literature_gwas(trait, semmed_predicate = NULL, mode = c("table", "raw"))

Arguments

trait

A trait name

semmed_predicate

Either NULL which returns entries from all predicates, or a SemMed predicate e.g. "DIAGNOSES" or "ASSOCIATED_WITH"

mode

If mode = "table", returns a data frame (a tibble as per tidyverse convention). If mode = "raw", returns a raw response from EpiGraphDB API with minimal parsing done by httr.

Value

Data from GET /literature/gwas

Examples

literature_gwas(trait = "Body mass index")
#> # A tibble: 50 x 9 #> gwas.trait gwas.id gs.localCount gs.pval triple.subject_… triple.predicate #> <chr> <chr> <int> <dbl> <chr> <chr> #> 1 Body mass… ebi-a-… 2 8.04e-4 Insulin|INS TREATS #> 2 Body mass… ebi-a-… 2 8.04e-4 Conjugated Equi… NEG_INTERACTS_W… #> 3 Body mass… ebi-a-… 2 8.04e-4 Spondylarthritis PREDISPOSES #> 4 Body mass… ebi-a-… 7 3.47e-5 Hypertensive di… COEXISTS_WITH #> 5 Body mass… ebi-a-… 7 3.47e-5 Hypertensive di… COEXISTS_WITH #> 6 Body mass… ebi-a-… 7 3.47e-5 Hypertensive di… COEXISTS_WITH #> 7 Body mass… ebi-a-… 7 3.47e-5 Hypertensive di… COEXISTS_WITH #> 8 Body mass… ebi-a-… 7 3.47e-5 Hypertensive di… COEXISTS_WITH #> 9 Body mass… ebi-a-… 7 3.47e-5 Hypertensive di… COEXISTS_WITH #> 10 Body mass… ebi-a-… 2 8.04e-4 ANGPTL4 ASSOCIATED_WITH #> # … with 40 more rows, and 3 more variables: triple.id <chr>, #> # triple.object_name <chr>, lit.pubmed_id <chr>