other_documents/prepare_gene_lists.md

In romanhaa/cerebroApp: Interactive visualization of scRNA-seq data with Cerebro

How to generate lists of ribosomal and mitochondrial genes

What is needed: Gene annotation as GTF file for human and mouse. We use the one from GENCODE: https://www.gencodegenes.org/

library('tidyverse')

Human (hg38)

gtf <- rtracklayer::import('gencode.v27.annotation.gtf')

Mitochondrial genes

t <- gtf %>%
  as_tibble() %>%
  filter(
    type == 'gene',
    grepl(gene_name, pattern = '^MT-')
  )

t %>%
select(gene_name) %>%
distinct() %>%
write_tsv('genes_mt_hg_name.tsv.gz', col_names = FALSE)

t %>%
select(gene_id) %>%
distinct() %>%
write_tsv('genes_mt_hg_gencode_v27.tsv.gz', col_names = FALSE)

t %>%
select(gene_id) %>%
mutate(gene_id = gsub(gene_id, pattern = '\\.[0-9]{1,3}', replacement = '')) %>%
distinct() %>%
write_tsv('genes_mt_hg_ensembl.tsv.gz', col_names = FALSE)

Ribosomal genes

t <- gtf %>%
  as_tibble() %>%
  filter(
    type == 'gene',
    grepl(gene_name, pattern = '^RP[SL]')
  )

t %>%
select(gene_name) %>%
distinct() %>%
write_tsv('genes_ribo_hg_name.tsv.gz', col_names = FALSE)

t %>%
select(gene_id) %>%
distinct() %>%
write_tsv('genes_ribo_hg_gencode_v27.tsv.gz', col_names = FALSE)

t %>%
select(gene_id) %>%
mutate(gene_id = gsub(gene_id, pattern = '\\.[0-9]{1,3}', replacement = '')) %>%
distinct() %>%
write_tsv('genes_ribo_hg_ensembl.tsv.gz', col_names = FALSE)

Mouse (mm10)

gtf <- rtracklayer::import('gencode.vM16.comprehensive.CHR.gtf')

Mitochondrial genes

t <- gtf %>%
  as_tibble() %>%
  filter(
    type == 'gene',
    grepl(gene_name, pattern = '^mt-')
  )

t %>%
select(gene_name) %>%
distinct() %>%
write_tsv('genes_mt_mm_name.tsv.gz', col_names = FALSE)

t %>%
select(gene_id) %>%
distinct() %>%
write_tsv('genes_mt_mm_gencode_vM16.tsv.gz', col_names = FALSE)

t %>%
select(gene_id) %>%
mutate(gene_id = gsub(gene_id, pattern = '\\.[0-9]{1,3}', replacement = '')) %>%
distinct() %>%
write_tsv('genes_mt_mm_ensembl.tsv.gz', col_names = FALSE)

Ribosomal genes

t <- gtf %>%
  as_tibble() %>%
  filter(
    type == 'gene',
    grepl(gene_name, pattern = '^Rp[sl]')
  )

t %>%
select(gene_name) %>%
distinct() %>%
write_tsv('genes_ribo_mm_name.tsv.gz', col_names = FALSE)

t %>%
select(gene_id) %>%
distinct() %>%
write_tsv('genes_ribo_mm_gencode_vM16.tsv.gz', col_names = FALSE)

t %>%
select(gene_id) %>%
mutate(gene_id = gsub(gene_id, pattern = '\\.[0-9]{1,3}', replacement = '')) %>%
distinct() %>%
write_tsv('genes_ribo_mm_ensembl.tsv.gz', col_names = FALSE)

romanhaa/cerebroApp documentation built on Nov. 25, 2021, 5:29 p.m.