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collaboratR

A package to support collaborative meta-analysis for MSU IBEEM

Authors:

  • Patrick S Bills
  • Ashwini Ramesh
  • Laís Petri
  • Phoebe Lehman Zarnetske, PI and Director, IBEEM

Contributors:

  • Kelly Kapsar, Data Scientist, IBEEM
  • Alejandra Martinez Blancas
  • Amar Deep Tiwari

Motivation

Performing a Meta-analysis requires collating and harmonizing data extracted from many different sources but most frequently scientific publications.
Collaborative meta-analysis requires a group of scientists to collectively develop and agree on their goals, type of data extracted, format of the those data, and to do so extremely consistently across papers. This package helps to support that efficiently by the easy-to-use Google Sheets for data definition and data entry. The workflow in this project can read directly from Google sheets into CSVs and validate the structure of a google sheet as well as the data using the Validate package.

Originally, this This R package was part of 3 repositories that support the data entry, validation and accumulation of a meta-analysis for a research project sponsored by MSU IBEEM

  1. collaboratR: data management code for L0 and L0->L1 layer in EDI framework
  2. data: version controlled data collection for tracking provenance using git, this is the L0 and L1 layers in the EDI framework. the collaboratR package assists with data transfer and validation from Google drive into the data repository.
  3. analysis: R code for reproducible data analysis , L1->L2 layers in EDI framework, using data in the data repository.

Installation - Package

  • clone this repository into a new Rstudio project and open it

  • install required packages: This package uses renv to manage the packages you need to install, which creates an renv.lock file for you. 1. install the renv package: this can go into your R environment used for all packages.

    1. in R run renv::restore() or if that complains about R versions

additional packages are required to build the package and this website, source the script R/install_dev_packages.R

Installation/Testing

Google drive in this package is set to interaction. To run any building, installing or checking in R, you must first manually connect to google drive, which must be set-up properly first.

See the vignette in this package “Google Sheets API setup using Google Cloud”, or in this source code see Google Sheets Vignette RMD

Once set-up you may have to log-in manually prior to running tests or checks, use

source("R/gdrive.R")

## Data Google Drive Project Setup

See the Vignette ["Google Sheets API setup using Google Cloud"](vignettes/google_sheets_api.Rmd) 
for details about setting up google sheets connection with R, which requires
a google cloud project in your institution

Note that for safety, this package only reads from google drive and it never
writes to google drive.  Therefore it only requests 'read-only' access.

## Usage

When reading in data sheets, you provide a URL for a datasheet that exists in any folder that you have access to.   The system will attempt to log you into to google drive and requests your permission for this code to access files on your behalf.   

```R
gurl<- 'https://docs.google.com/spreadsheets/d/1w6sYozjybyd53eeiTdigrRTonteQW2KXUNZNmEhQyM8/edit?gid=0#gid=0'
study_data<- read_commrules_sheet(gurl)

References

@article{van2021data, title={Data validation infrastructure for R}, author={van der Loo, Mark PJ and de Jonge, Edwin}, journal={Journal of Statistical Software}, year={2021}, volume ={97}, issue = {10}, pages = {1-33}, doi={10.18637/jss.v097.i10}, url = {https://www.jstatsoft.org/article/view/v097i10} }