inst/doc/dbparser.R

In dbparser: Drugs Databases Parser

## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "docs/articles/",
  out.width = "100%"
)

## ----eval=FALSE---------------------------------------------------------------
#  ## load dbparser package
#  library(dbparser)
#  library(dplyr)
#  library(ggplot2)
#  library(XML)
#  
#  ## parse data from XML and save it to memory
#  dvobj <- parseDrugBank(db_path            = "C:\drugbank.xml",
#                         drug_options       = drug_node_options(),
#                         parse_salts        = TRUE,
#                         parse_products     = TRUE,
#                         references_options = references_node_options(),
#                         cett_options       = cett_nodes_options())
#  
#  ## load drugs data
#  drugs <- dvobj$drugs$general_information
#  
#  ## load drug groups data
#  drug_groups <- dvobj$drugs$groups
#  
#  ## load drug targets actions data
#  drug_targets_actions <- dvobj$cett$targets$actions

## ----eval=FALSE---------------------------------------------------------------
#  ## view proportions of the different drug types (biotech vs. small molecule)
#  drugs %>%
#      select(type) %>%
#      ggplot(aes(x = type, fill = type)) +
#      geom_bar() +
#      guides(fill = FALSE)     ## removes legend for the bar colors

## ----eval=FALSE---------------------------------------------------------------
#  ## view proportions of the different drug types for each drug group
#  drugs %>%
#      full_join(drug_groups, by = c('primary_key' = 'drugbank_id')) %>%
#      select(type, group) %>%
#      ggplot(aes(x = group, fill = type)) +
#      geom_bar() +
#      theme(legend.position = 'bottom') +
#      labs(x = 'Drug Group',
#           y = 'Quantity',
#           title = "Drug Type Distribution per Drug Group",
#           caption = "created by ggplot") +
#      coord_flip()

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