#' ArrangeData_gt
#'
#' Reads in a directory of VCF files and converts them into a single dataframe
#'
#' @name ArrangeData_gt
#' @param vardir Directory path containing vcf files
#' @param ntlist Nucleotides (default ("A", "T", "G", "C") used for finding multiple alt alleles
#' @param annotated Whether the vcf files have been annotated using snpeff "yes" or "no" (default "yes")
#' @return A large dataframe containing information for all input vcf files.
#' @export
#' @examples
#' df = ArrangeData_gt(vardir, ntlist = c('A','G','T','C'), annotated = 'yes')
ArrangeData_gt = function(vardir, ntlist=c('A','G','T','C'), annotated = 'yes'){

    filelist = Sys.glob(glue("{vardir}*.vcf"))

    message("Length of input files: ", length(filelist))

    message("Input vcf files include: ", list(filelist))

    all_files = data.frame()  # empty df to build to

    for (filename in filelist){

        samplename = basename(file_path_sans_ext(filename)) # grab sample name to append later

        message("Sample name is: ", samplename)

        vcf_all = read.vcfR(file=filename)  # read in vcf file using vcfR

        vcf_tidy = vcfR2tidy(vcf_all)  # change into a tidy dataframe

        if (annotated == 'yes'){

          # $fix contains the INFO fields
          vcf_fix = vcf_tidy$fix %>% select('ChromKey','CHROM','POS','ID','REF','ALT','ANN')

        } else(
          # $fix contains the INFO fields
          vcf_fix = vcf_tidy$fix %>% select('ChromKey','CHROM','POS','ID','REF','ALT')
        )

        # $gt contains the genotype information. grab info we want
        vcf_gt = vcf_tidy$gt %>% select("ChromKey","POS","gt_AD","gt_DP")

        vcf_total = merge(vcf_fix, vcf_gt, by = c("ChromKey","POS"), all= TRUE)

        # if variants exist
        if (nrow(vcf_total>0)){

            vcf_total$sample = samplename

            snp_df = vcf_total %>% filter(REF %in% ntlist & ALT %in% ntlist) # only one ref and alt allele

            snp_df = snp_df %>% separate(gt_AD, c("REF_COUNT","ALT_COUNT"), sep = '[,]') # IT WILL THROW AN ERROR IF THERE ARE MULT ALLELES

            mult_alt = vcf_total %>% filter(REF %in% ntlist & !ALT %in% ntlist)  # mult alt alleles - need to use later!!

            if (nrow(snp_df) > 0){

                # one reference, one alt
                snp_df$REF_COUNT = as.numeric(as.character(snp_df$REF_COUNT))  # change to numeric to calc freq

                snp_df$ALT_COUNT = as.numeric(as.character(snp_df$ALT_COUNT))

                snp_df$REF_FREQ = snp_df$REF_COUNT/snp_df$gt_DP

                snp_df$ALT_FREQ = snp_df$ALT_COUNT/snp_df$gt_DP

                snp_df$ALT_TYPE <- ifelse(snp_df$ALT_FREQ < 0.50,
                        "minor","major")

                all_files = rbind(all_files, snp_df)

                } else(print("No snps for sample: ", samplename))

            }else(print(glue("No variant data: ", samplename)))

        }

    # rearranging the df
    all_files = all_files %>% mutate(majorfreq = ifelse(ALT_TYPE == 'major', ALT_FREQ, REF_FREQ),
                                         minorfreq = ifelse(ALT_TYPE == 'minor', ALT_FREQ, REF_FREQ),
                                         major = ifelse(ALT_TYPE == 'major', ALT, REF),
                                         minor = ifelse(ALT_TYPE == 'minor', ALT, REF))

    all_files = all_files[!duplicated(all_files), ] %>% droplevels()

    return(all_files)
}