Get your Research Project/Article Organized, Shareable and Reproducible using R and friends

Reproducible research practices are central for scholarly dissemination and communication. The importance of sharing data and computational code has been highlighted extensively to promote transparency and replication of scientific results. Data and code sharing practices are rare in the plant pathology, but is expect to increase in the near future. It is urgent that plant pathologists get training in how to organize their research in a way that promotes effective project management, reproducibility, collaboration and sharing of results. Standardized procedures for the collection and systematic organization of research outcomes (data files, codes, graphs, manuscript, etc.), known as "research compendium", has been proposed and tools are available to facilitate its production. Participants will learn how to use existing R tools for producing a research compendium for optimizing workflow and enhancing the efficiency of analysis, re-analysis and sharing. Other tools will include introductions to the Open Science Framework, websites for generating Digital Object Identifiers (DOI), how and why to establish pre-print publications, and tools for for making independent and automated analyses.

Transcript

1. Get your Research Project/Article
   Organized, Shareable and Reproducible
   using and friends
   Emerson M. Del Ponte
   Open Plant Pathology
   Universidade Federal de Viçosa
   4-h Workshop
   

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2. Why Reproducible Research (RR)?
   Data + Protocols + Code
   Knowledge
   Reproducible
   Documenting and Sharing
   Efficiency
   short term effect
   Accessibility
   short and long term effect
   Transparency
   Information
   pen
   Reproducibility
   Research
   Practices
   Replicability
   

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3. - Sponsors/journals require data (standard in molecular)
   - Work more efficiently and facilitate collaborations
   - Improved reproducibility (data and/or methods)
   - Technology (less cumbersome) is becoming available
   - Enhanced visibility and transparency
   - Multiple citable outcomes: data, code, manuscript, etc.
   Why to change/learn new things?
   

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4. When RR?
   Idea
   Register
   (proposal)
   Run experiments
   Get data
   Analyze
   Communicate
   

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5. Idea
   Register
   Preregistration
   Of studies
   University/Institution
   Laboratory computer
   When RR?
   

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6. Idea
   Register
   Preregistration
   of Studies
   University/Institution
   Laboratory computer
   https://osf.io/6tsnj
   When RR?
   

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7. Run experiments
   When RR?
   

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8. Run experiments
   When RR?
   

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9. Get data
   Submit datasets
   accompanying data
   descriptors to:
   Discipline-specific repositories
   Generalist repositories
   When RR?
   

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10. Analyze Research Compendium
    When RR?
    

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11. Communicate
    Abstract
    When RR?
    Preprint
    OA paper
    Paywalled paper
    Quick Files
    Talk Poster
    

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12. How RR?
    Science
    Collect
    Analyse
    Publish
    Write
    Summarise
    Reproduce
    Re-analyse
    (meta-analysis)
    Share data
    Open Repository
    Share code
    open/free tools
    Collaborative tools
    Citation manager
    Pre-prints
    Open Access
    

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13. Sparks et al. (unpublished)
    101
    99
    Count
    How are we plant pathologists doing?
    

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14. Sparks et al. (unpublished)
    No
    Upon request
    Paywalled
    Free access
    Are data made available?
    

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15. Sparks et al. (unpublished)
    No
    Free access
    Are codes made available?
    

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16. Sparks et al. (unpublished)
    No
    Name only
    Version #
    Full citation
    Is Software properly cited?
    

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17. Sparks et al. (unpublished)
    What are the software being used?
    

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18. - Lack of interest/knowledge (supplemental rarely posted)
    - Low incentive/pressure - that may change!
    - Perception that it takes time and effort
    - Document data and code
    - Versioning code and maintaining
    - FOBS - Fear of being scooped?
    - Not valued/taught in our graduate programs
    Why is it being so slow to adopt RR?
    

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19. Tools
    Workflows
    Environments
    Collaborative
    & sharing
    platforms
    Ok, I want do it differently, but how?
    Research Project
    Organized
    Documented
    Shared
    Accessible
    Reproducible
    

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20. Data wrangling - Excel
    Data visualization - Excel
    Data analysis - SAS, STATA
    Scientific plots - SigmaPlot
    Text editor - MSWord
    BIB
    Save money in Software! Use R and Friends
    

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21. Start small! Then build on it...
    Article
    Article (+ preprint)
    Supplemental (zip)
    - Protocols
    - Data
    Article + preprint
    Repository (citable)
    - Protocols
    - Data
    - Code
    Article + preprint
    Research compendium
    - Raw Data
    - Clean Data
    - Analysis (reproducible)
    Reproducibility
    0
    1
    2
    3
    level
    

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22. A new research/submission workflow?
    Project
    Data Analysis
    Manuscript
    Preprint
    Journal Submission
    system
    Early view
    Final publication
    Poster/Talk
    Research
    Compendium
    

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23. http://inundata.org/talks/rstd19/
    https://research-compendium.science/
    How RR?
    Source: https://research-compendium.science/
    

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24. http://inundata.org/talks/rstd19/
    How RR ?
    

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25. https://www.tandfonline.com/doi/full/10.1080/00031305.2017.1375986 https://peerj.com/preprints/3192/
    How RR?
    

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26. R package structure as inspiration
    Small
    Medium
    Large
    

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27. BIB
    Minimal RC
    Short RC
    webpage
    Full RC
    Website + manuscript
    Structures/templates for RC (not a package)
    CSL
    

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28. Let's work?
    5 Workout Sessions (45 min each)
    1) Introduction
    2) RStudio project + GitHub
    3) The research compendium
    4) Manuscript in RMarkdown
    5) Packages for automating tasks & RStudio Cloud
    

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29. Everything starts as a PROJECT!
    

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30. RStudio and his friend Git
    1. Download and install Git (GitHub Desktop)
    2. Download and install RStudio
    3. Go to GitHub and create a new repository
    Let's practice
    

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31. RStudio and his friend Git
    1. Create a new RStudio Project from Git
    2. Add your repository URL
    Your turn
    

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33. 1. Clone a repository (open in Desktop)
    2. https:/
    /github.com/emdelponte/paper-FHB-yield-loss
    3. Change files
    4. Create a pull request to the owner
    

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34. Let's explore a research compendium
    Short RC
    webpage
    1. Fork the repository (short webpage compendium)
    a. https:/
    /github.com/emdelponte/RC-example-webpage
    2. Explore the files
    3. Reproduce the analysis
    4. Knit to generate the webpage
    5. Commit and push to your GH
    

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35. GitHub and Open Science Framework
    1. Link GitHub and Open Science Framework
    2. Create an OSF Project
    

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36. 1. Link GitHub and Open Science Framework
    2. Name your project
    3. Enable GitHub Add-on
    GitHub and Open Science Framework
    

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37. 1. Link GitHub and Open Science Framework
    2. Name your project
    3. Select GitHub Add-on
    4. Configure Add-on
    GitHub and Open Science Framework
    

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38. 1. Finish description
    GitHub and Open Science Framework
    

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39. Let's practice: Data management
    1. Create/Open an RMarkdown file
    a. Modify the output parameters
    2. Load data
    a. .csv file
    b. .xlsx file
    c. .gsheet file
    3. Add some basic commenting
    4. Do some basic wrangling
    5. Export data to .csv
    

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40. How RR for data management
    Get data
    Data file types
    Binary
    Text files
    web-based
    

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41. Data management: must read!
    

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42. Organizing, naming, shaping!
    Data management
    Broman and Woo (2018)
    

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43. Analyze
    

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44. Analyze
    

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45. Fork or download a Repository
    1. Fork the RC as webpage template
    a. https://github.com/emdelponte/RC-example-webpage
    2. Download the files from GitHub
    3. Start with a new RStudio Project + Git
    4. Reproduce the analysis
    5. Change some content/parameters
    6. Push it to your GH account
    

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46. Add local folder and create a GitHub Repository
    

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47. Add local folder and create a GitHub Repository
    

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48. Let's practice
    1. Fork the RC as website template
    a. https:/
    /github.com/emdelponte/RC-example-website
    2. Change and/or generate the website (knit)
    3. Push changes to your GitHub
    4. Create a GH webpage for it
    5. Send it to OSF project
    

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49. RMarkdown templates
    1. RMarkdown html from the basic RStudio templates
    2. Rmdformats: https:/
    /github.com/juba/rmdformats
    3. Distill for RMarkdown: https:/
    /github.com/rstudio/distill
    4. RMarkdown websites:
    https:/
    /rmarkdown.rstudio.com/lesson-13.html
    

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50. YML header
    Manuscript in RMarkdown?
    ---
    title: "The title goes here"
    author: "Author name goes here"
    output:
    html_document: default
    word_document:
    reference_docx: template.docx
    linestretch: 2
    link-citations: yes
    linkcolor: blue
    csl: chicago-author-date.csl
    bibliography: crossref.bib
    ---
    BIB
    CSL
    https://www.zotero.org/styles
    

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51. Automating RC website creation
    Workflowr package
    Organized
    ● Provides a project template with organized subdirectories
    ● Mixes code and results with R Markdown
    ● Uses Git to version both source code and results
    Reproducible
    ● Displays the code version used to create each result
    ● Runs each analysis in an isolated R session
    ○ Records the session information of each analysis
    ○ Sets the same seed for random number generation for each analysis
    Shareable
    ○ Creates a website to present your research results
    ○ Documents how to host your website for free via GitHub Pages or GitLab Pages
    ○ Creates links to past versions of results
    https://jdblischak.github.io/workflowr
    

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52. Workflowr pkg
    https:/
    /jdblischak.github.io/workflowr/articles/wflow-01-getting-started.html
    

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53. rrtools, an R package to create RC as package!
    https://github.com/benmarwick/rrtools
    

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54. rrtools, pkg to facilitate creation of RC as a pkg!
    

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55. rrtools, pkg to facilitate creation of RC as a pkg!
    https:/
    /rstudio.cloud/project/424109
    

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56. Let's make it reproducible for future?
    

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57. remotes::install_github("karthik/holepunch")
    library(holepunch)
    write_compendium_description(package = "RC template ",
    description = "A template for a research compendium")
    write_dockerfile(maintainer = "Your name")
    generate_badge() # This generates a badge for your readme.
    # At this time push the code to GitHub
    # And click on the badge or use the function below to get the build
    # ready ahead of time.
    build_binder()
    Let's make it reproducible for future?
    

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58. https:/
    /github.com/emdelponte/RC-template
    RC was a website template
    Live examples:
    https://emdelponte.github.io/paper-FHB-Brazil-meta-analysis/
    https://emdelponte.github.io/paper-fungicides-whitemold/
    https://mladencucak.github.io/AnalysisPLBIreland/index.html
    

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59. www.openplantpathology.org
    

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