN LOOP, time: ", round(Sys.time() - tmpTime, 2))
if(length(ssignature) > 1) {
notMissing <- apply(!is.na(geData[, ssignature]), 1, sum)
notMissing <- notMissing > floor(length(ssignature)^coeffMissingAllowed)
} else {
notMissing <- !is.na(geData[, ssignature]) + 0
notMissing <- notMissing > 0
}
clusters <- rep(NA, n)
clusters[notMissing] <- classify(geData[notMissing, ssignature])$clusters
clusters <- goodAndPoorClassification(clusters) # 08/04/2012
# tmp1 <- min(survfit(stData[clusters[notMissing] == 1]~ 1)$surv)
# tmp2 <- min(survfit(stData[clusters[notMissing] == 2]~ 1)$surv)
# if(tmp1 > tmp2) {
# clusters[notMissing][clusters[notMissing] == 1] <- 0
# clusters[notMissing][clusters[notMissing] == 2] <- 1
# } else clusters[notMissing][clusters[notMissing] == 2] <- 0
K <- length(ssignature)
result$signature <- colnames(geData)[ssignature]
result$tValue <- survdiff(stData[notMissing] ~ clusters[notMissing])$chisq
result$pValue <- 1-pchisq(result$tValue, df = 1)
result$signatureIDs <- ssignature
names(result$signatureIDs) <- result$signature
result$classification <- clusters#08/04/2012
#result$classification <- as.factor(clusters)
#levels(result$classification) <- c("good", "poor")
#cat(paste("\n\nfinal signature: ", paste(colnames(geData)[ssignature], collapse = " "), sep = ""), file = logFileName, append = TRUE)
#cat(paste("\ntValue = ", runningDistance, " (", 1 - pchisq(runningDistance, df = 1), ")\n", sep = ""), file = logFileName, append = TRUE)
#cat(paste("\nlength of the signature = ", length(ssignature), sep = ""), file = logFileName, append = TRUE)
#cat(paste("\nnumber of joint missing values = ", sum(!notMissing), " (", 100*round(sum(!notMissing)/n,2), "%)", sep = ""), file = logFileName, append = TRUE)
#cat(paste("\n\nEnd of computation at ", t2 <- Sys.time(), "; elapsed time: ", t2 - ttime, ".", sep = ""), file = logFileName, append = TRUE)
message(paste("final signature: ", paste(colnames(geData)[ssignature], collapse = " "), sep = ""))
message(paste("tValue = ", runningDistance, " (", 1 - pchisq(runningDistance, df = 1), ")\n", sep = ""))
message(paste("length of the signature = ", length(ssignature), sep = ""))
message(paste("number of joint missing values = ", sum(!notMissing), " (", 100*round(sum(!notMissing)/n,2), "%)", sep = ""))
message(paste("End of computation at ", t2 <- Sys.time(), "; elapsed time: ", t2 - ttime, ".\n\n", sep = ""))
return(result)
}
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