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DOPE

Drug Ontology Parsing Engine

https://github.com/ctn-0094/dope

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    3 of 6 committers (50.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (14.1%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Drug Ontology Parsing Engine

Basic Info
Statistics
  • Stars: 23
  • Watchers: 3
  • Forks: 2
  • Open Issues: 18
  • Releases: 3
Created over 5 years ago · Last pushed about 1 year ago
Metadata Files
Readme Changelog License

README.md

Drug Ontology Parsing Engine (DOPE)

CRAN status Lifecycle: maturing CRAN downloads <!-- badges: end -->

The goal of DOPE is to provide a structured vocabulary and tools to look up details on drugs tracked by the DEA. The data structure is:

Figure 1. Detailed view of data structure can be seen on the package website.

Installation

Official Release

You can install the released version of DOPE from CRAN with:

r install.packages("DOPE")

Development Release

Run these two lines of code to install DOPE from GitHub (this requires RTools for Windows or Xcode for Mac to be installed on your computer):

r if (!requireNamespace("devtools")) install.packages("devtools") devtools::install_github("CTN-0094/DOPE")

Examples

You can look up details on a drug with the lookup() function. It will check brand, generic and street names.

r library(DOPE) lookup("adderall") lookup("ketamine") lookup("auntie")

The lookup funciton supports vectorized lookups: library(DOPE) lookup("cheese", "pizza", "with", "a", "soda") lookup(c("Buprenorphine", "Tramadol", "Bup/Nx"))

If your only care about the class and/or category and/or if you search returns many matches you can use the compress_lookup() function to drop columns and then remove duplicate rows.

lookup("cheese", "pizza", "with", "a", "soda") %>% compress_lookup(compressClass = FALSE, compressCategory = TRUE, compressSynonym = TRUE)

DOPE now allows for parsing out drug names from a vector which contains free text with the parse() function. You can use it in conjunction withlookup() and compress_lookup()

data(drug_df) parse(drug_df$textdrug[1:5]) %>% lookup()

Additional Information

For more information or to see detailed vignettes, please visit https://ctn-0094.github.io/DOPE/.

Owner

  • Name: CTN-0094
  • Login: CTN-0094
  • Kind: organization

This is the CTN 94 org

GitHub Events

Total
  • Watch event: 2
  • Push event: 1
  • Pull request event: 1
  • Pull request review event: 2
  • Fork event: 2
Last Year
  • Watch event: 2
  • Push event: 1
  • Pull request event: 1
  • Pull request review event: 2
  • Fork event: 2

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 102
  • Total Committers: 6
  • Avg Commits per committer: 17.0
  • Development Distribution Score (DDS): 0.48
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Layla Bouzoubaa l****8@m****u 53
nathaniel castor n****r@g****m 20
Raymond Balise b****e@m****u 14
gabrielodom g****m@f****u 11
Nathaniel Castor n****r@N****l 3
Nate 9****r 1
Committer Domains (Top 20 + Academic)
miami.edu: 2 fiu.edu: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 32
  • Total pull requests: 24
  • Average time to close issues: 26 days
  • Average time to close pull requests: 8 days
  • Total issue authors: 4
  • Total pull request authors: 5
  • Average comments per issue: 0.91
  • Average comments per pull request: 0.25
  • Merged pull requests: 22
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 12 minutes
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • labouz (22)
  • RaymondBalise (5)
  • gabrielodom (4)
  • mbreevoort (1)
Pull Request Authors
  • nathan-castor (9)
  • labouz (9)
  • kyleGrealis (4)
  • RaymondBalise (3)
  • gabrielodom (1)
Top Labels
Issue Labels
enhancement (12) bug (10) documentation (1)
Pull Request Labels
bug (1) enhancement (1)

Packages

  • Total packages: 1
  • Total downloads:
    • cran 287 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 3
  • Total maintainers: 1
cran.r-project.org: DOPE

Drug Ontology Parsing Engine

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 287 Last month
Rankings
Stargazers count: 13.3%
Forks count: 21.9%
Dependent packages count: 29.8%
Average: 33.1%
Dependent repos count: 35.5%
Downloads: 65.0%
Maintainers (1)
balise@miami.edu
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • R >= 2.10 depends
  • dplyr * imports
  • magrittr * imports
  • stats * imports
  • stringr * imports
  • tibble * imports
  • tidytext * imports
  • utils * imports
  • conflicted * suggests
  • knitr * suggests
  • purrr * suggests
  • readr * suggests
  • rmarkdown * suggests
  • rvest * suggests
  • sqldf * suggests
  • testthat * suggests
  • tidyr * suggests
  • usethis * suggests
  • xml2 * suggests