R/filterread_Trio_SVMerge.r

Defines functions run_bionano_filter_SVMerge_Trio

Documented in run_bionano_filter_SVMerge_Trio

#' Getting the data from annotated smaps to extract SV
#' information based on type of variants.
#'
#' @param input_fmt_geneList character. Choice of gene list input
#'        Text or Dataframe.
#' @param input_fmt_SV  character. Choice of gene list input
#'        Text or Dataframe.
#' @param smap  character. SV file name.
#' @param svData Dataframe Input data containing SV data.
#' @param dat_geneList Dataframe Input data containing geneList data.
#' @param fileName Character Name of file containing Gene List data.
#' @param outpath Character Directory to the output file.
#' @param outputFilename Character Output filename.
#' @param RZIPpath Character Path for the Rtools Zip package.
#' @param outputType Character. Variants in excel tabs or in different csv files.
#'        Options Excel or csv.
#' @param EnzymeType Character. Enzyme type used. Options SVMerge or SE.
#' @param fileprefix Character. fileprefix to use for each of the files in the directory.
#' @param directoryName Character. Directory name where individual SV files will be stored.
#' @param primaryGenesPresent boolean Checks whether the primary gene List is present or not.
#' @return Excel file containing the annotated SV map, tabs divided based on
#' type of SVs.
#' @examples
#' \dontrun{
#' smapName <- "GM24385_DLE-1_P_trio_hg19.smap"
#' outputFilename <- "GM24385_DLE-1_P_trio_hg19_out"
#' smappath <- system.file("extdata", smapName, package = "nanotatoR")
#' outpath <- system.file("extdata", smapName, package = "nanotatoR")
#' RZIPpath <- system.file("extdata", "zip.exe", package = "nanotatoR")
#' run_bionano_filter_SVMerge_Trio (input_fmt_geneList = c("Text"),
#' input_fmt_SV = c("Text"),
#' smap = smappath, 
#' dat_geneList = dat_geneList,
#' RZIPpath = RZIPpath, EnzymeType = c("SVMerge"),
#' outputType = c("Excel"),
#' primaryGenesPresent = FALSE, 
#' outputFilename = outputFilename,
#' outpath = outpath)#' }
#' @import openxlsx
#' @import hash
#' @importFrom stats na.omit
#' @export

run_bionano_filter_SVMerge_Trio <- function(
    input_fmt_geneList = c("Text", "dataFrame"), 
    input_fmt_SV = c("Text", "dataFrame"),
    EnzymeType = c("SVMerge", "SE"),
    smap = NULL, svData, dat_geneList, fileName, outpath,
    outputFilename = "", RZIPpath, primaryGenesPresent = TRUE,
    outputType = c("Excel", "csv"), directoryName, fileprefix) {
    # library(openxlsx)
    # library(hash)
    # setwd(path)##change the directory to your working directory
    Sys.setenv("R_ZIPCMD" = RZIPpath)
    ## GeneList Input Format
    
    ha <- hash()
    
    # ll<-list.files(pattern="txt")
        if(input_fmt_SV=="dataFrame"){
            smapdata = svData
            if(EnzymeType == "SVMerge"){
                #smapdata <- readSMap(smap, input_fmt_smap = "Text")
                SVID<-smapdata$SVIndex
            }
            else{
                #smapdata <- readSMap_DLE(smap, input_fmt_smap)
                SVID<-smapdata$SmapEntryID
            }
        }
        else if(input_fmt_SV=="Text"){
            if(EnzymeType == "SVMerge"){
                smapdata <- readSMap(smap, input_fmt_smap = "Text")
                SVID<-smapdata$SVIndex
            }
            else{
                smapdata <- readSMap_DLE(smap, input_fmt_smap = "Text")
                SVID<-smapdata$SmapEntryID
            }
        }
        else{
            stop("Input format for SMAP Incorrect")
        }
        r <- smapdata
        primaryGenesPresent = primaryGenesPresent
        if (primaryGenesPresent == TRUE){
            if (input_fmt_geneList == "Text") {
                rr <- read.table(fileName, header = TRUE)
            }
            else if (input_fmt_geneList == "dataFrame") {
                rr <- dat_geneList
            }
            else {
                stop("input_fmt_geneList Incorrect!!")
            }
    
    
            ogene <- as.character(r$OverlapGenes_strand_perc)
            upgene <- as.character(r$Upstream_nonOverlapGenes_dist_kb)
            dngene <- as.character(r$Downstream_nonOverlapGenes_dist_kb)
            # nogene<-c(upgene,dngene)
    
            ### OverlapGene
            dataPGOV <- overlappingGenes (rr, ogene)
            ### Non-Overlap Up-stream Gene
            dataPGUP <- nonOverlappingUPGenes (rr, upgene)
            ### Non-Overlap Down-stream Gene
            dataPGDN <- nonOverlappingDNGenes (rr, dngene)
            ### Non-OverlapDnGene
    
            # len<-length(pagene)-length(pg)
            # genesPG<-c(as.character(pg),rep("-",len))
            data <- data.frame(cbind(
                r, Overlap_PG = as.character(dataPGOV$pagene),
                Overlap_Terms = as.character(dataPGOV$pagene_term),
                Overlap_ClinicalSig = as.character(dataPGOV$pagene_clinSig),
                Non_Overlap_UP_PG = as.character(dataPGUP$nopageneup),
                Non_Overlap_UP_Terms = as.character(dataPGUP$nopageneup_term),
                Non_Overlap_UP_ClinicalSig = as.character(
                    dataPGUP$nopageneup_clinSig),
                Non_Overlap_DN_PG = as.character(dataPGDN$nopagenedn),
                Non_Overlap_DN_Terms = as.character(dataPGDN$nopagenedn_term),
                Non_Overlap_DN_ClinicalSig = as.character(
                    dataPGDN$nopagenedn_clinSig)))
                }else if (primaryGenesPresent == FALSE){
                    data <- smapdata
                }else {stop("primaryGenesPresent Incorrect!!")}
    ##
    data$BNG_Freq_Perc_Filtered<-gsub("-", 0, as.character(
    data$BNG_Freq_Perc_Filtered))
    data$BNG_Freq_Perc_UnFiltered<-gsub("-",0,as.character(
    data$BNG_Freq_Perc_UnFiltered))
    data$DGV_Freq_Perc<-as.numeric(data$DGV_Freq_Perc)
    data$Internal_Freq_Perc_Filtered<-as.numeric(
    data$Internal_Freq_Perc_Filtered)
    data$Internal_Freq_Perc_Unfiltered<-as.numeric(
        data$Internal_Freq_Perc_Unfiltered)
    data$BNG_Freq_Perc_Filtered<-as.numeric(data$BNG_Freq_Perc_Filtered)
    data$BNG_Freq_Perc_UnFiltered<-as.numeric(data$BNG_Freq_Perc_UnFiltered)
    data$DECIPHER_Frequency<-as.numeric(data$DECIPHER_Frequency)
    data$Type1<-as.character(data$Type1)
    data$Type2<-as.character(data$Type2)
    
    
    dat <- data[which(data$Type %in% "insertion"), ]
    dat1 <- data[which(data$Type %in% "deletion"), ]
    dat44 <- data[which(data$Type %in% "duplication"), ]
    dat45 <- data[which(data$Type %in% "duplication_split"), ]
    dat46 <- data[which(data$Type %in% "duplication_inverted"), ]
    dat_dup_rem<-rbind(dat44,dat45,dat46)
    dat_dup_rem_FINAL<-dat_dup_rem[which(((
        dat_dup_rem$Type %in% "duplication") 
        | (dat_dup_rem$Type %in% "duplication_split") 
        | (dat_dup_rem$Type %in% "duplication_inverted"))
        & (((dat_dup_rem$Fail_BSPQI_assembly_chimeric_score == "pass"
        & dat_dup_rem$Fail_BSSSI_assembly_chimeric_score == "pass") 
        | (dat_dup_rem$Fail_BSPQI_assembly_chimeric_score == "fail" 
        & dat_dup_rem$Fail_BSSSI_assembly_chimeric_score == "pass") 
        | (dat_dup_rem$Fail_BSPQI_assembly_chimeric_score == "pass" 
        & dat_dup_rem$Fail_BSSSI_assembly_chimeric_score == "fail")
        | (dat_dup_rem$Fail_BSPQI_assembly_chimeric_score == "pass"
        & dat_dup_rem$Fail_BSSSI_assembly_chimeric_score == "-")
        | (dat_dup_rem$Fail_BSPQI_assembly_chimeric_score == "-" 
        & dat_dup_rem$Fail_BSSSI_assembly_chimeric_score == "pass")))), ]
        
    dat3 <- rbind(dat1, dat, dat_dup_rem_FINAL)
    dat10 <- dat3[which(((dat3$Found_in_self_BSPQI_molecules == "yes"
        & dat3$Found_in_self_BSSSI_molecules == "yes") 
        | (dat3$Found_in_self_BSPQI_molecules == "no"
        & dat3$Found_in_self_BSSSI_molecules == "yes") 
        | (dat3$Found_in_self_BSPQI_molecules == "yes"
        & dat3$Found_in_self_BSSSI_molecules == "no") 
        | (dat3$Found_in_self_BSPQI_molecules == "yes"
        & dat3$Found_in_self_BSSSI_molecules == "-") 
        | (dat3$Found_in_self_BSPQI_molecules == "-" 
        & dat3$Found_in_self_BSSSI_molecules == "yes")) 
        & ((dat3$Found_in_parents_BSPQI_molecules == "none"
        & dat3$Found_in_parents_BSSSI_molecules == "none") 
        | (dat3$Found_in_parents_BSPQI_molecules == "none"
        & dat3$Found_in_parents_BSSSI_molecules == "-") 
        | (dat3$Found_in_parents_BSPQI_molecules == "-" 
        & dat3$Found_in_parents_BSSSI_molecules == "none"))), ]
        
    dat11 <- dat3[which(((dat3$Found_in_self_BSPQI_molecules == "yes" 
        & dat3$Found_in_self_BSSSI_molecules == "yes") 
        | (dat3$Found_in_self_BSPQI_molecules == "no" 
        & dat3$Found_in_self_BSSSI_molecules == "yes") 
        | (dat3$Found_in_self_BSPQI_molecules == "yes" 
        & dat3$Found_in_self_BSSSI_molecules == "no") 
        | (dat3$Found_in_self_BSPQI_molecules == "yes" 
        & dat3$Found_in_self_BSSSI_molecules == "-") 
        | (dat3$Found_in_self_BSPQI_molecules == "-" 
        & dat3$Found_in_self_BSSSI_molecules == "yes")) 
        & ((dat3$Found_in_parents_BSPQI_molecules == "both" 
        & dat3$Found_in_parents_BSSSI_molecules == "both") 
        | (dat3$Found_in_parents_BSPQI_molecules == "-" 
        & dat3$Found_in_parents_BSSSI_molecules == "both") 
        | (dat3$Found_in_parents_BSPQI_molecules == "both" 
        & dat3$Found_in_parents_BSSSI_molecules == "-") 
        | (dat3$Found_in_parents_BSPQI_molecules == "both" 
        & dat3$Found_in_parents_BSSSI_molecules == "mother") 
        | (dat3$Found_in_parents_BSPQI_molecules == "mother" 
        & dat3$Found_in_parents_BSSSI_molecules == "both") 
        | (dat3$Found_in_parents_BSPQI_molecules == "both" 
        & dat3$Found_in_parents_BSSSI_molecules == "father") 
        | (dat3$Found_in_parents_BSPQI_molecules == "father" 
        & dat3$Found_in_parents_BSSSI_molecules == "both"))),]
    dat12 <- dat3[which(((dat3$Found_in_self_BSPQI_molecules == "yes" 
        & dat3$Found_in_self_BSSSI_molecules == "yes") 
        | (dat3$Found_in_self_BSPQI_molecules == "no" 
        & dat3$Found_in_self_BSSSI_molecules == "yes") 
        | (dat3$Found_in_self_BSPQI_molecules == "yes" 
        & dat3$Found_in_self_BSSSI_molecules == "no") 
        | (dat3$Found_in_self_BSPQI_molecules == "yes" 
        & dat3$Found_in_self_BSSSI_molecules == "-") 
        | (dat3$Found_in_self_BSPQI_molecules == "-" 
        & dat3$Found_in_self_BSSSI_molecules == "yes")) 
        & ((dat3$Found_in_parents_BSPQI_molecules == "mother" 
        & dat3$Found_in_parents_BSSSI_molecules == "mother") 
        | (dat3$Found_in_parents_BSPQI_molecules == "-" 
        & dat3$Found_in_parents_BSSSI_molecules == "mother") 
        | (dat3$Found_in_parents_BSPQI_molecules == "mother" 
        & dat3$Found_in_parents_BSSSI_molecules == "-"))), ]
    dat13 <- dat3[which(((dat3$Found_in_self_BSPQI_molecules == "yes" 
        & dat3$Found_in_self_BSSSI_molecules == "yes") 
        | (dat3$Found_in_self_BSPQI_molecules == "no" 
        & dat3$Found_in_self_BSSSI_molecules == "yes") 
        | (dat3$Found_in_self_BSPQI_molecules == "yes" 
        & dat3$Found_in_self_BSSSI_molecules == "no") 
        | (dat3$Found_in_self_BSPQI_molecules == "yes" 
        & dat3$Found_in_self_BSSSI_molecules == "-") 
        | (dat3$Found_in_self_BSPQI_molecules == "-" 
        & dat3$Found_in_self_BSSSI_molecules == "yes")) 
        & ((dat3$Found_in_parents_BSPQI_molecules == "father" 
        & dat3$Found_in_parents_BSSSI_molecules == "father") 
        | (dat3$Found_in_parents_BSPQI_molecules == "-" 
        & dat3$Found_in_parents_BSSSI_molecules == "father") 
        | (dat3$Found_in_parents_BSPQI_molecules == "father" 
        & dat3$Found_in_parents_BSSSI_molecules == "-"))), ]
    dat14 <- rbind(dat12, dat13)
    
    gg <- grep("inversion", as.character(data$Type))
    dat8 <- data[gg, ]
    dat8 <- dat8[which(((dat8$Found_in_self_BSPQI_molecules == "yes"
        & dat8$Found_in_self_BSSSI_molecules == "yes") 
        | (dat8$Found_in_self_BSPQI_molecules == "no" 
        & dat8$Found_in_self_BSSSI_molecules == "yes") 
        | (dat8$Found_in_self_BSPQI_molecules == "yes" 
        & dat8$Found_in_self_BSSSI_molecules == "no") 
        | (dat8$Found_in_self_BSPQI_molecules == "yes" 
        & dat8$Found_in_self_BSSSI_molecules == "-") 
        | (dat8$Found_in_self_BSPQI_molecules == "-" 
        & dat8$Found_in_self_BSSSI_molecules == "yes")) 
        & ((dat8$Fail_BSPQI_assembly_chimeric_score == "pass" 
        & dat8$Fail_BSSSI_assembly_chimeric_score == "pass") 
        | (dat8$Fail_BSPQI_assembly_chimeric_score == "fail"
        & dat8$Fail_BSSSI_assembly_chimeric_score == "pass") 
        | (dat8$Fail_BSPQI_assembly_chimeric_score == "pass" 
        & dat8$Fail_BSSSI_assembly_chimeric_score == "fail")
        | (dat8$Fail_BSPQI_assembly_chimeric_score == "pass"
        & dat8$Fail_BSSSI_assembly_chimeric_score == "-")
        | (dat8$Fail_BSPQI_assembly_chimeric_score == "-" 
        & dat8$Fail_BSSSI_assembly_chimeric_score == "pass")
        )), ]
    gg1 <- grep("translocation", as.character(data$Type))
    dat7 <- data[gg1, ]
    dat7 <- dat7[which(((dat7$Found_in_self_BSPQI_molecules == "yes" 
        & dat7$Found_in_self_BSSSI_molecules == "yes") 
        | (dat7$Found_in_self_BSPQI_molecules == "no" 
        & dat7$Found_in_self_BSSSI_molecules == "yes") 
        | (dat7$Found_in_self_BSPQI_molecules == "yes" 
        & dat7$Found_in_self_BSSSI_molecules == "no") 
        | (dat7$Found_in_self_BSPQI_molecules == "yes" 
        & dat7$Found_in_self_BSSSI_molecules == "-") 
        | (dat7$Found_in_self_BSPQI_molecules == "-" 
        & dat7$Found_in_self_BSSSI_molecules == "yes")) 
        & ((dat7$Fail_BSPQI_assembly_chimeric_score == "pass"
        & dat7$Fail_BSSSI_assembly_chimeric_score == "pass") 
        | (dat7$Fail_BSPQI_assembly_chimeric_score == "fail" 
        & dat7$Fail_BSSSI_assembly_chimeric_score == "pass")
        | (dat7$Fail_BSPQI_assembly_chimeric_score == "pass" 
        & dat7$Fail_BSSSI_assembly_chimeric_score == "fail")
        | (dat7$Fail_BSPQI_assembly_chimeric_score == "pass"
        & dat7$Fail_BSSSI_assembly_chimeric_score == "-")
        | (dat7$Fail_BSPQI_assembly_chimeric_score == "-" 
        & dat7$Fail_BSSSI_assembly_chimeric_score == "pass"))), ]
    dat6 <- data[which(data$Type %in% "MisMatch"), ]
    dat14 <- rbind(dat12, dat13)
    ovrlapPG <- which(!((as.character(data$Overlap_PG)=="-")))
    datovrlapPG <- data[ovrlapPG,]
    nonovrlapupPG <- which(!((as.character(data$Non_Overlap_UP_PG)=="-")))
    datnonovrlapUPPG <- data[nonovrlapupPG,]
    nonovrlapdnPG <- which(!((as.character(data$Non_Overlap_DN_PG)=="-")))
    datnonovrlapDNPG <- data[nonovrlapdnPG,]
    datOvrLap <- rbind(datovrlapPG,datnonovrlapUPPG,datnonovrlapDNPG)
    
    'list_of_datasets <- list(
    "all" = data, "indel_dup_denovo" = dat10,
    "indel_dup_both" = dat11,
    "indel_dup_mother" = dat12, "indel_dup_father" = dat13,
    "indel_dup_cmpdHET" = dat14, "inv" = dat8, "trans" = dat7, "mismatch" = dat6,
    "all_PG_OV" = datovrlapPG, "all_PG_Non_OV_UP" = datnonovrlapUPPG,"all_PG_Non_OV_DN" = datnonovrlapDNPG
    )'
        if (outputType == "Excel"){
            list_of_datasets <- list(
            "indel_dup_denovo" = dat10,
            "indel_dup_both" = dat11, "indel_dup_cmpdHET" = dat14,
            "inv" = dat8, "trans" = dat7,
            "indel_dup_mother" = dat12, "indel_dup_father" = dat13,
            "all_PG_OV" = datOvrLap, "mismatch" = dat6, "all" = data
            )
            fname <- paste(outputFilename, ".xlsx", sep = "")
            write.xlsx(list_of_datasets, file = file.path(outpath, fname), keepNA = TRUE)
        } else if (outputType == "csv"){
            write.csv(dat10, file.path(directoryName, paste(
                fileprefix,"_indel_dup.csv",sep = "")), row.names = FALSE)
            write.csv(dat11, file.path(directoryName, paste(
                fileprefix,"_indel_dup_both.csv",sep = "")), row.names = FALSE)
            write.csv(dat14, file.path(directoryName, paste(
                fileprefix,"_indel_dup_cmpdHET.csv",sep = "")), row.names = FALSE)
            write.csv(dat8, file.path(directoryName, paste(
                fileprefix,"_inv.csv",sep = "")), row.names = FALSE)
            write.csv(dat7, file.path(directoryName, paste(
                fileprefix,"_trans.csv",sep = "")), row.names = FALSE)
            write.csv(dat12, file.path(directoryName, paste(
                fileprefix,"_indel_dup_mother.csv",sep = "")), row.names = FALSE)
            write.csv(dat13, file.path(directoryName, paste(
                fileprefix,"_indel_dup_father.csv",sep = "")), row.names = FALSE)
            write.csv(datOvrLap, file.path(directoryName, paste(
                fileprefix,"_all_PG_OV.csv",sep = "")), row.names = FALSE)
            write.csv(dat6, file.path(directoryName, paste(
                fileprefix,"_mismatch.csv",sep = "")), row.names = FALSE)
            write.csv(data, file.path(directoryName, paste(
                fileprefix,"_all.csv",sep = "")), row.names = FALSE)
        } else {stop(" outputType incorrect !!")}
    
    
    
    # gg<-grep("inversion",as.character(data$Type))
    # dat8<-data[gg,]
    # gg1<-grep("translocation",as.character(data$Type))
    # dat7<-data[gg1,]
    # dat6<-data[which(data$Type %in% "MisMatch"),]
    # list_of_datasets <- list("all" = data, "indel" = dat3, "indel_denovo"= dat10, "indel_both"= dat11,
    #"indel_mother"= dat12, "indel father"= dat13, "indel_cmpdHET"=dat14, "inv"= dat8, "trans"=dat7, "mismatch"=dat6,
    # "all_PG_OV"=data, "all_PG_Non_OV"= data)
    # st1<-strsplit(smap,".txt")[[1]][1]
    
    }
    
    
    ### Running the code
    ### Copy this 1 line at a time without the hash (#)
    ### Warning1: Don't remove the # from before the command from filterread.r
    ### Warning2: give the fullpath with filename for theR code
    # source("Z:\\bionano\\Test_R_Codes\\filterread.r")##path of where the Rcode is
    #
    # run_bionano_filter(path,smap,fileName)
    
VilainLab/nanotatoR documentation built on Aug. 3, 2024, 12:46 a.m.