gtexr.R
In gtexr: Query the GTEx Portal API

## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = Sys.getenv("IN_PKGDOWN") == "true"
)

## ----setup, message = FALSE---------------------------------------------------
# library(gtexr)
# library(dplyr)
# library(purrr)

## -----------------------------------------------------------------------------
# get_eqtl_genes("Whole_Blood")

## -----------------------------------------------------------------------------
# # to retrieve the first 3 pages, with default setting of 250 items per page
# 1:3 |>
#   map(\(page) get_eqtl_genes("Whole_Blood", page = page, .verbose = FALSE) |>
#         suppressWarnings()) |>
#   bind_rows()

## -----------------------------------------------------------------------------
# get_variant(snpId = "rs1410858") |>
#   tidyr::separate(
#     col = b37VariantId,
#     into = c(
#       "chromosome",
#       "position",
#       "reference_allele",
#       "alternative_allele",
#       "genome_build"
#     ),
#     sep = "_",
#     remove = FALSE
#   ) |>
#   select(snpId:genome_build)

## ----get-genes----------------------------------------------------------------
# get_genes("CRP") |>
#   select(geneSymbol, gencodeId)

## ----get-variant--------------------------------------------------------------
# get_variant(snpId = "rs1410858") |>
#   select(snpId, variantId)

## ----get-significant-single-tissue-eqtls--------------------------------------
# gene_symbol_of_interest <- "CRP"
# 
# gene_gencodeId_of_interest <- get_genes(gene_symbol_of_interest) |>
#   pull(gencodeId) |>
#   suppressMessages()
# 
# gene_gencodeId_of_interest |>
#   get_significant_single_tissue_eqtls() |>
#   distinct(geneSymbol, gencodeId, tissueSiteDetailId)

## ----calculate-eqtls----------------------------------------------------------
# variants_of_interest <- c("rs12119111", "rs6605071", "rs1053870")
# 
# variants_of_interest |>
#   set_names() |>
#   map(
#     \(x) calculate_expression_quantitative_trait_loci(
#       tissueSiteDetailId = "Liver",
#       gencodeId = "ENSG00000237973.1",
#       variantId = x
#     )
#   ) |>
#   bind_rows(.id = "rsid") |>
#   # optionally, reformat output - first extract genomic coordinates and alleles
#   tidyr::separate(
#     col = "variantId",
#     into = c(
#       "chromosome",
#       "position",
#       "reference_allele",
#       "alternative_allele",
#       "genome_build"
#     ),
#     sep = "_"
#   ) |>
#   # ...then ascertain alternative_allele frequency
#   mutate(
#     alt_allele_count = (2 * homoAltCount) + hetCount,
#     total_allele_count = 2 * (homoAltCount + hetCount + homoRefCount),
#     alternative_allele_frequency = alt_allele_count / total_allele_count
#   ) |>
#   select(
#     rsid,
#     beta = nes,
#     se = error,
#     pValue,
#     minor_allele_frequency = maf,
#     alternative_allele_frequency,
#     chromosome:genome_build,
#     tissueSiteDetailId
#   )