## code to prepare `geisha_expression` dataset goes here
library(tidyverse)
url <- 'http://geisha.arizona.edu/geisha/expression.txt'
expression <- readr::read_tsv(url, col_types = 'cccccccc', quote = '')
hh_stages <- c(as.character(as.roman(10:14)), as.character(c(1:44)))
geisha_expression <-
expression %>%
tidyr::separate_rows('stages', sep = ',') %>%
tidyr::separate_rows('locations', sep = ',\\s?') %>% # Use ',\\s?' instead of ', because of "Mesoderm, early"
dplyr::mutate(stages = factor(stages, levels = hh_stages)) %>%
dplyr::mutate(locations = gsub('[\"]', '', locations)) %>%
dplyr::rename(
stage = stages,
tissue = locations,
ncbi_gene_id = `Chicken NCBI gene ID`,
gene_name = `Chicken gene name`,
geisha_id = `GEISHA ID`,
birdbase_id = `BirdBase ID`,
ensembl_gene_id = `Ensembl ID`,
gene_ontology_id = `GO ids`
) %>%
dplyr::arrange(ncbi_gene_id, stage, tissue) %>%
dplyr::relocate(ncbi_gene_id, ensembl_gene_id, gene_name, stage, tissue, geisha_id, birdbase_id, gene_ontology_id)
usethis::use_data(geisha_expression, overwrite = TRUE)
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