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#' Retrieves tag variants and studies for a given index variant.
#'
#' For an input index variant ID, this function fetches information about the tag variants
#' and associated studies, including scores.
#'
#' @param variant_id Character: Open Targets Genetics generated ID for a variant (CHRPOSITION_REFALLELE_ALTALLELE or rsId).
#' @param pageindex Integer: Index of the current page for pagination (>= 0).
#' @param pagesize Integer: Number of records in a page for pagination (> 0).
#'
#' @return Returns a data frame containing the variant associations connected to the input index variant.
#' The columns in the data frame are as follows:
#' \itemize{
#' \item{\code{tagVariant.id}:} \emph{Character}. Tag variant ID.
#' \item{\code{tagVariant.chromosome}:} \emph{Character}. Chromosome of the tag variant.
#' \item{\code{tagVariant.rsId}:} \emph{Character}. rsID of the tag variant.
#' \item{\code{tagVariant.position}:} \emph{Integer}. Position of the tag variant.
#' \item{\code{study.studyId}:} \emph{Character}. Study ID.
#' \item{\code{study.traitReported}:} \emph{Character}. Reported trait of the study.
#' \item{\code{study.traitCategory}:} \emph{Character}. Category of the trait in the study.
#' \item{\code{pval}:} \emph{Numeric}. P-value.
#' \item{\code{pvalMantissa}:} \emph{Numeric}. Mantissa of the p-value.
#' \item{\code{pvalExponent}:} \emph{Integer}. Exponent of the p-value.
#' \item{\code{nTotal}:} \emph{Integer}. Total number of samples.
#' \item{\code{nCases}:} \emph{Integer}. Number of cases in the study.
#' \item{\code{overallR2}:} \emph{Numeric}. Overall R-squared value.
#' \item{\code{afr1000GProp}:} \emph{Numeric}. Proportion in African 1000 Genomes population.
#' \item{\code{amr1000GProp}:} \emph{Numeric}. Proportion in Admixed American 1000 Genomes population.
#' \item{\code{eas1000GProp}:} \emph{Numeric}. Proportion in East Asian 1000 Genomes population.
#' \item{\code{eur1000GProp}:} \emph{Numeric}. Proportion in European 1000 Genomes population.
#' \item{\code{sas1000GProp}:} \emph{Numeric}. Proportion in South Asian 1000 Genomes population.
#' \item{\code{oddsRatio}:} \emph{Numeric}. Odds ratio.
#' \item{\code{oddsRatioCILower}:} \emph{Numeric}. Lower bound of the odds ratio confidence interval.
#' \item{\code{oddsRatioCIUpper}:} \emph{Numeric}. Upper bound of the odds ratio confidence interval.
#' \item{\code{posteriorProbability}:} \emph{Numeric}. Posterior probability.
#' \item{\code{beta}:} \emph{Numeric}. Beta value.
#' \item{\code{betaCILower}:} \emph{Numeric}. Lower bound of the beta value confidence interval.
#' \item{\code{betaCIUpper}:} \emph{Numeric}. Upper bound of the beta value confidence interval.
#' \item{\code{direction}:} \emph{Character}. Direction of the effect.
#' \item{\code{log10Abf}:} \emph{Numeric}. Log base 10 of the approximate Bayes factor.
#' }
#'
#' @examples
#' \dontrun{
#' result <- tagVariantsAndStudiesForIndexVariant(variant_id = "1_109274968_G_T")
#' result <- tagVariantsAndStudiesForIndexVariant(variant_id = "1_109274968_G_T"
#' ,pageindex = 1, pagesize = 50)
#' }
#' @importFrom magrittr %>%
#' @export
#'
tagVariantsAndStudiesForIndexVariant <- function(variant_id, pageindex = 0, pagesize = 20) {
# Check if the variant ID argument is empty or null
if (missing(variant_id) || is.null(variant_id) || variant_id == "") {
message("Please provide a value for the variant ID argument.")
return(NULL)
}
## Set up to query Open Targets Genetics API
tryCatch({
cli::cli_progress_step("Connecting the database...", spinner = TRUE)
otg_cli <- ghql::GraphqlClient$new(url = "https://api.genetics.opentargets.org/graphql")
otg_qry <- ghql::Query$new()
# Check variant id format
if (grepl(pattern = "rs\\d+", variant_id)) {
# Convert rs id to variant id
query_searchid <- "query ConvertRSIDtoVID($queryString:String!) {
search(queryString:$queryString){
totalVariants
variants{
id
}
}
}"
variables <- list(queryString = variant_id)
otg_qry$query(name = "convertid", x = query_searchid)
id_result <- jsonlite::fromJSON(otg_cli$exec(otg_qry$queries$convertid, variables), flatten = TRUE)$data
input_variant_id <- id_result$search$variants$id
} else if (grepl(pattern = "\\d+_\\d+_[a-zA-Z]+_[a-zA-Z]+", variant_id)) {
input_variant_id <- variant_id
} else {
stop("\n Please provide a variant Id")
}
query <- "query tagVariantsAndStudiesForIndexVariantquery($variantId: String!, $pageIndex: Int!, $pageSize:Int!){
tagVariantsAndStudiesForIndexVariant(variantId: $variantId, pageIndex: $pageIndex, pageSize: $pageSize) {
associations {
tagVariant {
id
chromosome
rsId
position
}
study {
studyId
traitReported
}
pval
pvalMantissa
pvalExponent
nTotal
nCases
overallR2
afr1000GProp
amr1000GProp
eas1000GProp
eur1000GProp
sas1000GProp
oddsRatio
oddsRatioCILower
oddsRatioCIUpper
posteriorProbability
beta
betaCILower
betaCIUpper
direction
log10Abf
}
}
}"
## Execute the query
variables <- list(variantId = input_variant_id, pageIndex = pageindex, pageSize = pagesize)
otg_qry$query(name = "tagVariantsAndStudiesForIndexVariant_query", x = query)
cli::cli_progress_step("Downloading data...", spinner = TRUE)
tag_var_studies <- jsonlite::fromJSON(otg_cli$exec(otg_qry$queries$tagVariantsAndStudiesForIndexVariant_query, variables, flatten = TRUE))$data
tag_var_studies <- tag_var_studies$tagVariantsAndStudiesForIndexVariant$associations %>% as.data.frame()
return(tag_var_studies)
}, error = function(e) {
# Handling connection timeout
if(grepl("Timeout was reached", e$message)) {
stop("Connection timeout reached while connecting to the Open Targets Genetics GraphQL API.")
} else {
stop(e) # Handle other types of errors
}
})
}
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