How to read gencode gtf file

analysis

how_to

Author

Haky Im

Published

April 27, 2023

Code

suppressMessages(library(tidyverse))
suppressMessages(library(glue))
PRE = "/Users/haekyungim/Library/CloudStorage/Box-Box/LargeFiles/imlab-data/data-Github/web-data"
SLUG="how-to-read-gencode-gtf-file" ## copy the slug from the header
bDATE='2023-04-27' ## copy the date from the blog's header here
DATA = glue("{PRE}/{bDATE}-{SLUG}")
if(!file.exists(DATA)) system(glue::glue("mkdir {DATA}"))
WORK=DATA

## move data to DATA
#tempodata=("~/Downloads/tempo/gwas_catalog_v1.0.2-associations_e105_r2022-04-07.tsv")
#system(glue::glue("cp {tempodata} {DATA}/"))

#system(glue("open {DATA}")) ## this will open the folder

install if necessary

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("rtracklayer")

Code

# Load the rtracklayer package
library(rtracklayer)

# Define the path to your GFF file
gff_file_path <- glue("{DATA}/gencode.v43.annotation.gff3.gz")

# Read the GFF file
gff_data <- import(gff_file_path, format = "gff3")

# Convert the GFF data to a data frame
gff_data_frame <- as.data.frame(gff_data)

# Display the first few rows of the data frame
head(gff_data_frame)

Code

"ENSG00000164308"

## all gene_id start with ENSG
table(substr(gff_data_frame$gene_id,1,4))
## all entries have a gene_id
dim(gff_data_frame)
## number of genes with positive vs negative strands

to load version 75 of ensembl

Code

library(biomaRt)

# mart <- useMart(biomart = "ENSEMBL_MART_ENSEMBL", 
#                 host = "https://dec2013.archive.ensembl.org", # This host corresponds to Ensembl version 75
#                 path = "/biomart/martservice")
mart <- useMart(biomart = "ENSEMBL_MART_ENSEMBL", 
                host = "https://feb2014.archive.ensembl.org", # This host corresponds to Ensembl version 75
                path = "/biomart/martservice")