al2na

require(data.table)
.structureAMPoutput<-function(data)
{  
  strand=rep("+",nrow(data))
  strand[data[,4]=="R"]="-"
  numCs=round(data[,5]*data[,6]/100)
  numTs=round(data[,5]*data[,7]/100)
  
  data.frame(chr=data[,2],start=data[,3],end=data[,3]
             ,strand=strand,coverage=data[,5],numCs=numCs,numTs=numTs)

al2na

# returns a matrix of mean methylation values for groups defined
# by treatment vector in the methylBase obj
meanMethGroup<-function(methylBase.obj,weighted=TRUE ){
  
  data=getData(methylBase.obj) # get data frame part of the object
  treatment=methylBase.obj@treatment # get the treatment vector from the object
  
  # create the the empty resulting matrix
  result=matrix(0,ncol=length(unique(methylBase.obj@treatment)) ,nrow=nrow(methylBase.obj)  )
  colnames(result)=paste('group',unique(treatment),sep='') # column names are from treatmet vector

al2na

#' function for making ideogram for differential methylation values
#' requires methylKit, ggbio and GenomicRanges
#'
#' @example
#' library(BSgenome)
#' library("BSgenome.Hsapiens.UCSC.hg18")
#' chr.len = seqlengths(Hsapiens)  # get chromosome lengths
#' # remove X,Y,M and random chromosomes
#' chr.len = chr.len[grep("_|M|X|Y", names(chr.len), invert = T)] 
#' 

al2na

.readTableFast<-function(filename,header=T,skip=0,sep="")
{
  tab5rows <- read.table(filename, header = header,skip=skip,sep=sep, 
                         nrows = 100,stringsAsFactors=FALSE)
  classes  <- sapply(tab5rows, class)
  classes[classes=="logical"]="character"
  return( read.table(filename, header = header,skip=skip,sep=sep, 
                     colClasses = classes)  )
}

al2na

subsetByChr<-function(methylRawList.obj,my.chr="chr21"){
  
  sub=lapply(methylRawList.obj, function(x) x[x$chr==my.chr]  )
  
 new("methylRawList",sub,treatment=methylRawList.obj@treatment)
  
  
}

my.chrs= unique(methylRawList.obj[[1]]$chr)

al2na

require(GenomicRanges)
require(Biostrings)


#' get OE ratio and GC content for a given set of DNAstrings
getOE.strset<-function(str.set)
{
  di.mat=dinucleotideFrequency(  str.set )
  a.mat =alphabetFrequency( str.set ,baseOnly=TRUE )
  exp=(a.mat[,2]*a.mat[,3])/width(str.set )

al2na

#' call primer3 for a given set of DNAstringSet object
#'
#' @param seq DNAstring object, one DNA string for the given amplicon
#' @param size_range default: '151-500'
#' @param Tm melting temprature parameters default:c(55,57,58)
#' @param name name of the amplicon in chr_start_end format
#' @param primer3 primer3 location
#' @param therme.param thermodynamic parameters folder
#' @param settings text file for parameters
#' @author Altuna Akalin modified Arnaud Krebs' original function

al2na

setGeneric("tileMethylCounts2", 
           function(object,win.size=1000,step.size=1000,cov.bases=0)
             standardGeneric("tileMethylCounts2") )

setMethod("tileMethylCounts2", signature(object="methylRaw"),
          function(object,win.size,step.size,cov.bases){
            
            g.meth =as(object,"GRanges")
            chrs   =as.character(unique(seqnames(g.meth)))
            widths =seqlengths(g.meth)

al2na

  require(data.table)
  require(QuasR)
 
# arguments:  
# proj: qProject object
# range: GRanges object with ONE!!!! range
# samp: sample.name
#
getCMethMatrix<-function(proj,range,samp){  
  Cs=qMeth(proj, query=range,mode="allC",reportLevel="alignment")

al2na

.libPaths("/work2/gschub/altuna/RlibsDev")
require(data.table)

summarizeScores<-function(loc.gr,score.gr,score.col){

  ov <- as.matrix(findOverlaps(loc.gr,score.gr))
  
  dt=data.table(id=ov[,1],score=values(score.gr)[ov[,2],which(names(values(score.gr))==score.col)])
  dt=dt[,list(av=mean(score)),by=id]