R/vegaMC.R

setGeneric("vegaMC", 
			function(dataset, output_file_name="output", beta=0.5, 
			min_region_bp_size=1000, correction=FALSE,
    	    loss_threshold=-0.2, gain_threshold=0.2, baf=TRUE,
    	    loh_threshold=0.75, loh_frequency=0.8, bs=1000,
    	    pval_threshold=0.05, html=TRUE, getGenes=TRUE,
    	    mart_database="ensembl",
    	    ensembl_dataset="hsapiens_gene_ensembl")
    	    standardGeneric("vegaMC"))

setMethod("vegaMC", "character", 
		function(dataset, output_file_name="output", 
		beta=0.5, min_region_bp_size=1000, correction=FALSE,
        loss_threshold=-0.2, gain_threshold=0.2, baf=TRUE,
        loh_threshold=0.75, loh_frequency=0.8, bs=1000,
        pval_threshold=0.05, html=TRUE, getGenes=TRUE,
        mart_database="ensembl",
        ensembl_dataset="hsapiens_gene_ensembl"){

    if(!file.exists(dataset)){
	message("ERROR: Specified Input File does not Exists")
	return(FALSE)
    }
    if( output_file_name == "" || 
	    substr(output_file_name, 
		nchar(output_file_name), nchar(output_file_name)) == "/" ){
	message("ERROR: Invalid Output File Name")
	return(FALSE)
    }
    n_samples=0
    n_probes=0
    n_chromosomes=0

    if(baf){
        baf = 1
    }else{
        baf=0
    }
    res <- .C("run_vegaMC", data=as.character(dataset),
            out=as.character(output_file_name),   
            b= as.double(beta),
            mrbs = as.integer(min_region_bp_size),
            losst = as.double(loss_threshold),
            gaint = as.double(gain_threshold),
            ba = as.integer(baf),
            loht = as.double(loh_threshold),
            lohf = as.double(loh_frequency),
            bsp = as.integer(bs),
            ns = as.integer(n_samples),
            np = as.integer(n_probes),
            nc = as.integer(n_chromosomes))

    n_samples = res$ns
    n_probes = res$np
    n_chromosomes = res$nc

    segmentation <- read.table(output_file_name, sep="\t",
                    header=TRUE, as.is=TRUE)
    segmentation <- as.matrix(segmentation)
    segmentation[which(is.nan(segmentation))] <- 0
    
    if(correction==TRUE){
	segmentation[,6] <- qvalue(as.numeric(segmentation[,6]))
	segmentation[,7] <- qvalue(as.numeric(segmentation[,7]))
	segmentation[,8] <- qvalue(as.numeric(segmentation[,8]))
    }
    segmentation[,6] <- round(as.numeric(segmentation[,6]), 5)
    segmentation[,7] <- round(as.numeric(segmentation[,7]), 5)
    segmentation[,8] <- round(as.numeric(segmentation[,8]), 5)
    

    f_l <- 
	as.numeric(segmentation[,9]) * abs(
		as.numeric(segmentation[,13]))/ as.numeric(segmentation[,12 ])
    f_g <- 
	as.numeric(segmentation[,10]) * abs(
		as.numeric(segmentation[,14]))/ as.numeric(segmentation[,12 ])
    f_loh<- 
	as.numeric(segmentation[,11]) * abs(
		as.numeric(segmentation[,15]))/ as.numeric(segmentation[,12 ])
    
    
    segmentation <- cbind(segmentation, f_l, f_g, f_loh)
    segmentation[which(is.nan(segmentation))] <- 0

    segmentation[,9] <- round(as.numeric(segmentation[,9])*100, 1)
    segmentation[,10] <- round(as.numeric(segmentation[,10])*100, 1)
    segmentation[,11] <- round(as.numeric(segmentation[,11])*100, 1)
    segmentation[,9] <- paste(as.numeric(segmentation[,9]), "%", sep="")
    segmentation[,10] <- paste(as.numeric(segmentation[,10]), "%", sep="")
    segmentation[,11] <- paste(as.numeric(segmentation[,11]), "%", sep="")
    colnames(segmentation)[12:18] <- c("Probe Size", "Loss Mean", "Gain Mean",
					"LOH Mean", "Focal-score Loss",
					"Focal-score Gain", "Focal-score LOH")
    write.table(segmentation, output_file_name, sep="\t", row.names=FALSE,
		col.names=TRUE, quote=FALSE, eol="\n")
   

    ## Creating the html file
    if(html==TRUE || getGenes==TRUE){
        js_file <- system.file("scripts/sorttable.js", package="VegaMC")
        logo <- system.file("template/image/bioinfologo.png",
                        package="VegaMC")
        ens <- system.file("template/image/ensemblicon.gif",
                        package="VegaMC")
        ## Get the output directory from output_file_name argument
        tmp_str <- unlist(strsplit(output_file_name, split=""))
        pos <- which(tmp_str=="/")
        if(length(pos)==0){
        file.copy(js_file, ".")
        file.copy(logo, ".")
        if(getGenes==TRUE){
            file.copy(ens, ".")
        }
    }else{
        file.copy(js_file, substr(output_file_name, 1,
                pos[length(pos)]))
        file.copy(logo, substr(output_file_name, 1,
                pos[length(pos)]))
        if(getGenes==TRUE){
            file.copy(ens, substr(output_file_name, 1,
                pos[length(pos)]))
        }
    }
       
       
    }

    if(html==TRUE){
        message("Creating HTML file '", paste(output_file_name,
                            ".html", sep=""), "'")
        createHTML(paste(output_file_name, ".html", sep=""), segmentation,
                pval_threshold, loss_threshold, gain_threshold,
                loh_frequency, loh_threshold, baf, n_samples,
                n_probes, 1:n_chromosomes, beta, min_region_bp_size,
                bs, getGenes, correction)
        message("Done\n")
    }

    if(getGenes==TRUE){
        message("Creating Gene Summary HTML file '",
        paste(output_file_name, "Genes.html", sep=""),"'")
        getGenes(paste(output_file_name, "Genes.html", sep=""),
                segmentation, pval_threshold, baf, ensembl_dataset,
                mart_database, html, correction)
        message("\nDone")
    }
    return(segmentation)   

}
)

Try the VegaMC package in your browser

Any scripts or data that you put into this service are public.

VegaMC documentation built on Nov. 8, 2020, 6:48 p.m.