In ed-lau/calcWCD: Calculation of Weighted Co-publication Distances

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

calcWCD v.1.0.2

calcWCD calculates weighted copublication distance between a gene/protein and a disease/term in PubMed literature.

Installation

The released version of calcWCD can be installed from this repo directly:

devtools::install_github("ed-lau/calcWCD")

Updates

2023-07-15 v.1.0.1 Due to 2023 changes to the NCBI EUtils API limiting PubMed retrieval to 9999 items, calcWCD now uses the EuropePMC API to retrieve PMIDs. A new max_retrieval argument is added to pmid() to limit the number of retrievals.

Example

A basic example using test PMID and Annotation data included in the package:

require(calcWCD)
w <- wcd(pmids = test_pmids, annot = test_annotation)

w

Distribution of WCD values in the test files:

hist(w$WCD, main="Distribution of WCD values.")

Reference

Edward Lau, Vidya Venkatraman, Cody T Thomas, Jennifer E Van Eyk, Maggie P. Y. Lam. Identifying high-priority proteins across the human diseasome using semantic similarity. bioRxiv 309203; doi: https://doi.org/10.1101/309203

ed-lau/calcWCD documentation built on Aug. 6, 2023, 4:15 p.m.