--- a
+++ b/R/Gene_Dictionary.R
@@ -0,0 +1,84 @@
+# 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")
\ No newline at end of file