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methylDBFunctions.R
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methylDBFunctions.R
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# Helper Functions ---------------------------------------------------
#' @noRd
## function checks wether a tabix file already exists and
## appends number if file already exists
.checkTabixFileExists <- function(tabixfile) {
message("\nchecking wether tabix file already exists:")
tabixfile <- paste0(tabixfile,".bgz")
message(tabixfile)
if(file.exists(tabixfile) ) {
message("tabix file already exists, renaming output file:")
i = 1
filename2 = tabixfile
while(file.exists(filename2) ) {
filename2 = gsub(".txt.bgz",paste0("_",i,".txt.bgz"),tabixfile)
i = i + 1
}
message(filename2)
tabixfile <- filename2
message(paste("HINT: consider using 'suffix' argument to write",
"different function calls to different files"))
} else message("tabix file is new.")
tabixfile <- gsub(".bgz","",tabixfile)
message("continuing now ...\n")
return(tabixfile)
}
# MethylRawDB and MethylRawListDB -----------------------------------------
# filterByCoverage --------------------------------------------------------
#' @aliases filterByCoverage,methylRawDB-method
#' @rdname filterByCoverage-methods
setMethod("filterByCoverage", signature(methylObj="methylRawDB"),
function(methylObj,lo.count,lo.perc,hi.count,hi.perc,chunk.size,
save.db=TRUE,...){
if( is.null(lo.count) & is.null(lo.perc) & is.null(hi.count) &
is.null(hi.perc) ){return(methylObj)}
if(save.db) {
filter <- function(data,lo.count,lo.perc,hi.count,hi.perc) {
.setMethylDBNames(data,"methylRawDB")
#figure out which cut-offs to use, maybe there is more elagent
# ways, quick&dirty works for now
if(is.numeric(lo.count) ){lo.count=lo.count}
if(is.numeric(lo.perc)){lo.count=quantile(data$coverage,lo.perc/100)}
if(is.numeric(hi.count)){hi.count=hi.count}
if(is.numeric(hi.perc)){hi.count=quantile(data$coverage,hi.perc/100)}
if(is.numeric(lo.count)){data=data[data$coverage>=lo.count,]}
if(is.numeric(hi.count)){data=data[data$coverage<hi.count,]}
return(data)
}
# catch additional args
args <- list(...)
dir <- dirname(methylObj@dbpath)
if( "dbdir" %in% names(args) ){
if( !(is.null(args$dbdir)) ){
dir <- .check.dbdir(args$dbdir)
}
}
if(!( "suffix" %in% names(args) ) ){
suffix <- paste0("_","filtered")
} else {
suffix <- paste0("_",args$suffix)
}
# filename <- paste0(paste([email protected],collapse = "_"),suffix,".txt")
# tabixfile
filename <- paste0(gsub(".txt.bgz",replacement = "",methylObj@dbpath),
suffix,".txt")
filename <- .checkTabixFileExists(filename)
filename <- basename(filename)
## creating the tabix header
slotList <- list(dbtype = "tabix",
sample.id = [email protected],
assembly = methylObj@assembly, context = methylObj@context,
resolution = methylObj@resolution)
tabixHead <- makeTabixHeader(slotList)
tabixHeadString <- .formatTabixHeader(class = "methylRawDB",
tabixHead = tabixHead)
newdbpath <- applyTbxByChunk(methylObj@dbpath,chunk.size = chunk.size,
dir=dir,filename = filename,
return.type = "tabix", FUN = filter,
lo.count=lo.count, lo.perc=lo.perc,
hi.count=hi.count, hi.perc=hi.perc,
tabixHead = tabixHeadString)
readMethylRawDB(dbpath = newdbpath,dbtype = "tabix",
sample.id = [email protected],
assembly = methylObj@assembly, context = methylObj@context,
resolution = methylObj@resolution)
} else {
methylObj <- methylObj[]
#print(class(methylObj))
filterByCoverage(methylObj,lo.count,lo.perc,hi.count,hi.perc,
chunk.size,save.db=FALSE,...)
}
})
#' @aliases filterByCoverage,methylRawListDB-method
#' @rdname filterByCoverage-methods
setMethod("filterByCoverage", signature(methylObj="methylRawListDB"),
function(methylObj,lo.count,lo.perc,hi.count,hi.perc,chunk.size,
save.db=TRUE,...){
if(save.db){
args <- list(...)
if( !( "dbdir" %in% names(args)) ){
dbdir <- NULL
} else { dbdir <- basename(.check.dbdir(args$dbdir)) }
new.list=lapply(methylObj,filterByCoverage,lo.count,lo.perc,hi.count,
hi.perc,chunk.size,save.db,dbdir=dbdir,...)
new("methylRawListDB", new.list,treatment=methylObj@treatment)
} else {
new.list=lapply(methylObj,filterByCoverage,lo.count,lo.perc,hi.count,
hi.perc,chunk.size,save.db=FALSE,...)
new("methylRawList", new.list,treatment=methylObj@treatment)
}
})
# getCoverageStats --------------------------------------------------------
#' @rdname getCoverageStats-methods
#' @aliases getCoverageStats,methylRawDB-method
setMethod("getCoverageStats", "methylRawDB",
function(object,plot,both.strands,labels,...,chunk.size){
tmp = applyTbxByChunk(object@dbpath,chunk.size = chunk.size,
return.type = "data.table",
FUN = function(x) {
.setMethylDBNames(x,"methylRawDB");
return(x[,c("strand","coverage"),with=FALSE])} )
if(!plot){
qts=seq(0,0.9,0.1) # get quantiles
qts=c(qts,0.95,0.99,0.995,0.999,1)
if(both.strands){
plus.cov=tmp[strand=="+",coverage]
mnus.cov=tmp[strand=="-",coverage]
cat("read coverage statistics per base\n\n")
cat("FORWARD STRAND:\n")
cat("summary:\n")
print( summary( plus.cov ) )
cat("percentiles:\n")
print(quantile( plus.cov,p=qts ))
cat("\n\n")
cat("REVERSE STRAND:\n")
cat("summary:\n")
print( summary( mnus.cov ) )
cat("percentiles:\n")
print(quantile( mnus.cov,p=qts ))
cat("\n")
}else{
all.cov=tmp[,coverage]
cat("read coverage statistics per base\n")
cat("summary:\n")
print( summary( all.cov ) )
cat("percentiles:\n")
print(quantile( all.cov,p=qts ))
cat("\n")
}
}else{
if(both.strands){
plus.cov=tmp[strand=="+",coverage]
mnus.cov=tmp[strand=="-",coverage]
par(mfrow=c(1,2))
if(labels){
a=hist(log10(plus.cov),plot=FALSE)
my.labs=as.character(round(100*a$counts/length(plus.cov),1))
}else{my.labs=FALSE}
hist(log10(plus.cov),col="chartreuse4",
xlab=paste("log10 of read coverage per",object@resolution),
main=paste("Histogram of", object@context,
"coverage: Forward strand"),
labels=my.labs,...)
mtext([email protected], side = 3)
if(labels){
a=hist(log10(mnus.cov),plot=FALSE)
my.labs=as.character(round(100*a$counts/length(mnus.cov),1))
}else{my.labs=FALSE}
a=hist(log10(mnus.cov),plot=FALSE)
hist(log10(mnus.cov),col="chartreuse4",
xlab=paste("log10 of read coverage per",object@resolution),
main=paste("Histogram of", object@context,
"coverage: Reverse strand"),
labels=my.labs,...)
mtext([email protected], side = 3)
}else{
all.cov=tmp[,coverage]
if(labels){
a=hist(log10(all.cov),plot=FALSE)
my.labs=as.character(round(100*a$counts/length(all.cov),1))
}else{my.labs=FALSE}
hist(log10(all.cov),col="chartreuse4",
xlab=paste("log10 of read coverage per",object@resolution),
main=paste("Histogram of", object@context, "coverage"),
labels=my.labs,...)
mtext([email protected], side = 3)
}
}
})
# getMethylationStats -----------------------------------------------------
#' @rdname getMethylationStats-methods
#' @aliases getMethylationStats,methylRawDB-method
setMethod("getMethylationStats", "methylRawDB",
function(object,plot,both.strands,labels,...,chunk.size){
numCs=coverage=strand=.=NULL
tmp = applyTbxByChunk(object@dbpath,chunk.size = chunk.size,
return.type = "data.table",
FUN = function(x) {
.setMethylDBNames(x,"methylRawDB");
return(x[,.(strand,coverage,numCs)])} )
plus.met=100* tmp[strand=="+",numCs/coverage]
mnus.met=100* tmp[strand=="-",numCs/coverage]
all.met =100* tmp[,numCs/coverage]
if(!plot){
qts=seq(0,0.9,0.1) # get quantiles
qts=c(qts,0.95,0.99,0.995,0.999,1)
if(both.strands){
cat("methylation statistics per base\n\n")
cat("FORWARD STRAND:\n")
cat("summary:\n")
print( summary( plus.met ) )
cat("percentiles:\n")
print(quantile( plus.met,p=qts ))
cat("\n\n")
cat("REVERSE STRAND:\n")
cat("summary:\n")
print( summary( mnus.met ) )
cat("percentiles:\n")
print(quantile( mnus.met,p=qts ))
cat("\n")
}else{
cat("methylation statistics per base\n")
cat("summary:\n")
print( summary( all.met ) )
cat("percentiles:\n")
print(quantile( all.met,p=qts ))
cat("\n")
}
}else{
if(both.strands){
par(mfrow=c(1,2))
if(labels){
a=hist((plus.met),plot=FALSE,...)
my.labs=as.character(round(100*a$counts/length(plus.met),1))
}else{my.labs=FALSE}
hist((plus.met),col="cornflowerblue",
xlab=paste("% methylation per",object@resolution),
main=paste("Histogram of %", object@context,
"methylation: Forward strand"),
labels=my.labs,...)
mtext([email protected], side = 3)
if(labels){
a=hist((mnus.met),plot=FALSE,...)
my.labs=as.character(round(100*a$counts/length(mnus.met),1))
}
else{my.labs=FALSE}
hist((mnus.met),col="cornflowerblue",
xlab=paste("% methylation per",object@resolution),
main=paste("Histogram of %", object@context,
"methylation: Reverse strand"),
labels=my.labs,...)
mtext([email protected], side = 3)
}else{
if(labels){
a=hist((all.met),plot=FALSE,...)
my.labs=as.character(round(100*a$counts/length(all.met),1))
}else{my.labs=FALSE}
hist((all.met),col="cornflowerblue",
xlab=paste("% methylation per",object@resolution),
main=paste("Histogram of %", object@context,"methylation"),
labels=my.labs,...)
mtext([email protected], side = 3)
}
}
})
# adjustMethylC -----------------------------------------------------------
#' @rdname adjustMethylC
#' @aliases adjustMethylC,methylRawDB,methylRawDB-method
setMethod("adjustMethylC", c("methylRawDB","methylRawDB"),
function(mc,hmc,save.db=TRUE,...,chunk.size){
if(save.db) {
lst=new("methylRawListDB",list(mc,hmc),treatment=c(1,0))
base=unite(lst)
adjust <- function(data) {
.setMethylDBNames(data,"methylBaseDB")
diff=(data$numCs1)-round(data$coverage1*(data$numCs2/data$coverage2))
diff[diff<0]=0
data$numCs1=diff
data$numTs1=data$coverage1-data$numCs1
return(data[1:7])
}
# catch additional args
args <- list(...)
dir <- dirname(mc@dbpath)
if( "dbdir" %in% names(args) ){
if( !(is.null(args$dbdir)) ){
dir <- .check.dbdir(args$dbdir)
}
}
if(!( "suffix" %in% names(args) ) ){
suffix <- paste0("_","adjusted")
} else {
suffix <- paste0("_",args$suffix)
}
# filename <- paste0(paste([email protected],collapse = "_"),suffix,".txt")
filename <- paste0(gsub(".txt.bgz",replacement = "",mc@dbpath),suffix,".txt")
filename <- .checkTabixFileExists(filename)
filename <- basename(filename)
## creating the tabix header
slotList <- list([email protected],
assembly=mc@assembly, context =mc@context,
resolution=mc@resolution,
dbtype = mc@dbtype)
tabixHead <- makeTabixHeader(slotList)
tabixHeadString <- .formatTabixHeader(class = "methylRawDB",
tabixHead = tabixHead)
newdbpath <- applyTbxByChunk(base@dbpath,chunk.size = chunk.size,
dir=dir,filename = filename,
return.type = "tabix", FUN = adjust,
tabixHead = tabixHeadString)
unlink(list.files(dirname(base@dbpath),
pattern = basename(gsub(".txt.bgz","",base@dbpath)),
full.names = TRUE))
readMethylRawDB(dbpath = newdbpath,[email protected],
assembly=mc@assembly, context =mc@context,
resolution=mc@resolution,
dbtype = mc@dbtype)
} else {
mc.tmp <- mc[]
hmc.tmp <- hmc[]
adjustMethylC(mc.tmp,hmc.tmp,save.db=FALSE,...)
}
})
#' @rdname adjustMethylC
#' @aliases adjustMethylC,methylRawListDB,methylRawListDB-method
setMethod("adjustMethylC", c("methylRawListDB","methylRawListDB"),
function(mc,hmc,save.db=TRUE,...,chunk.size){
# check lengths equal if not give error
if(length(mc) != length(hmc)){stop("lengths of methylRawList objects should be same\n")}
if(save.db){
args <- list(...)
if( !( "dbdir" %in% names(args)) ){
dbdir <- NULL
} else { dbdir <- basename(.check.dbdir(args$dbdir)) }
my.list=list()
for(i in 1:length(mc)){
my.list[[i]]=adjustMethylC(mc[[i]],hmc[[i]],save.db,
dbdir=dbdir,...,chunk.size)
}
new("methylRawListDB",my.list,treatment=mc@treatment )
} else {
my.list=list()
for(i in 1:length(mc)){
my.list[[i]]=adjustMethylC(mc[[i]],hmc[[i]],save.db=FALSE,...)
}
new("methylRawList",my.list,treatment=mc@treatment )
}
})
# normalizeCoverage -------------------------------------------------------
#' @rdname normalizeCoverage-methods
#' @aliases normalizeCoverage,methylRawListDB-method
setMethod("normalizeCoverage", "methylRawListDB",
function(obj,method,chunk.size,save.db=TRUE,...){
if( !(method %in% c("median","mean") ) )
{
stop("method option should be either 'mean' or 'median'\n")
}
if(save.db) {
normCov <- function(data,method) {
.setMethylDBNames(data)
if(method=="median"){
x=median(data$coverage)
}else {
x=mean(data$coverage)
}
sc.fac=max(x)/x #get scaling factor
all.cov=data$coverage
fCs =data$numCs/all.cov
fTs =data$numT/all.cov
data$coverage=round(sc.fac*data$coverage)
data$numCs =round(data$coverage*fCs)
data$numTs =round(data$coverage*fTs)
return(data)
}
# catch additional args
args <- list(...)
if( ( "dbdir" %in% names(args)) ){
# if(!(is.null(args$dbdir))) {
dir <- .check.dbdir(args$dbdir)
# }
} else {
dir <- dirname(obj[[1]]@dbpath)
}
if(!( "suffix" %in% names(args) ) ){
suffix <- paste0("_","normed")
} else {
suffix <- paste0("_",args$suffix)
}
outList <- list()
for(i in 1:length(obj)){
# filename <- paste0(paste(obj[[i]]@sample.id,collapse = "_"),
# suffix,".txt")
filename <- paste0(gsub(".txt.bgz",replacement = "",
obj[[i]]@dbpath),suffix,".txt")
filename <- .checkTabixFileExists(filename)
filename <- basename(filename)
## creating the tabix header
slotList <- list(sample.id=obj[[i]]@sample.id,
assembly=obj[[i]]@assembly,
context =obj[[i]]@context,
resolution=obj[[i]]@resolution,
dbtype = obj[[i]]@dbtype)
tabixHead <- makeTabixHeader(slotList)
tabixHeadString <- .formatTabixHeader(class = "methylRawDB",
tabixHead = tabixHead)
newdbpath <- applyTbxByChunk(obj[[i]]@dbpath,
chunk.size = chunk.size,
dir=dir,filename = filename,
return.type = "tabix",
FUN = normCov,method = method,
tabixHead = tabixHeadString)
outList[[i]] <- readMethylRawDB(dbpath = newdbpath,
sample.id=obj[[i]]@sample.id,
assembly=obj[[i]]@assembly,
context =obj[[i]]@context,
resolution=obj[[i]]@resolution,
dbtype = obj[[i]]@dbtype)
}
new("methylRawListDB",outList,treatment=obj@treatment)
} else {
# coerce methylRawDB to methylRaw
tmp.list <- lapply(obj,function(x) x[])
tmp <- new("methylRawList",tmp.list,treatment=obj@treatment)
normalizeCoverage(tmp,method,save.db=FALSE)
}
})
# reorganize --------------------------------------------------------------
#' @rdname reorganize-methods
#' @aliases reorganize,methylRawListDB-method
setMethod("reorganize", signature(methylObj="methylRawListDB"),
function(methylObj,sample.ids,treatment,chunk.size,save.db=TRUE,...){
#sample.ids length and treatment length should be equal
if(length(sample.ids) != length(treatment) ){
stop("length of sample.ids should be equal to treatment")
}
# get ids from the list of methylRaw
orig.ids=sapply(methylObj,function(x) [email protected])
if( ! all(sample.ids %in% orig.ids) ){
stop("provided sample.ids is not a subset of the sample ids of the object")
}
# get the column order in the original matrix
col.ord=order(match(orig.ids,sample.ids))[1:length(sample.ids)]
if(save.db) {
# catch additional args
args <- list(...)
outList=list()
# do not rename per default
suffix <- NULL
if( ("dbdir" %in% names(args)) | ( "suffix" %in% names(args) ) ) {
if( "suffix" %in% names(args) ) { suffix <- paste0("_",args$suffix) }
if( ( "dbdir" %in% names(args)) ){
dir <- .check.dbdir(args$dbdir)
for(i in 1:length(sample.ids)){
obj <- methylObj[[ col.ord[i] ]]
# filename <- paste0(dir,"/",paste([email protected],collapse = "_"),
# suffix,".txt.bgz")
filename <- paste0(dir,"/",gsub(".txt.bgz",replacement =
"",obj@dbpath),suffix,".txt.bgz")
filename <- .checkTabixFileExists(filename)
filename <- basename(filename)
file.copy(obj@dbpath,filename)
outList[[i]]=readMethylRawDB(dbpath = filename,
dbtype = obj@dbtype,
sample.id = [email protected],
assembly = obj@assembly,
context = obj@context,
resolution = obj@resolution)
}
} else {
for(i in 1:length(sample.ids)){
obj <- methylObj[[ col.ord[i] ]]
# filename <- paste0(dirname(obj@dbpath),paste([email protected],collapse = "_")
# ,suffix,".txt.bgz")
filename <- paste0(gsub(".txt.bgz",replacement = "",obj@dbpath),
suffix,".txt.bgz")
filename <- .checkTabixFileExists(filename)
filename <- basename(filename)
file.copy(obj@dbpath,filename)
outList[[i]]=readMethylRawDB(dbpath = filename,
dbtype = obj@dbtype,
sample.id = [email protected],
assembly = obj@assembly,
context = obj@context,
resolution = obj@resolution)
}
}
} else {
for(i in 1:length(sample.ids)){
outList[[i]]=methylObj[[ col.ord[i] ]]
}
}
new("methylRawListDB",outList,treatment=treatment)
} else {
outList=list()
for(i in 1:length(sample.ids)){
outList[[i]]=methylObj[[ col.ord[i] ]][]
}
new("methylRawList",outList,treatment=treatment)
}
})
# MethylBaseDB ------------------------------------------------------------
# unite -------------------------------------------------------------------
unite.methylRawListDB <- function(object,destrand=FALSE,min.per.group=NULL,
chunk.size=1e6,mc.cores=1,save.db=TRUE,...){
if(save.db) {
#check if assemblies,contexts and resolutions are same type NOT IMPLEMENTED
if( length(unique(vapply(object,function(x) x@context,FUN.VALUE="character"))) > 1)
{
stop("supplied methylRawList object have different methylation contexts:not all methylation events from the same bases")
}
if( length(unique(vapply(object,function(x) x@assembly,FUN.VALUE="character"))) > 1)
{
stop("supplied methylRawList object have different genome assemblies")
}
if( length(unique(vapply(object,function(x) x@resolution,FUN.VALUE="character"))) > 1)
{
stop("supplied methylRawList object have different methylation resolutions:some base-pair some regional")
}
if( (!is.null(min.per.group)) & ( ! is.integer( min.per.group ) ) )
{
stop("min.per.group should be an integer\ntry providing integers as 1L, 2L,3L etc.\n")
}
if( any(min.per.group > min(table(object@treatment))) )
{
stop("min.per.group can not be higher than number of samples in smallest group\n")
}
if(Sys.info()['sysname']=="Windows") {mc.cores = 1}
# destrand single objects contained in methylRawListDB
if(destrand) {
message("destranding...")
destrandFun <- function(obj){
if(obj@resolution == "base") {
dir <- dirname(obj@dbpath)
filename <- paste(gsub(".txt.bgz","",obj@dbpath),
"destrand.txt",sep="_")
# filename <- .checkTabixFileExists(filename)
filename <- basename(filename)
## creating the tabix header
slotList <- list(dbtype = "tabix",
sample.id = [email protected],
assembly = obj@assembly,
context = obj@context,
resolution = obj@resolution)
tabixHead <- makeTabixHeader(slotList)
tabixHeadString <- .formatTabixHeader(class = "methylRawDB",
tabixHead = tabixHead)
# need to use .CpG.dinuc.unifyOld because output needs to be ordered
newdbpath <- applyTbxByChunk(obj@dbpath,
chunk.size = chunk.size,
dir=dir,filename = filename,
return.type = "tabix",
FUN = function(x) {
.CpG.dinuc.unify(.setMethylDBNames(x,
"methylRawDB") )},
tabixHead = tabixHeadString)
readMethylRawDB(dbpath = newdbpath,dbtype = "tabix",
sample.id = [email protected],
assembly = obj@assembly, context = obj@context,
resolution = obj@resolution)
}else {obj}
}
new.list=suppressMessages(lapply(object,destrandFun))
object <- new("methylRawListDB", new.list,treatment=object@treatment)
on.exit(unlink(c(getDBPath(object),paste0(getDBPath(object),".tbi"))),add = TRUE)
}
#merge raw methylation calls together
message("uniting...")
objList <- getDBPath(object)
args <- list(...)
#print(args)
if( ( "dbdir" %in% names(args)) )
{
dir <- .check.dbdir(args$dbdir)
} else {
dir <- dirname(object[[1]]@dbpath)
}
# if(!( "dbtype" %in% names(args) ) ){
# dbtype <- "tabix"
# } else { dbtype <- args$dbtype }
if(!( "suffix" %in% names(args) ) ){
suffix <- NULL
} else {
suffix <- args$suffix
suffix <- paste0("_",suffix)
}
# filename will be "methylBase" concatenated with either 13-char random string or suffix
filename <- paste0( dir, "/", ifelse(is.null(suffix),
yes = tempfile(pattern = "methylBase_",tmpdir = "."),
no = paste0("methylBase",suffix)),
".txt")
filename <- .checkTabixFileExists(filename)
# remove the "./" that tempfile prepends
filename <- basename(filename)
# filename <- tempfile(pattern = "methylBase",tmpdir = ".",fileext = ".txt")
#filename <- paste0(paste(getSampleID(object),collapse = "_"),".txt")
# get indices of coverage in the data frame
coverage.ind=seq(5,by=3,length.out=length(object))
numCs.ind =coverage.ind+1
numTs.ind =coverage.ind+2
slotList <- list(dbtype = object[[1]]@dbtype,
sample.ids = getSampleID(object),assembly = object[[1]]@assembly,
context = object[[1]]@context,resolution = object[[1]]@resolution,
coverage.index=coverage.ind,numCs.index=numCs.ind,numTs.index=numTs.ind,
treatment = object@treatment,destranded = destrand)
tabixHead <- makeTabixHeader(slotList)
tabixHeadString <- .formatTabixHeader(class = "methylBaseDB",
tabixHead = tabixHead)
if(is.null(min.per.group)) {
message("merging tabix files ...")
dbpath <- mergeTabix(tabixList = objList ,dir = dir,
filename = filename,mc.cores = mc.cores,
tabixHead = tabixHeadString)
dbpath <- gsub(".tbi","",dbpath)
} else {
# if the the min.per.group argument is supplied, remove the rows
# that doesn't have enough coverage
message("merging tabix files ...")
# keep rows with no matching in all samples
tmpPath <- mergeTabix(tabixList = objList ,dir = dir,
filename = paste0(filename,".tmp"),
mc.cores = mc.cores,all=TRUE,
tabixHead = tabixHeadString)
tmpPath <- gsub(".tbi","",tmpPath)
# get indices of coverage in the data frame
coverage.ind=seq(5,by=3,length.out=length(object))
filter <- function(df, coverage.ind, treatment,min.per.group){
df <- as.data.table(df)
for(i in unique(treatment) ){
my.ind=coverage.ind[treatment==i]
ldat = !is.na(df[,my.ind,with=FALSE])
if( is.null(dim(ldat)) ){ # if there is only one dimension
df=df[ldat>=min.per.group,]
}else{
df=df[rowSums(ldat)>=min.per.group,]
}
}
return(as.data.frame(df))
}
message("filter mincov per group ...")
dbpath <- applyTbxByChunk(tbxFile = tmpPath, chunk.size = chunk.size,
dir = dir, filename = filename,
return.type = "tabix", FUN = filter,
treatment=object@treatment, coverage.ind=coverage.ind,
min.per.group=min.per.group, tabixHead = tabixHeadString)
unlink(list.files(dirname(tmpPath),pattern = basename(gsub(".txt.bgz","",tmpPath)),full.names = TRUE))
}
obj <- tryCatch(expr = {
readMethylBaseDB(dbpath = dbpath,dbtype = object[[1]]@dbtype,
sample.ids = getSampleID(object),assembly = object[[1]]@assembly,
context = object[[1]]@context,resolution = object[[1]]@resolution,
treatment = object@treatment,destranded = destrand)
},
error = function(e) {
stop(sprintf("no %s were united. try adjusting 'min.per.group'.",
object[[1]]@resolution))
}
)
message(paste0("flatfile located at: ",obj@dbpath))
obj
} else {
obj <- object
class(obj) <- "methylRawList"
unite(obj,destrand,min.per.group,chunk.size,mc.cores,save.db=FALSE,...)
}
}
#' @rdname unite-methods
#' @aliases unite,methylRawListDB-method
setMethod("unite", "methylRawListDB",unite.methylRawListDB)
# getCorrelation ----------------------------------------------------------
#' @rdname getCorrelation-methods
#' @aliases getCorrelation,methylBaseDB-method
setMethod("getCorrelation", "methylBaseDB",
function(object,method,plot,nrow=2e6){
if(is.null(nrow)){
meth.fun <- function(data, numCs.index, numTs.index){
data[, numCs.index]/( data[,numCs.index] + data[,numTs.index] )
}
meth.mat = applyTbxByChunk(object@dbpath,return.type = "data.frame",
FUN = meth.fun, numCs.index = [email protected],
numTs.index = [email protected])
}else{
data = headTabix(object@dbpath,nrow=nrow,return.type = "data.frame")
meth.mat = data[, [email protected]]/( data[,[email protected]] +
data[,[email protected]] )
}
names(meth.mat)[email protected]
method <- match.arg(method)
print( cor(meth.mat,method=method) )
if(plot) {
.plotCorrelation(meth.mat = meth.mat,
title = paste(object@context, object@resolution ,method,"cor."),
method = method)
}
}
)
# reconstruct -------------------------------------------------------------
#' @rdname reconstruct-methods
#' @aliases reconstruct,methylBaseDB-method
setMethod("reconstruct",signature(mBase="methylBaseDB"),
function(methMat,mBase,chunk.size,save.db=TRUE,...){
if(save.db){
if(is.matrix(methMat) ) {
# check if indeed methMat is percent methylation matrix
if(min(methMat)<0 | max(methMat)>100 ){
stop("\nmake sure 'methMat' is percent methylation matrix ",
"(values between 0-100) \n")
}
# check if methMat is percent methylation matrix fitting to mBase
if(nrow(methMat) != [email protected] |
ncol(methMat) != length([email protected]) ){
stop("\nmethMat dimensions do not match number of samples\n",
"and number of bases in methylBase object\n")
}
rndFile=paste(sample(c(0:9, letters, LETTERS),9, replace=TRUE),collapse="")
matFile=paste(rndFile,"methMat.txt",sep="_")
.write.bed(methMat,matFile,quote=FALSE,col.names=FALSE,row.names=FALSE,
sep="\t")
methMat = matFile
} else {
# methMat can also be a file containing a percent methylation matrix
mat <- fread(methMat,header = FALSE)
# check if indeed methMat is percent methylation matrix
if(min(methMat)<0 | max(methMat)>100 ){
stop("\nmake sure 'methMat' is percent methylation matrix ",
"(values between 0-100) \n")
}
# check if methMat is percent methylation matrix fitting to mBase
if(nrow(mat) != [email protected] | ncol(mat) != length([email protected]) ){
stop("\nmethMat dimensions do not match number of samples\n",
"and number of bases in methylBase object\n")
}
rm(mat)
}
reconstr <- function(data, methMat, chunk, numCs.index, numTs.index) {
mat=data[,numCs.index]+data[,numTs.index]
methMat = read.table(methMat,header = FALSE, nrows = chunk, sep="\t")
# get new unmethylated and methylated counts
numCs=round(methMat*mat/100)
numTs=round((100-methMat)*mat/100)
data[,numCs.index]=numCs
data[,numTs.index]=numTs
return(data)
}
# catch additional args
args <- list(...)
if( !( "dbdir" %in% names(args)) ){
dir <- dirname(mBase@dbpath)
} else { dir <- .check.dbdir(args$dbdir) }
if(!( "suffix" %in% names(args) ) ){
suffix <- "_reconstructed"
} else {
suffix <- paste0("_",args$suffix)
}
# filename <- paste0(paste([email protected],collapse = "_"),suffix,".txt")
filename <- paste0(gsub(".txt.bgz","",mBase@dbpath),suffix,".txt")
filename <- .checkTabixFileExists(filename)
filename <- basename(filename)
con <- file(methMat,open = "r")