{"Package":"dbparser","Title":"'DrugBank' Database XML Parser","Version":"1.0.4","Authors@R":"\nc(\nperson(\"Mohammed\", \"Ali\", email = \"moh_fcis@yahoo.com\", role = c(\"aut\", \"cre\")),\nperson(\"Ali\", \"Ezzat\", email = \"ali_ezzat85@yahoo.com\", role = \"aut\"))","Description":"This tool is for parsing the 'DrugBank' XML database . The parsed\ndata are then returned in a proper 'R' dataframe with the ability to save\nthem in a given database.","License":"MIT + file LICENSE","Encoding":"UTF-8","LazyData":"true","Imports":"DBI, odbc, purrr, readr, RMariaDB, tibble, tidyr, tools, XML","RoxygenNote":"6.1.1","Suggests":"knitr, rmarkdown, testthat","VignetteBuilder":"knitr","URL":"https://dainanahan.github.io/dbparser/index.html","BugReports":"https://github.com/Dainanahan/dbparser/issues","NeedsCompilation":"no","Packaged":"2019-08-28 20:24:21 UTC; Mohammed","Author":"Mohammed Ali [aut, cre],\nAli Ezzat [aut]","Maintainer":"Mohammed Ali ","Repository":"CRAN","Date/Publication":"2019-08-28 20:50:02 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/dbparser_1.0.4.tar.gz","jsonAuthors":[{"name":"Mohammed Ali","email":"moh_fcis@yahoo.com","maintainer":true},{"name":"Ali Ezzat","email":"ali_ezzat85@yahoo.com","maintainer":false}],"readme":"\n\n\n# dbparser\n\n[![Build\nStatus](https://travis-ci.org/Dainanahan/dbparser.svg?branch=master)](https://travis-ci.org/Dainanahan/dbparser)\n[![CRAN\\_Status\\_Badge](http://www.r-pkg.org/badges/version/dbparser)](https://cran.r-project.org/package=dbparser)\n[![DOWNLOADSTOTAL](https://cranlogs.r-pkg.org/badges/grand-total/dbparser)](https://cranlogs.r-pkg.org/badges/grand-total/dbparser)\n[![Rdoc](http://www.rdocumentation.org/badges/version/dbparser)](http://www.rdocumentation.org/packages/dbparser)\n\nThe main purpose of the `dbparser` package is to parse the\n[DrugBank](http://drugbank.ca/) database which is downloadable in XML\nformat from [this link](https://www.drugbank.ca/releases/latest). The\nparsed data can then be explored and analyzed as desired by the user.\nThe `dbparser` package further provides the facility of saving the\nparsed data into a given database.\n\n## Installation\n\nYou can install the released version of dbparser from\n[CRAN](https://CRAN.R-project.org) with:\n\n``` r\ninstall.packages(\"dbparser\")\n```\n\nor you can install the latest updates directly from the repo\n\n``` r\nlibrary(devtools)\ndevtools::install_github(\"Dainanahan/dbparser\")\n```\n\n## Example\n\nThis is a basic example which shows you how to solve a common problem:\n\n``` r\n## parse data from XML and save it to memory\ndbparser::get_xml_db_rows(\n system.file(\"extdata\", \"drugbank_record.xml\", package = \"dbparser\")\n )\n#> [1] TRUE\n\n## load drugs data\ndrugs <- dbparser::parse_drug()\n\n## load drug groups data\ndrug_groups <- dbparser::parse_drug_groups()\n\n## load drug targets actions data\ndrug_targets_actions <- dbparser::parse_drug_targets_actions()\n```\n\n## Saving into a database\n\nThe parsed data may be saved into a given database. Databases supported\nby `dbparser` include MS SQL Server, MySQL and any database supported by\n`DBI` package. Following is an example of saving the parsed data into a\nMySQL database.\n\n``` r\nlibrary(dbparser)\n\n## open a connection to the desired database engine with an already\n## created database\n open_db(xml_db_name = \"drugbank.xml\", driver = \"SQL Server\",\n server = \"ServerName\\\\\\\\SQL2016\", output_database = \"drugbank\")\n\n## save 'drugs' dataframe to DB\n parse_drug(TRUE)\n\n## save 'drug_groups' dataframe to DB\n parse_drug_groups(TRUE)\n\n## save 'drug_targets_actions' dataframe to DB\n parse_drug_targets_actions(TRUE)\n\n## finally close db connection \n close_db()\n```\n\n## Exploring the data\n\nFollowing is an example involving a quick look at a few aspects of the\nparsed data. First we look at the proportions of `biotech` and\n`small-molecule` drugs in the\ndata.\n\n``` r\n## view proportions of the different drug types (biotech vs. small molecule)\ndrugs %>% \n select(type) %>% \n ggplot(aes(x = type, fill = type)) + \n geom_bar() + \n guides(fill=FALSE) ## removes legend for the bar colors\n```\n\n

\n\nBelow, we view the different `drug_groups` in the data and how prevalent\nthey are.\n\n``` r\n## view proportions of the different drug types for each drug group\ndrugs %>% \n full_join(drug_groups, by = c('primary_key' = 'drugbank_id')) %>% \n select(type, group) %>% \n ggplot(aes(x = group, fill = type)) + \n geom_bar() + \n theme(legend.position= 'bottom') + \n labs(x = 'Drug Group', \n y = 'Quantity', \n title=\"Drug Type Distribution per Drug Group\", \n caption=\"created by ggplot\") + \n coord_flip()\n```\n\n

\n\nFinally, we look at the `drug_targets_actions` to observe their\nproportions as well.\n\n``` r\n## get counts of the different target actions in the data\ntargetActionCounts <- \n drug_targets_actions %>% \n group_by(action) %>% \n summarise(count = n()) %>% \n arrange(desc(count))\n\n## get bar chart of the 10 most occurring target actions in the data\np <- \n ggplot(targetActionCounts[1:10,], \n aes(x = reorder(action,count), y = count, fill = letters[1:10])) + \n geom_bar(stat = 'identity') +\n labs(fill = 'action', \n x = 'Target Action', \n y = 'Quantity', \n title = 'Target Actions Distribution', \n subtitle = 'Distribution of Target Actions in the Data',\n caption = 'created by ggplot') + \n guides(fill = FALSE) + ## removes legend for the bar colors\n coord_flip() ## switches the X and Y axes\n\n## display plot\np\n```\n\n

","jobInfo":{"package":"dbparser","version":"1.0.4","parsingStatus":"success","parserVersion":1,"parsedAt":"2020-02-21T07:29:47+0000"}}

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