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Get Sqtl Genes

Source: R/get_sqtl_genes.R
get_sqtl_genes.Rd

Retrieve sGenes (sQTL Genes).

  • This service returns sGenes (sQTL Genes) from the 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_sqtl_genes(
  tissueSiteDetailIds = NULL,
  datasetId = "gtex_v8",
  page = 0,
  itemsPerPage = getOption("gtexr.itemsPerPage"),
  .verbose = getOption("gtexr.verbose"),
  .return_raw = FALSE
)

Arguments

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_significant_single_tissue_sqtls()

Examples

get_sqtl_genes("Whole_Blood")
#> Warning: ! Total number of items (3013) exceeds the selected maximum page size (250).
#> ✖ 2763 items were not retrieved.
#> ℹ To retrieve all available items, increase `itemsPerPage`, ensuring you reuse
#>   your original query parameters e.g.
#>   `get_sqtl_genes(<your_existing_parameters>, itemsPerPage = 100000)`
#> ℹ Alternatively, adjust global "gtexr.itemsPerPage" setting e.g.
#>   `options(list(gtexr.itemsPerPage = 100000))`
#> 
#> ── Paging info ─────────────────────────────────────────────────────────────────
#> • numberOfPages = 13
#> • page = 0
#> • maxItemsPerPage = 250
#> • totalNumberOfItems = 3013
#> # A tibble: 250 × 11
#>    nPhenotypes pValueThreshold phenotypeId        geneSymbol    pValue datasetId
#>          <int>           <dbl> <chr>              <chr>          <dbl> <chr>    
#>  1           9      0.0000145  chr1:15947:16607:… WASH7P     7.15e-  8 gtex_v8  
#>  2           6      0.00000634 chr1:1090428:1091… C1orf159   6.85e- 10 gtex_v8  
#>  3           7      0.00000908 chr1:1228946:1231… SDF4       1.16e-188 gtex_v8  
#>  4           6      0.00000861 chr1:1310688:1310… PUSL1      2.50e- 40 gtex_v8  
#>  5           3      0.00000954 chr1:1325102:1327… CPTP       9.60e-  7 gtex_v8  
#>  6           2      0.0000147  chr1:1487914:1489… ATAD3C     1.61e- 25 gtex_v8  
#>  7           5      0.00000740 chr1:1487914:1489… ATAD3B     1.61e- 25 gtex_v8  
#>  8           2      0.0000361  chr1:1545002:1547… SSU72      3.28e- 25 gtex_v8  
#>  9          19      0.00000176 chr1:1629311:1629… MIB2       1.97e- 12 gtex_v8  
#> 10           8      0.00000273 chr1:1641113:1641… CDK11B     3.08e- 56 gtex_v8  
#> # ℹ 240 more rows
#> # ℹ 5 more variables: empiricalPValue <dbl>, tissueSiteDetailId <chr>,
#> #   ontologyId <chr>, qValue <dbl>, gencodeId <chr>