Get Significant Single Tissue Eqtls

Find significant single tissue eQTLs.

• This service returns precomputed significant single tissue eQTLs.

• Results may be filtered by tissue, gene, variant or dataset.

• To search by gene, use the versioned GENCODE ID.

• To search by variant, use the dbSNP rs ID (snpId).

By default, the service queries the latest GTEx release and the retrieved data is split into pages with items_per_page entries per page

GTEx Portal API documentation.

Usage

get_significant_single_tissue_eqtls(
  gencodeIds = NULL,
  variantIds = NULL,
  tissueSiteDetailIds = NULL,
  datasetId = "gtex_v8",
  page = 0,
  itemsPerPage = 250
)

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).

Value

A tibble.

Details

Note: although the GTEx Portal API documentation says to use the dbSNP rsID when searching by variant, this returns no results. Instead use gtex variant IDs e.g. use "chr1_153209640_C_A_b38" instead of "rs1410858".

See also

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

Examples

# \dontrun{
# search by gene
get_significant_single_tissue_eqtls(gencodeIds = c("ENSG00000132693.12",
                                                  "ENSG00000203782.5"))
#> 
#> ── Paging info ─────────────────────────────────────────────────────────────────
#> • numberOfPages = 1
#> • page = 0
#> • maxItemsPerPage = 250
#> • totalNumberOfItems = 249
#> # A tibble: 249 × 13
#>    snpId            pos snpIdUpper variantId  geneSymbol  pValue geneSymbolUpper
#>    <chr>          <int> <chr>      <chr>      <chr>        <dbl> <chr>          
#>  1 rs12128960 159343657 RS12128960 chr1_1593… CRP        8.52e-5 CRP            
#>  2 rs12132451 159344052 RS12132451 chr1_1593… CRP        7.92e-5 CRP            
#>  3 rs12136402 159347493 RS12136402 chr1_1593… CRP        7.92e-5 CRP            
#>  4 rs10908709 159350390 RS10908709 chr1_1593… CRP        7.92e-5 CRP            
#>  5 rs10908710 159351189 RS10908710 chr1_1593… CRP        7.92e-5 CRP            
#>  6 rs11265178 159359256 RS11265178 chr1_1593… CRP        9.62e-5 CRP            
#>  7 rs35532309 159360755 RS35532309 chr1_1593… CRP        6.11e-5 CRP            
#>  8 rs6692378  159369451 RS6692378  chr1_1593… CRP        1.17e-6 CRP            
#>  9 rs10908714 159370563 RS10908714 chr1_1593… CRP        1.80e-5 CRP            
#> 10 rs6656924  159372915 RS6656924  chr1_1593… CRP        1.00e-6 CRP            
#> # ℹ 239 more rows
#> # ℹ 6 more variables: datasetId <chr>, tissueSiteDetailId <chr>,
#> #   ontologyId <chr>, chromosome <chr>, gencodeId <chr>, nes <dbl>

# search by variant - must be variantId (not rsid)
get_significant_single_tissue_eqtls(variantIds = "chr1_153209640_C_A_b38")
#> 
#> ── Paging info ─────────────────────────────────────────────────────────────────
#> • numberOfPages = 1
#> • page = 0
#> • maxItemsPerPage = 250
#> • totalNumberOfItems = 2
#> # A tibble: 2 × 13
#>   snpId           pos snpIdUpper variantId   geneSymbol   pValue geneSymbolUpper
#>   <chr>         <int> <chr>      <chr>       <chr>         <dbl> <chr>          
#> 1 rs1410858 153209640 RS1410858  chr1_15320… LOR        5.47e- 5 LOR            
#> 2 rs1410858 153209640 RS1410858  chr1_15320… PRR9       5.35e-19 PRR9           
#> # ℹ 6 more variables: datasetId <chr>, tissueSiteDetailId <chr>,
#> #   ontologyId <chr>, chromosome <chr>, gencodeId <chr>, nes <dbl>

# filter by gene/variant and tissue site - either `gencodeIds` or `variantIds`
# should be supplied as a minimum
get_significant_single_tissue_eqtls(gencodeIds = c("ENSG00000132693.12",
                                                  "ENSG00000203782.5"),
                                    variantIds = "chr1_153209640_C_A_b38",
                                    tissueSiteDetailIds = "Whole_Blood")
#> 
#> ── Paging info ─────────────────────────────────────────────────────────────────
#> • numberOfPages = 1
#> • page = 0
#> • maxItemsPerPage = 250
#> • totalNumberOfItems = 1
#> # A tibble: 1 × 13
#>   snpId    pos snpIdUpper variantId geneSymbol  pValue geneSymbolUpper datasetId
#>   <chr>  <int> <chr>      <chr>     <chr>        <dbl> <chr>           <chr>    
#> 1 rs14… 1.53e8 RS1410858  chr1_153… LOR        5.47e-5 LOR             gtex_v8  
#> # ℹ 5 more variables: tissueSiteDetailId <chr>, ontologyId <chr>,
#> #   chromosome <chr>, gencodeId <chr>, nes <dbl>
# }