Calculate and add related studies to study table — calculate_related

Processes study summary text to identify clusters of related studies. Calculates tf-idf values for 1 and 2 length ngrams, and clusters studies using the ward.D clustering method. Adds results as annotations to the studies.

Usage

calculate_related_studies(
  study_table_id,
  n_clust = NULL,
  n_k = NULL,
  dry_run = TRUE
)

Arguments

study_table_id: The synapse id of the portal study table. Must have write access.
n_clust: Target number of clusters to generate using hierarchical clustering. In practice, the number of total summaries divided by 3 is a good starting point (100 studies = 33 clusters). If given n_k is ignored.
n_k: Generate target number of most closely related studies using k-nearest-neighbors instead; since the number of desired related studies is specified, this may be preferable over using n_clust, which gives variable number of related studies because clusters vary in size. Ignored if n_clust is already given.
dry_run: Default = TRUE. Skips annotating the studies and instead prints study tibble.

Value

If dry_run == T, returns study tibble and skips upload.

Examples

if (FALSE) { # \dontrun{
result1  <- calculate_related_studies(study_table_id = "syn16787123",
                           n_clust = 40,
                           dry_run = T)
result2  <- calculate_related_studies(study_table_id = "syn16787123",
                           n_k = 4,
                           dry_run = T)
x <- lapply(result1$relatedStudies, jsonlite::fromJSON)
y <- lapply(result2$relatedStudies, jsonlite::fromJSON)
# Compare
mapply(function(x, y) sum(y %in% x), x, y)
} # }