R/internal_functions.r

In gonzolgarcia/svpluscnv: Integrative analyses of CNV segmentation and SV variant calls

#' Obtains interquantile average for a defined 'x' vector and both lower and upper quantiles
#' @param x numeric vector to compute interquantile average
#' @param lowQ lower quantile
#' @param upQ upper quantile
#' @return (numeric) the IQM value
#' @keywords statistics, interquartile 
#' @export
#' @examples
#' 
#' x <- rnorm(100)
#' IQM(x)


IQM <- function(x, lowQ=0.1, upQ=0.9){
    
    stopifnot(is.numeric(x))
    
    rx <- rank(x,ties.method ='random')
    qt1<-quantile(rx,lowQ)
    qt2<-quantile(rx,upQ)
    
    inter_quantile_mean <- mean(x[intersect(which(rx > qt1),which(rx < qt2))])
    
    return(inter_quantile_mean)
}


#' Obtains inter quantile standard deviation for a defined 'x' vector and both lower and upper quantiles
#' @param x numeric vector to compute interquantile standard deviation
#' @param lowQ lower quantile
#' @param upQ upper quantile
#' @return (numeric) the IQSD value
#' @keywords statistics, interquartile 
#' @export
#' @examples
#' 
#' x <- rnorm(100)
#' IQSD(x)


IQSD <- function(x,lowQ=0.1,upQ=0.9){
    stopifnot(is.numeric(x))
    
    rx <- rank(x,ties.method ='random')
    qt1<-quantile(rx,lowQ)
    qt2<-quantile(rx,upQ)
    
    inter_quantile_mean <- sd(x[intersect(which(rx > qt1),which(rx < qt2))])
    return(inter_quantile_mean)
    
}

#' Obtains inter quantile average for a defined 'x' vector and both lower and upper quantiles
#' @param x numeric vector 
#' @param pal color palette
#' @param limits numeric limit fr color mapping
#' @return a color vector graded according to x
#' @keywords color, number 
#' @export
#' @examples
#' 
#' x <- rnorm(100)
#' pal <- colorRampPalette(c("lightblue","white","salmon"))(256)
#' limits<-c(-1,1)
#' map2color(x,pal,limits)

map2color <- function(x, pal, limits=NULL){
    if(is.null(limits)) limits = range(x)
    return(pal[findInterval(x, seq(limits[1], limits[2], length.out = length(pal)+1), all.inside=TRUE)])
}



#' Generates n unique random character strings of a given length
#' @param n the number of unique random strings to return
#' @param strlen random string length
#' @return a vector of unique random character strings
#' @keywords random string
#' @export
#' @examples
#' # for reproducibility make sure to set the seed
#' set.seed(123456789)
#' createRandomString(1, 10)


createRandomString <- function(n=1, strlen=10){
    
    strlenchain <- strlen*n*2
    
    chain <- paste(sample(c(letters, LETTERS),strlenchain, replace=TRUE),collapse="")
    idresult <- strsplit(gsub(paste("(.{",strlen,"})",sep=""), "\\1 ", chain)," ")
    
    if(anyDuplicated(idresult[[1]]) != 0) stop("Repeated strings were produced; try modifying the 'seed' or increasing 'strlen'")
    
    return(idresult[[1]][1:n])
}



#' A function to order a list of chromosomes 
#' @param chrlist (character): a vector containing chromosome names (chr1, chr2...chrX,chrY  ) 
#' @return a character vector of sorted chromosomes
#' @keywords CNV, segmentation, genes
#' @export
#' @examples
#' 
#' d3gb.chr.lim(genome.v="hg19")
#' 

d3gb.chr.lim <- function(genome.v){
    
    stopifnot(genome.v %in% c("hg19","hg38","GRCh37","GRCh38"))
    
    if(genome.v %in% c("hg19","GRCh37")){ bands <- GRCh37.bands
    }else if(genome.v %in% c("hg38","GRCh38")){ bands <- GRCh38.bands}
    
    ends<- aggregate(end ~ chr, bands, max)
    ends<- ends[order(ends$chr),]
    ends<- ends[suppressWarnings(order(as.numeric(as.character(ends$chr)) )),]
    
    chr.lim <- data.table(paste("chr",ends$chr,sep=""),rep(0,length(ends)),ends$end)
    colnames(chr.lim) <-c("chrom","begin","end")
    
    return(chr.lim)
}

#' Given two lists with (or without common names) returns a combined list; if common names their values merged and returned as unique
#' @param x (list): input list 1
#' @param y (list): input list 2
#' @param fun (character): Either 'unique' or 'intersect' are accepted
#' @return (list) merged list from x and y 
#' @keywords merge lists 
#' @export
#' @examples
#' 
#' x <- sapply(letters[1:10], function(i) sample(1:10)[1:sample(2:10)[1]], simplify=FALSE )
#' y <- sapply(letters[5:15], function(i) sample(1:10)[1:sample(2:10)[1]], simplify=FALSE )
#' merge2lists(x,y)

merge2lists <- function(x,y,fun="unique"){

mergedList <- list()

if(fun == "unique"){
    for(i in unique(c(names(x),names(y)))){
        if(length(y[[i]]) == 0 & length(x[[i]]) > 0){
            mergedList[[i]] <- x[[i]]
        }else if(length(y[[i]]) > 0 & length(x[[i]]) == 0){
            mergedList[[i]] <- y[[i]]
        }else if(length(y[[i]]) > 0 & length(x[[i]]) > 0){
            mergedList[[i]] <- unique(c(x[[i]],y[[i]]))
        }
    }
}else if(fun == "intersect"){
    for(i in intersect(names(x),names(y)) ){
        commonElements <- intersect(x[[i]],y[[i]])
        if(length(commonElements) > 0){
            mergedList[[i]] <- commonElements
        }
    }
}else{
    stop(paste("Unknown function:",func) )
}

return(mergedList)

}