added fcn docs and revised README structure

Author: ngiangre

R/functions.R

@@ -1,6 +1,6 @@
 #' Download the Pediatric Drug Safety database
 #'
-#' Download the database published in Giangreco et al. 2022. Warning, the size of the uncompressed 'sqlite' file is close to 0.9GB or 900 MB. Use with caution
+#' Download the database published in Giangreco et al. 2022. This function will prompt to download the database, so the cache directory will be identified and the database will be downloaded to it only after consent. Warning, the size of the uncompressed 'sqlite' file is close to 0.9GB or 900 MB. Use with caution.
 #'
 #' @param method The method to download the sqlite database. See \code{download.file}
 #' @param quiet Whether to download quietly. See \code{download.file}
@@ -116,7 +116,7 @@ disconnect_sqlite_db <- function(con){
 
 #' Return database cache
 #'
-#' This function identifies and returns the cache location for the database on your machine
+#' This function returns the URL, sqlite database file, and cache names to be used for downloading the database to your machine.
 #'
 #' @importFrom tools R_user_dir
 #'

README.Rmd

@@ -15,23 +15,27 @@ output: github_document
 knitr::opts_chunk$set(echo = TRUE)
 ```
 
+This R data package contains observation, summary, and model-level data from pediatric drug safety research developed by Nicholas Giangreco for his PhD dissertation in the Tatonetti lab at Columbia University.
+
 # Installation
 
+**The database is downloaded after consent is given when using the package. Installing the package will not download the database, but it will make it easier to download and connect to the database from your R session.**
+
 ```{r,eval=FALSE}
 install.packages('kidsides')
 remotes::install_github("ngiangre/kidsides")
 ```
 
 # Summary
 
-This R data package contains observation, summary, and model-level data from pediatric drug safety research developed by Nicholas Giangreco for his PhD dissertation in the Tatonetti lab at Columbia University.
-
 The database is comprised of 17 tables including a table with descriptions of the fields in each table. The main table, `ade_nichd`, contains quantitative data from nearly 500,000 pediatric drug safety signals across 7 child development stages spanning from birth through late adolescence (21 years of age).
 
 The database was created using the methods and analyses in the references.
 
 This data resource can be used under the [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) license agreement. 
 
+**See the `Overview` vignette for more details on the data and the online portal**
+
 # Usage
 
 ```{r}
@@ -61,8 +65,6 @@ kidsides::disconnect_sqlite_db(con)
 
 ```
 
-** See the `Overview` vignette for more details on the data and the online portal**
-
 # References
 
 

README.md

@@ -11,19 +11,24 @@ coverage](https://codecov.io/gh/ngiangre/kidsides/branch/main/graph/badge.svg)](
 status](https://www.r-pkg.org/badges/version/kidsides)](https://CRAN.R-project.org/package=kidsides)
 <!-- badges: end -->
 
+This R data package contains observation, summary, and model-level data
+from pediatric drug safety research developed by Nicholas Giangreco for
+his PhD dissertation in the Tatonetti lab at Columbia University.
+
 # Installation
 
+**The database is downloaded after consent is given when using the
+package. Installing the package will not download the database, but it
+will make it easier to download and connect to the database from your R
+session.**
+
 ``` r
 install.packages('kidsides')
 remotes::install_github("ngiangre/kidsides")
 ```
 
 # Summary
 
-This R data package contains observation, summary, and model-level data
-from pediatric drug safety research developed by Nicholas Giangreco for
-his PhD dissertation in the Tatonetti lab at Columbia University.
-
 The database is comprised of 17 tables including a table with
 descriptions of the fields in each table. The main table, `ade_nichd`,
 contains quantitative data from nearly 500,000 pediatric drug safety
@@ -36,6 +41,9 @@ references.
 This data resource can be used under the [CC BY
 4.0](https://creativecommons.org/licenses/by/4.0/) license agreement.
 
+**See the `Overview` vignette for more details on the data and the
+online portal**
+
 # Usage
 
 ``` r
@@ -176,90 +184,6 @@ dplyr::tbl(con,"ade_raw") %>%
 kidsides::disconnect_sqlite_db(con)
 ```
 
-# Background
-
-Adverse drug reactions are a leading cause of morbidity and mortality
-that costs billions of dollars for the healthcare system. In children,
-there is increased risk for adverse drug reactions with potentially
-lasting adverse effects into adulthood. The current pediatric drug
-safety landscape, including clinical trials, is limited as it rarely
-includes children and relies on extrapolation from adults. Children are
-not small adults but go through an evolutionarily conserved and
-physiologically dynamic process of growth and maturation. We hypothesize
-that adverse drug reactions manifest from the interaction between drug
-exposure and dynamic biological processes during child growth and
-development.
-
-We hypothesize that by developing statistical methodologies with prior
-knowledge of dynamic, shared information during development, we can
-improve the detection of adverse drug events in children. This data
-package downloads the SQLite database created by applying
-covariate-adjusted disproportionality generalized additive models
-(dGAMs) in a systematic way to develop a resource of nearly half a
-million adverse drug event (ADE) risk estimates across child development
-stages.
-
-# Pediatric Drug Safety (PDS) data
-
-## Observation-level data
-
-The observation-level data, case reports for drug(s) potentially linked
-to adverse event(s), was collected by the Food and Drug Administration
-Adverse Event System (FAERS) in the US. This data is publicly available
-on the openFDA platform [here](https://open.fda.gov/data/downloads/) as
-downloadable [json files](https://api.fda.gov/download.json). However,
-utilizing this data as-is is non-trivial, where the drug event report
-data is published in chunks as a nested json structure each quarter per
-year since the 1990s. With an API key with extended permissions, I
-developed custom python notebooks and scripts available in the
-‘openFDA_drug_event-parsing’ github repository (DOI:
-<https://doi.org/10.5281/zenodo.4464544>) to extract and format all drug
-event reports prior to the third quarter of 2019. This observation-level
-data used, called Pediatric FAERS, for downstream analyses is stored in
-the table `ade_raw`.
-
-## Summary-level data
-
-The drugs and adverse events reported were coded into standard,
-hierarchical vocabularies. Adverse events were standardized by the
-Medical Dictionary of Regulatory Activities (MedDRA) vocabulary (details
-of the hierarcy founds
-[here](https://www.meddra.org/how-to-use/basics/hierarchy)). Drugs were
-standardized by the Anatomical Therapeutic Class (ATC) vocabulary
-(details found
-[here](https://www.who.int/tools/atc-ddd-toolkit/atc-classification)).
-The reporting of adverse events and drugs can be dependent on the
-disease context of a report’s subject. This was represented by
-summarizing the number of drugs of a therapeutic class for each report.
-
-## Model-level data
-
-We invented the disproportionality generalized additive model (dGAM)
-method for detecting adverse drug events from these spontaneous reports.
-We applied the logistic generalized additive model to all unique
-drug-event pairs in Pediatric FAERS. The drug-event GAM was used to
-quantify adverse event risk due to drug exposure versus no exposure
-across child development stages. Please see the references for the full
-specification and details on the GAM.
-
-# PDSportal: accessible data access
-
-We provide the [PDSportal](https://pdsportal.shinyapps.io/pdsportal/) as
-an accessible web application as well as a plaatform to download our
-database for the community to explore from identifying safety endpoints
-in clinical trials to evaluating known and novel developmental
-pharmacology.
-
-# KidSIDES
-
-The `kidsides` R package downloads a sqlite database to your local
-machine and connects to the database using the `DBI` R package. This is
-a novel data resource of half a million pediatric drug safety signals
-across growth and development stages. Please see the references for
-details on data fields and the [code
-repository](https://github.com/ngiangre/pediatric_ade_database_study)
-for the [paper](https://www.ssrn.com/abstract=3898786).
-
 # References
 
 Giangreco, Nicholas. Mind the developmental gap: Identifying adverse