R/pk_study.R
pk_get_study_list.Rd
Return studies that contain taxa which are members of the optional input taxon, and characters which have phenotype annotations subsumed by the given entity and quality terms.
pk_get_study_list(taxon = NA, entity = NA, quality = NA, phenotype = NA, includeRels = NA, relation = "part of")
taxon | character. The name of the taxon by which to filter, if any. |
---|---|
entity | character. The name of the anatomical entity by which to filter, if any. |
quality | character. The name of the phenotypic quality by which to filter, if any. |
phenotype | character. The phenotype (as its identifier) by which to filter, if any. If provided, matching studies (through its one or more of its character states) must be linked to the given phenotype, or one subsumed by it. This must be provided as identifier, no text search will be performed for resolution. |
includeRels | character or vector of characters. The names of relationships
for anatomical entities to include in addition to subtype ( |
relation | character. Deprecated, for backwards compatibility defaults to
|
data.frame
if (FALSE) { # by default, parts are included slist <- pk_get_study_list(taxon = "Siluridae", entity = "fin") colnames(slist) nrow(slist) # can also disable parts slist <- pk_get_study_list(taxon = "Siluridae", entity = "fin", includeRels = FALSE) nrow(slist) # or filter studies only by entity, including their parts slist <- pk_get_study_list(entity = "pelvic fin", includeRels = c("part of")) nrow(slist) # or filter studies only by entity, including their parts slist <- pk_get_study_list(entity = "pelvic fin", includeRels = c("part of")) nrow(slist) # including not only parts but also historical and serial homologs slist <- pk_get_study_list(entity = "pelvic fin", includeRels = c("part of", "serially homologous to", "historical homologous to")) nrow(slist) # relationship names can be given as prefixes slist1 <- pk_get_study_list(entity = "pelvic fin", includeRels = c("part", "serial", "historical")) nrow(slist1) == nrow(slist) # or apply no filter, obtaining all studies in the KB slist <- pk_get_study_list() nrow(slist) }