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Get Significant Single Tissue Sqtls

Source: R/get_significant_single_tissue_sqtls.R
get_significant_single_tissue_sqtls.Rd

Retrieve Single Tissue sQTL Data.

  • This service returns single tissue sQTL data for the given genes, from a specified dataset.

  • Results may be filtered by tissue

  • By default, the service queries the latest GTEx release.

The retrieved data is split into pages with items_per_page entries per page

GTEx Portal API documentation.

Usage

get_significant_single_tissue_sqtls(
  gencodeIds = NULL,
  variantIds = NULL,
  tissueSiteDetailIds = NULL,
  datasetId = "gtex_v8",
  page = 0,
  itemsPerPage = getOption("gtexr.itemsPerPage"),
  .verbose = getOption("gtexr.verbose"),
  .return_raw = FALSE
)

Arguments

gencodeIds

A character vector of Versioned GENCODE IDs, e.g. c("ENSG00000132693.12", "ENSG00000203782.5").

variantIds

Character vector. Gtex variant IDs.

tissueSiteDetailIds

Character vector of IDs for tissues of interest. Can be GTEx specific IDs (e.g. "Whole_Blood"; use get_tissue_site_detail() to see valid values) or Ontology IDs.

datasetId

String. Unique identifier of a dataset. Usually includes a data source and data release. Options: "gtex_v8", "gtex_snrnaseq_pilot".

page

Integer (default = 0).

itemsPerPage

Integer (default = 250). Set globally to maximum value 100000 with options(list(gtexr.itemsPerPage = 100000)).

.verbose

Logical. If TRUE (default), print paging information. Set to FALSE globally with options(list(gtexr.verbose = FALSE)).

.return_raw

Logical. If TRUE, return the raw API JSON response. Default = FALSE

Value

A tibble. Or a list if .return_raw = TRUE.

See also

Other Static Association Endpoints: get_eqtl_genes(), get_fine_mapping(), get_independent_eqtl(), get_multi_tissue_eqtls(), get_significant_single_tissue_eqtls(), get_significant_single_tissue_eqtls_by_location(), get_significant_single_tissue_ieqtls(), get_significant_single_tissue_isqtls(), get_sqtl_genes()

Examples

# search by gene
get_significant_single_tissue_sqtls(gencodeIds = c(
  "ENSG00000065613.9",
  "ENSG00000203782.5"
))
#> 
#> ── Paging info ─────────────────────────────────────────────────────────────────
#> • numberOfPages = 1
#> • page = 0
#> • maxItemsPerPage = 250
#> • totalNumberOfItems = 176
#> # A tibble: 176 × 14
#>    snpId            pos snpIdUpper variantId  geneSymbol  pValue geneSymbolUpper
#>    <chr>          <int> <chr>      <chr>      <chr>        <dbl> <chr>          
#>  1 rs4636462  152442732 RS4636462  chr1_1524… LOR        7.71e-5 LOR            
#>  2 rs4845768  152442997 RS4845768  chr1_1524… LOR        6.57e-5 LOR            
#>  3 rs12069640 152444300 RS12069640 chr1_1524… LOR        7.13e-5 LOR            
#>  4 rs11803629 152445670 RS11803629 chr1_1524… LOR        1.81e-4 LOR            
#>  5 rs12125681 152445737 RS12125681 chr1_1524… LOR        1.81e-4 LOR            
#>  6 rs11205004 152446586 RS11205004 chr1_1524… LOR        1.81e-4 LOR            
#>  7 rs11579085 152447965 RS11579085 chr1_1524… LOR        1.81e-4 LOR            
#>  8 rs1885529  152448570 RS1885529  chr1_1524… LOR        1.81e-4 LOR            
#>  9 rs1885528  152448978 RS1885528  chr1_1524… LOR        1.81e-4 LOR            
#> 10 rs1885527  152449069 RS1885527  chr1_1524… LOR        1.81e-4 LOR            
#> # ℹ 166 more rows
#> # ℹ 7 more variables: datasetId <chr>, tissueSiteDetailId <chr>,
#> #   ontologyId <chr>, chromosome <chr>, gencodeId <chr>, nes <dbl>,
#> #   phenotypeId <chr>