calculate_expression_quantitative_trait_loci {gtexr} | R Documentation |
Calculate Expression Quantitative Trait Loci
Description
Calculate your own eQTLs
This service calculates the gene-variant association for any given pair of gene and variant, which may or may not be significant.
This requires as input a GENCODE ID, GTEx variant ID, and tissue site detail ID.
By default, the calculation is based on the latest GTEx release.
GTEx Portal API documentation.
Usage
calculate_expression_quantitative_trait_loci(
tissueSiteDetailId,
gencodeId,
variantId,
datasetId = "gtex_v8",
.return_raw = FALSE
)
Arguments
tissueSiteDetailId |
String. The ID of the tissue of interest. Can be a
GTEx specific ID (e.g. "Whole_Blood"; use |
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". |
.return_raw |
Logical. If |
Details
Notes on output:
Beta and standard error are recorded in columns
nes
anderror
respectively (see GTEx FAQs)-
variantId
contains (in order) chromosome, position, reference allele, alternative allele and human genome build separated by underscores. The reference and alternative alleles for "chr1_13550_G_A_b38" for example are "G" and "A" respectively. See examples for how to calculate minor and alternative allele frequencies.
Notes on input:
Argument
variantId
also accepts RSIDs.
Value
A tibble. Or a list if .return_raw = TRUE
.
See Also
Other Dynamic Association Endpoints:
calculate_ieqtls()
,
calculate_isqtls()
,
calculate_splicing_quantitative_trait_loci()
Examples
## Not run:
# perform request - returns a tibble with a single row
calculate_expression_quantitative_trait_loci(
tissueSiteDetailId = "Whole_Blood",
gencodeId = "ENSG00000203782.5",
variantId = "rs79641866"
)
# unnest list columns with tidyr::unnest()
calculate_expression_quantitative_trait_loci(
tissueSiteDetailId = "Whole_Blood",
gencodeId = "ENSG00000203782.5",
variantId = "rs79641866"
) |>
tidyr::unnest(c("data", "genotypes"))
# to calculate minor and alternative allele frequencies
calculate_expression_quantitative_trait_loci(
tissueSiteDetailId = "Liver",
gencodeId = "ENSG00000237973.1",
variantId = "rs12119111"
) |>
dplyr::bind_rows(.id = "rsid") |>
tidyr::separate(
col = "variantId",
into = c(
"chromosome",
"position",
"reference_allele",
"alternative_allele",
"genome_build"
),
sep = "_"
) |>
# ...then ascertain alternative_allele frequency
dplyr::mutate(
alt_allele_count = (2 * homoAltCount) + hetCount,
total_allele_count = 2 * (homoAltCount + hetCount + homoRefCount),
alternative_allele_frequency = alt_allele_count / total_allele_count
) |>
dplyr::select(
rsid,
beta = nes,
se = error,
pValue,
minor_allele_frequency = maf,
alternative_allele_frequency,
chromosome:genome_build,
tissueSiteDetailId
)
## End(Not run)