data-raw/gene.R

In cancer-genomics/plasmasv: Methods for identification of tumor-specific structural variants in plasma

# wgEncodeGencodeBasicV19_hg19.txt: wgEncodeGencodeBasicV19 table from the UCSC genome browser for the hg19 genome build. Downloaded
# April 10, 2020 from https://genome.ucsc.edu/cgi-bin/hgTables with the following settings:
# clade: Mammal
# genome: Human
# assembly: Feb. 2009 (GRCh37/hg19)
# group: Genes and Gene Predictions
# track: GENCODE Genes V19
# table: Basic (wgEncodeGencodeBasicV19)
# When I clicked 'get output' I selected the option to link to the hg19.wgEncodeGencodeAttrsV19 table

library(GenomicRanges)

# Only including protein-coding genes
gene.df <- read.table("/dcl01/scharpf1/data/dbruhm/delfi_followup/split-reads/pcawg_analysis/data/raw_data/wgEncodeGencodeBasicV19_hg19.txt",
                      header = TRUE, stringsAsFactors = FALSE, comment.char = "", sep = "\t")
chrs <- paste0("chr", c(seq(1, 22, 1), "X", "Y"))
gene.df <- subset(gene.df, gene.df$hg19.wgEncodeGencodeBasicV19.chrom %in% chrs)
gene.df <- subset(gene.df, hg19.wgEncodeGencodeAttrsV19.geneType == "protein_coding")
gene.gr <- GRanges(seqnames = gene.df$hg19.wgEncodeGencodeBasicV19.chrom,
                   ranges = IRanges(start = gene.df$hg19.wgEncodeGencodeBasicV19.txStart,
                                    end = gene.df$hg19.wgEncodeGencodeBasicV19.txEnd))
gene.gr <- reduce(gene.gr)
gene <- gene.gr


save(gene, file = "/dcl01/scharpf1/data/dbruhm/delfi_followup/split-reads/pcawg_analysis/data/processed_data/gene.rda")