gtexr (version 0.2.1)

get_multi_tissue_eqtls: Get Multi Tissue Eqtls

Description

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
)

Value

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

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

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

if (FALSE) { # identical(Sys.getenv("IN_PKGDOWN"), "true")
# search by gene
get_multi_tissue_eqtls(gencodeId = "ENSG00000132693.12")

# note that 'tissues' is a list-column
x <- get_multi_tissue_eqtls(gencodeId = "ENSG00000132693.12",
                            variantId = "chr1_159476920_T_C_b38")

x$tissues[[1]]
}