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Get Multi Tissue Eqtls

Source: R/get_multi_tissue_eqtls.R
get_multi_tissue_eqtls.Rd

Find multi-tissue eQTL Metasoft results.

  • This service returns multi-tissue eQTL Metasoft results for a given gene and variant in a specified dataset.

  • A Versioned GENCODE ID must be provided.

  • For each tissue, the results include: m-value (mValue), normalized effect size (nes), p-value (pValue), and standard error (se).

  • The m-value is the posterior probability that an eQTL effect exists in each tissue tested in the cross-tissue meta-analysis (Han and Eskin, PLoS Genetics 8(3): e1002555, 2012).

  • The normalized effect size is the slope of the linear regression of normalized expression data versus the three genotype categories using single-tissue eQTL analysis, representing eQTL effect size.

  • The p-value is from a t-test that compares observed NES from single-tissue eQTL analysis to a null NES of 0.

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_multi_tissue_eqtls(
  gencodeId,
  variantId = NULL,
  datasetId = "gtex_v8",
  page = 0,
  itemsPerPage = getOption("gtexr.itemsPerPage"),
  .verbose = getOption("gtexr.verbose"),
  .return_raw = FALSE
)

Arguments

gencodeId

String. A Versioned GENCODE ID of a gene, e.g. "ENSG00000065613.9".

variantId

String. A gtex variant ID.

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_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(), get_sqtl_genes()

Examples

# search by gene
get_multi_tissue_eqtls(gencodeId = "ENSG00000132693.12")
#> 
#> ── Paging info ─────────────────────────────────────────────────────────────────
#> • numberOfPages = 1
#> • page = 0
#> • maxItemsPerPage = 250
#> • totalNumberOfItems = 93
#> # A tibble: 93 × 5
#>    gencodeId          datasetId    metaP variantId               tissues 
#>    <chr>              <chr>        <dbl> <chr>                   <list>  
#>  1 ENSG00000132693.12 gtex_v8   0.00142  chr1_159476920_T_C_b38  <tibble>
#>  2 ENSG00000132693.12 gtex_v8   0.0927   chr1_159245536_C_T_b38  <tibble>
#>  3 ENSG00000132693.12 gtex_v8   0.00158  chr1_159439013_C_T_b38  <tibble>
#>  4 ENSG00000132693.12 gtex_v8   0.000735 chr1_159441913_T_A_b38  <tibble>
#>  5 ENSG00000132693.12 gtex_v8   0.00158  chr1_159471651_G_A_b38  <tibble>
#>  6 ENSG00000132693.12 gtex_v8   0.00158  chr1_159396484_C_T_b38  <tibble>
#>  7 ENSG00000132693.12 gtex_v8   0.00158  chr1_159386699_AT_A_b38 <tibble>
#>  8 ENSG00000132693.12 gtex_v8   0.00263  chr1_159545608_A_T_b38  <tibble>
#>  9 ENSG00000132693.12 gtex_v8   0.00142  chr1_159476580_G_A_b38  <tibble>
#> 10 ENSG00000132693.12 gtex_v8   0.00166  chr1_159505857_T_A_b38  <tibble>
#> # ℹ 83 more rows

# note that 'tissues' is a list-column
x <- get_multi_tissue_eqtls(gencodeId = "ENSG00000132693.12",
                            variantId = "chr1_159476920_T_C_b38")
#> 
#> ── Paging info ─────────────────────────────────────────────────────────────────
#> • numberOfPages = 1
#> • page = 0
#> • maxItemsPerPage = 250
#> • totalNumberOfItems = 1

x$tissues[[1]]
#> # A tibble: 49 × 5
#>    tissue                          mValue    pValue     se     nes
#>    <chr>                            <dbl>     <dbl>  <dbl>   <dbl>
#>  1 Thyroid                          0.983 0.0000292 0.0593  0.250 
#>  2 Testis                           0.342 0.0404    0.0835 -0.172 
#>  3 Small_Intestine_Terminal_Ileum   0.551 0.864     0.122  -0.0211
#>  4 Brain_Frontal_Cortex_BA9         0.489 0.204     0.113  -0.144 
#>  5 Skin_Not_Sun_Exposed_Suprapubic  0.552 0.806     0.0654  0.0160
#>  6 Vagina                           0.514 0.437     0.130  -0.102 
#>  7 Whole_Blood                      0.494 0.632     0.0407  0.0195
#>  8 Breast_Mammary_Tissue            0.679 0.395     0.0746  0.0636
#>  9 Pituitary                        0.421 0.175     0.0972 -0.132 
#> 10 Minor_Salivary_Gland             0.678 0.349     0.126   0.118 
#> # ℹ 39 more rows