# Gene_Dictionary.R

if (!require(data.table)) {

    install.packages("data.table")

    library(data.table)

}

if (!require(biomaRt)) {

    BiocInstaller::biocLite("biomaRt")

    library(biomaRt)

}

if (!require(curl)) {

    install.packages("curl")

    library(curl)

}

# ==== Create a dictionary for all genes ====

# Load a gene expression file

exp_file <- get(load("Data/TCGA/SummarizedExperiments/Exp/TCGA-ACC_GeneExpression.rdata"))

all_genes <- rownames(exp_file)

# Use an older version of biomaRt to ensure hg19 coordinates are retrieved

ensembl_75 = useMart(

    biomart = "ENSEMBL_MART_ENSEMBL",

    host = "feb2014.archive.ensembl.org",

    path = "/biomart/martservice",

    dataset = "hsapiens_gene_ensembl"

)

atts <- listAttributes(ensembl_75, what = "name")

atts[grep(pattern = "gene", x = atts, ignore.case = T)]

atts[grep(pattern = "exon", x = atts, ignore.case = T)]

atts[grep(pattern = "location", x = atts, ignore.case = T)]

atts[grep(pattern = "entrez", x = atts, ignore.case = T)]

# Retrieve relevant attributes

length(all_genes)

dict <- biomaRt::getBM(attributes = c("ensembl_gene_id", "entrezgene",

                                      "external_gene_id",

                                      "gene_biotype",

                                      'chromosome_name', 'start_position',

                                      'end_position', 'strand'),

                       filters = "ensembl_gene_id", values = all_genes,

                       mart = ensembl_75)

dict_dt <- as.data.table(dict)

nrow(dict_dt)

t <- biomaRt::getBM(attributes = c("ensembl_gene_id", "ensembl_exon_id"),

                    filters = "ensembl_gene_id", values = all_genes,

                    mart = ensembl_75)

t <- as.data.table(t)

t[, exon_count := nrow(.SD), by = ensembl_gene_id]

exon_counts <- unique(t[, c("ensembl_gene_id", "exon_count")])

dict_dt <- merge(x = dict_dt, y = exon_counts)

fwrite(dict_dt, file = "Data/gene_dictionary.txt", sep = "\t")

# ==== Find the source of miRNAs ====

# Download miRNA data from mirBase

download.file(url = "ftp://mirbase.org/pub/mirbase/20/genomes/hsa.gff3",

              destfile = "mirbase_data_hsa.gff3")

mirbase <- fread("mirbase_data_hsa.gff3")

# Extract miRNA names

temp <- gsub(pattern = "Derives.*", replacement = "", x = mirbase$V9)

temp <- gsub(pattern = ".*Name=", replacement = "", x = temp)

temp <- gsub(pattern = ";", replacement = "", x = temp)

mirbase <-

    data.table(

        chr = mirbase$V1,

        start = mirbase$V4,

        end = mirbase$V5,

        name = temp,

        strand = mirbase$V7

    )

# Create a GRanges object

miRNA_gr <- makeGRangesFromDataFrame(

    df = mirbase,

    keep.extra.columns = F,

    seqnames.field = "chr",

    start.field = "start",

    end.field = "end",

    strand.field = "strand"

)

names(miRNA_gr) <- temp

# Save

saveRDS(miRNA_gr, "Human_miRNA_GRanges.rds")