ReproducibleResearch.ctv

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<CRANTaskView>
  <name>ReproducibleResearch</name>
  <topic>Reproducible Research</topic>
  <maintainer email="jdblischak@gmail.com">John Blischak, Alison Hill</maintainer>
  <version>2021-12-20</version>
  <info>
    <p>
      The goal of reproducible research is to tie specific instructions to data
      analysis and experimental data so that scholarship can be recreated,
      better understood and verified. Packages in R for this purpose can be
      split into groups for: literate programming, pipeline toolkits, package
      reproducibility, project workflows, code/data formatting tools, format
      convertors, and object caching.
    </p>
    <p>
      The maintainers gratefully acknowledge
      <a href="https://github.com/annakrystalli">Anna Krystalli</a>,
      <a href="https://github.com/topepo">Max Kuhn</a>,
      <a href="https://github.com/wlandau"> Will Landau</a>,
      <a href="https://github.com/benmarwick">Ben Marwick</a>, and
      <a href="https://github.com/nuest">Daniel Nüst</a>
      for their useful feedback and contributions.
    </p>
    <p>
      If you would like to recommend a package to be included in this task view,
      please open a
      <a href="https://github.com/jdblischak/reproducible-research-ctv/issues/new?template=package_suggestion.md">GitHub Issue</a>
      to discuss.
    </p>
    <h1>Literate Programming</h1>
    <p>
      The primary way that R facilitates reproducible research is using a
      document that is a combination of content and data analysis code. The
      <code>Sweave</code> function (in the base R utils package) and the
      <pkg>knitr</pkg> package can be used to blend the subject matter and R
      code so that a single document defines the content and the analysis. The
      <pkg>brew</pkg>  and <pkg>R.rsp</pkg> packages contain alternative
      approaches to embedding R code into various markups.
    </p>
    <p>
      The resources for literate programming are best organized by the document
      type/markup language:
    </p>
    <h2>LaTeX</h2>
    <p>
      Both <code>Sweave</code> and <pkg>knitr</pkg> can process LaTeX files.
      <pkg>lazyWeave</pkg> can create LaTeX documents from scratch.
    </p>
    <p>
      The <pkg>knitr</pkg> and <pkg>rmarkdown</pkg> packages (along with
      <a href="https://pandoc.org/">pandoc</a>) can be used to create slides
      using the LaTeX <a href="https://ctan.org/pkg/beamer">beamer</a> class.
    </p>
    <p>
      Object Conversion Functions:
    </p>
    <ul>
      <li>
        <i>summary tables/statistics</i>:
          <pkg>Hmisc</pkg>,
          <pkg>NMOF</pkg>,
          <pkg>papeR</pkg>,
          <pkg>quantreg</pkg>,
          <pkg>rapport</pkg>,
          <pkg>reporttools</pkg>,
          <pkg>sparktex</pkg>,
          <pkg>tables</pkg>,
          <pkg>xtable</pkg>,
          <pkg>ztable</pkg>
      </li>
      <li>
        <i>tables/cross-tabulations</i>:
          <pkg>Hmisc</pkg>,
          <pkg>huxtable</pkg>,
          <pkg>lazyWeave</pkg>,
          <pkg>knitLatex</pkg>,
          <pkg>knitr</pkg>,
          <pkg>reporttools</pkg>,
          <pkg>ztable</pkg>
      </li>
      <li>
        <i>graphics</i>:
          <pkg>animation</pkg>,
          <pkg>Hmisc</pkg>,
          <code>grDevices:::pictex</code>,
          <pkg>sparktex</pkg>,
          <pkg>tikzDevice</pkg>
      </li>
      <li>
        <i>statistical models/methods</i>:
          <pkg>apsrtable</pkg>,
          <pkg>memisc</pkg>,
          <pkg>quantreg</pkg>,
          <pkg>rms</pkg>,
          <pkg>stargazer</pkg>,
          <pkg>suRtex</pkg>,
          <pkg>texreg</pkg>,
          <pkg>xtable</pkg>,
          <pkg>ztable</pkg>
      </li>
      <li>
        <i>bibtex</i>:
          <pkg>bibtex</pkg> and
          <pkg>RefManageR</pkg>
      </li>
      <li>
        <i>others</i>:
          <pkg>latex2exp</pkg> converts LaTeX equations to <tt>plotmath</tt>
          expressions.
      </li>
    </ul>
    <p>
      Miscellaneous Tools
    </p>
    <ul>
      <li>
        <pkg>Hmisc</pkg> contains a function to correctly escape special
        characters. Standardized exams can be created using the
        <pkg>exams</pkg> package.
      </li>
    </ul>
    <h2>HTML</h2>
    <p>
      The <pkg>knitr</pkg> package can process HTML files directly.
      <code>Sweave</code> can also work with HTML by way of the <pkg>R2HTML</pkg>
      package. <pkg>lazyWeave</pkg> can create HTML format documents from
      scratch.
    </p>
    <p>
      For HTML slides, a combination of the <pkg>knitr</pkg> and
      <pkg>rmarkdown</pkg> packages (along with <a
      href="https://pandoc.org/">pandoc</a>) can be used to create slides
      using <a
      href="https://bookdown.org/yihui/rmarkdown/ioslides-presentation.html">ioslides</a>,
      <a href="https://revealjs.com/">reveal.js</a>, <a
      href="https://www.w3.org/Talks/Tools/Slidy2/">Slidy</a>, or <a
      href="https://remark.js.org/">remark.js</a> (from the
      <pkg>xaringan</pkg> package).
    </p>
    <p>
      Object Conversion Functions:
    </p>
    <ul>
      <li>
        <i>summary tables/statistics</i>:
          <pkg>stargazer</pkg>
      </li>
      <li>
        <i>tables/cross-tabulations</i>:
          <pkg>DT</pkg>,
          <pkg>flextable</pkg>,
          <pkg>formattable</pkg>,
          <pkg>gt</pkg>,
          <pkg>htmlTable</pkg>,
          <pkg>HTMLUtils</pkg>,
          <pkg>huxtable</pkg>,
          <pkg>hwriter</pkg>,
          <pkg>knitr</pkg>,
          <pkg>lazyWeave</pkg>,
          <pkg>texreg</pkg>,
          <pkg>ztable</pkg>
      </li>
      <li>
        <i>statistical models/methods</i>:
          <pkg>rapport</pkg>,
          <pkg>stargazer</pkg>,
          <pkg>xtable</pkg>
      </li>
      <li>
        <i>others</i>:
          <pkg>knitcitations</pkg>,
          <pkg>RefManageR</pkg>
      </li>
    </ul>
    <p>
      Miscellaneous Tools:
        <pkg>htmltools</pkg> has various tools for working with HTML.
        <pkg>tufterhandout</pkg> can create Tufte-style handouts.
    </p>
    <h2>Markdown</h2>
    <p>
      The <pkg>knitr</pkg> package can process markdown files without
      assistance. The packages  <pkg>markdown</pkg> and <pkg>rmarkdown</pkg>
      have general tools for working with documents in this format.
      <pkg>lazyWeave</pkg> can create markdown format documents from scratch.
      Also, the <pkg>ascii</pkg> package can write R objects to the <a
      href="https://asciidoc.org/">AsciiDoc</a> format.
    </p>
    <p>
      Object Conversion Functions:
    </p>
    <ul>
      <li>
        <i>summary tables/statistics</i>:
          <pkg>papeR</pkg>
      </li>
      <li>
        <i>tables/cross-tabulations</i>:
          <pkg>DT</pkg>,
          <pkg>formattable</pkg>,
          <pkg>htmlTable</pkg>,
          <pkg>knitr</pkg>,
          <pkg>lazyWeave</pkg>,
          <pkg>papeR</pkg>
      </li>
      <li>
        <i>statistical models/methods</i>:
          <pkg>pander</pkg>,
          <pkg>papeR</pkg>,
          <pkg>rapport</pkg>,
          <pkg>texreg</pkg>
      </li>
      <li>
        <i>others</i>:
          <pkg>RefManageR</pkg>
      </li>
    </ul>
    <p>
      Miscellaneous Tools:
        <pkg>tufterhandout</pkg> can create Tufte-style handouts.
        <pkg>kfigr</pkg> allows for figure indexing in markdown documents.
    </p>
    <h2>Microsoft/LibreOffice Formats</h2>
    <p>
      The <pkg>officer</pkg> (formerly ReporteRs and before that R2DOCX) package
      can create <tt>docx</tt> and <tt>pptx</tt> files. <pkg>R2wd</pkg> (windows
      only) can also create Word documents from scratch and <pkg>R2PPT</pkg>
      (also windows only) can create PowerPoint slides. The <pkg>rtf</pkg>
      package does the same for Rich Text Format documents. The
      <pkg>openxlsx</pkg> package creates <tt>xlsx</tt> files. The
      <pkg>readODS</pkg> package can read and write Open Document Spreadsheets.
    </p>
    <p>
      Object Conversion Functions:
    </p>
    <ul>
      <li>
        <i>tables/cross-tabulations</i>:
          <pkg>flextable</pkg>,
          <pkg>huxtable</pkg>,
          <pkg>pharmaRTF</pkg>,
          <pkg>r2rtf</pkg>
      </li>
      <li>
        <i>graphics</i>:
          <pkg>mschart</pkg>
      </li>
      <li>
        <i>others</i>:
          <pkg>unrtf</pkg>
      </li>
    </ul>
    <h1>Pipeline Toolkits</h1>
    <p>
      <a href="https://github.com/pditommaso/awesome-pipeline">Pipeline
      toolkits</a> help maintain and verify reproducibility. They synchronize
      computational output with the underlying code and data, and they tell the
      user when everything is up to date. In other words, they provide concrete
      evidence that results are re-creatable from the starting materials, and
      the data analysis project does not need to rerun from scratch. The
      <pkg>targets</pkg> package is such a pipeline toolkit. It is similar to <a
      href="https://www.gnu.org/software/make/">GNU Make</a>, but it is
      R-focused.
    </p>
    <ul>
      <li>
        <pkg>drake</pkg>: A general-purpose computational engine for data
        analysis, drake rebuilds intermediate data objects when their
        dependencies change, and it skips work when the results are already up
        to date.
      </li>
      <li>
        <pkg>flowr</pkg>: This framework allows you to design and implement
        complex pipelines, and deploy them on your institution's computing
        cluster.
      </li>
      <li>
        <pkg>makepipe</pkg>: A suite of tools for transforming an existing
        workflow into a self-documenting pipeline with very minimal upfront
        costs.
      </li>
      <li>
        <pkg>repo</pkg>: A data manager meant to avoid manual storage/retrieval
        of data to/from the file system.
      </li>
      <li>
        <pkg>targets</pkg>: As a pipeline toolkit for Statistics and data
        science in R, the 'targets' package brings together function-oriented
        programming and 'Make'-like declarative workflows.
      </li>
    </ul>
    <h1>Package Reproducibility</h1>
    <p>
      R has various tools for ensuring that specific packages versions can be
      required for analyses. As an example, the <pkg>renv</pkg> package installs
      packages in project-specific directory, records "snapshots" of the current
      package versions in a "lockfile", and restores the package setup on a
      different machine.
    </p>
    <ul>
      <li>
        <pkg>checkpoint</pkg>: Allows you to install packages as they existed on
        CRAN on a specific snapshot date as if you had a CRAN time machine.
      </li>
      <li>
        <pkg>groundhog</pkg>: Make R scripts that rely on packages reproducible,
        by ensuring that every time a given script is run, the same version of
        the used packages are loaded.
      </li>
      <li>
        <pkg>liftr</pkg>: Persistent reproducible reporting by containerization
        of R Markdown documents.
      </li>
      <li>
        <pkg>miniCRAN</pkg>: Makes it possible to create an internally
        consistent repository consisting of selected packages from CRAN-like
        repositories.
      </li>
      <li>
        <pkg>packrat</pkg>: Manage the R packages your project depends on in an
        isolated, portable, and reproducible way.
      </li>
      <li>
        <pkg>rbundler</pkg>: Manages a project-specific library for dependency
        package installation.
      </li>
      <li>
        <pkg>renv</pkg>: Create and manage project-local R libraries, save the
        state of these libraries to a 'lockfile', and later restore your library
        as required.
      </li>
      <li>
        <pkg>Require</pkg>: A single key function, 'Require' that wraps
        'install.packages', 'remotes::install_github',
        'versions::install.versions', and 'base::require' that allows for
        reproducible workflows.
      </li>
      <li>
        <pkg>switchr</pkg>: Provides an abstraction for managing, installing,
        and switching between sets of installed R packages.
      </li>
    </ul>
    <h1>Project Workflows</h1>
    <p>
      Successfully completing a data analysis project often requires much more
      than statistics and visualizations. Efficiently managing the code, data,
      and results as the project matures helps reduce stress and errors. The
      following "workflow" packages assist the R programmer by managing project
      infrastructure and/or facilitating a reproducible workflow.
    </p>
    <p>
      Workflow utility packages provide single-use functions to implement
      project infrastructure or solve a specific problem. As a typical example,
      <code>usethis::use_git()</code> initializes a Git repository, ignores
      common R files, and commits all project files.
    </p>
    <ul>
      <li>
        <pkg>cabinets</pkg>: Creates project specific directory and file
        templates that are written to a .Rprofile file.
      </li>
      <li>
        <pkg>here</pkg>: Constructs paths to your project's files.
      </li>
      <li>
        <pkg>prodigenr</pkg>: Create a project directory structure, along with
        typical files for that project.
      </li>
      <li>
        <pkg>RepoGenerator</pkg>: Generates a project and repo for easy
        initialization of a GitHub repo for R workshops.
      </li>
      <li>
        rrtools (<a href="https://github.com/benmarwick/rrtools">GitHub
        only</a>): Instructions, templates, and functions for making a basic
        compendium suitable for doing reproducible research with R.
      </li>
      <li>
        starters (<a href="https://github.com/lockedata/starters">GitHub
        only</a>): Setting up R project directories for teaching, presenting,
        analysis, package development can be a pain. starters shortcuts this by
        creating folder structures and setting good defaults for you.
      </li>
      <li>
        <pkg>usethis</pkg>: Automate package and project setup tasks that are
        otherwise performed manually.
      </li>
    </ul>
    <p>
      Workflow framework packages provide an organized directory structure and
      helper functions to assist during the development of the project. As a
      typical example, <code>ProjectTemplate::create.project()</code> creates an
      organized setup with many subdirectories, and
      <code>ProjectTemplate::run.project()</code> executes each R script that is
      saved in the <code>src/</code> subdirectory.
    </p>
    <ul>
      <li>
        <pkg>exreport</pkg>: Analysis of experimental results and automatic
        report generation in both interactive HTML and LaTeX.
      </li>
      <li>
        <pkg>madrat</pkg>: Provides a framework which should improve
        reproducibility and transparency in data processing. It provides
        functionality such as automatic meta data creation and management,
        rudimentary quality management, data caching, work-flow management and
        data aggregation.
      </li>
      <li>
        <pkg>makeProject</pkg>: This package creates an empty framework of files
        and directories for the "Load, Clean, Func, Do" structure described by
        Josh Reich.
      </li>
      <li>
        <pkg>orderly</pkg>: Order, create and store reports from R.
      </li>
      <li>
        <pkg>projects</pkg>: Provides a project infrastructure with a focus on
        manuscript creation.
      </li>
      <li>
        <pkg>ProjectTemplate</pkg>: Provides functions to automatically build a
        directory structure for a new R project. Using this structure,
        'ProjectTemplate' automates data loading, preprocessing, library
        importing and unit testing.
      </li>
      <li>
        <pkg>reportfactory</pkg>: Provides an infrastructure for handling
        multiple R Markdown reports, including automated curation and
        time-stamping of outputs, parameterisation and provision of helper
        functions to manage dependencies.
      </li>
      <li>
        <pkg>represtools</pkg>: Reproducible research tools automates the
        creation of an analysis directory structure and work flow. There are R
        markdown skeletons which encapsulate typical analytic work flow steps.
        Functions will create appropriate modules which may pass data from one
        step to another.
      </li>
      <li>
        <pkg>tinyProject</pkg>: Creates useful files and folders for data
        analysis projects and provides functions to manage data, scripts and
        output files.
      </li>
      <li>
        <pkg>worcs</pkg>: Create reproducible and transparent research projects
        in 'R'. This package is based on the Workflow for Open Reproducible Code
        in Science (WORCS), a step-by-step procedure based on best practices for
        Open Science.
      </li>
      <li>
        <pkg>workflowr</pkg>: Provides a workflow for your analysis projects by
        combining literate programming ('knitr' and 'rmarkdown') and version
        control ('Git', via 'git2r') to generate a website containing
        time-stamped, versioned, and documented results.
      </li>
      <li>
        <pkg>zoon</pkg>: Reproducible and remixable species distribution
        modelling.
      </li>
    </ul>
    <h1>Formatting Tools</h1>
    <p>
      <pkg>formatR</pkg> and <pkg>styler</pkg> can be used to format R code.
    </p>
    <p>
      <pkg>highlight</pkg> and <pkg>highr</pkg> can be used to color R code.
    </p>
    <p>
      Packages <pkg>humanFormat</pkg>, <pkg>lubridate</pkg>,
      <pkg>prettyunits</pkg>, and <pkg>rprintf</pkg> have functions to better
      format data.
    </p>
    <h1>Format Convertors </h1>
    <p>
      <pkg>pander</pkg> can be used for rendering R objects into <a
      href="http://pandoc.org/">Pandoc's</a> markdown. <pkg>knitr</pkg> has the
      function <tt>pandoc</tt> that can call an installed version of <a
      href="http://pandoc.org/">Pandoc</a> to convert documents between formats
      such as Markdown, HTML, LaTeX, PDF and Word. <pkg>tth</pkg> facilitates
      TeX to HTML/MathML conversions.
    </p>
    <h1>Object Caching Packages</h1>
    <p>
      When using <code>Sweave</code> and <pkg>knitr</pkg> it can be advantageous
      to <i>cache</i> the results of time consuming code chunks if the document
      will be re-processed (i.e. during debugging). <pkg>knitr</pkg> facilitates
      object caching and the Bioconductor package <bioc>weaver</bioc> can be
      used with <code>Sweave</code>.
    </p>
    <p>
      Non-literate programming packages to facilitating caching/archiving are
      <pkg>archivist</pkg>, <pkg>R.cache</pkg>, <pkg>reproducible</pkg>,
      <pkg>storr</pkg>, and <pkg>trackr</pkg>.
    </p>
  </info>
  <packagelist>
    <pkg>animation</pkg>
    <pkg>apsrtable</pkg>
    <pkg>archivist</pkg>
    <pkg>ascii</pkg>
    <pkg>bibtex</pkg>
    <pkg>brew</pkg>
    <pkg>cabinets</pkg>
    <pkg>checkpoint</pkg>
    <pkg>drake</pkg>
    <pkg>DT</pkg>
    <pkg>exams</pkg>
    <pkg>exreport</pkg>
    <pkg>flextable</pkg>
    <pkg>flowr</pkg>
    <pkg>formatR</pkg>
    <pkg>formattable</pkg>
    <pkg>groundhog</pkg>
    <pkg>here</pkg>
    <pkg>highlight</pkg>
    <pkg>highr</pkg>
    <pkg>gt</pkg>
    <pkg priority="core">Hmisc</pkg>
    <pkg>htmlTable</pkg>
    <pkg>htmltools</pkg>
    <pkg>HTMLUtils</pkg>
    <pkg>humanFormat</pkg>
    <pkg>huxtable</pkg>
    <pkg>hwriter</pkg>
    <pkg>latex2exp</pkg>
    <pkg>lazyWeave</pkg>
    <pkg>liftr</pkg>
    <pkg>lubridate</pkg>
    <pkg>kfigr</pkg>
    <pkg>knitcitations</pkg>
    <pkg>knitLatex</pkg>
    <pkg priority="core">knitr</pkg>
    <pkg>madrat</pkg>
    <pkg>makepipe</pkg>
    <pkg>makeProject</pkg>
    <pkg>markdown</pkg>
    <pkg>memisc</pkg>
    <pkg>miniCRAN</pkg>
    <pkg>mschart</pkg>
    <pkg>NMOF</pkg>
    <pkg>officer</pkg>
    <pkg>openxlsx</pkg>
    <pkg>orderly</pkg>
    <pkg>packrat</pkg>
    <pkg>pander</pkg>
    <pkg>papeR</pkg>
    <pkg>pharmaRTF</pkg>
    <pkg>prettyunits</pkg>
    <pkg>prodigenr</pkg>
    <pkg>projects</pkg>
    <pkg>ProjectTemplate</pkg>
    <pkg>quantreg</pkg>
    <pkg>R.cache</pkg>
    <pkg>R.rsp</pkg>
    <pkg priority="core">R2HTML</pkg>
    <pkg>R2PPT</pkg>
    <pkg>r2rtf</pkg>
    <pkg>R2wd</pkg>
    <pkg>rapport</pkg>
    <pkg>rbundler</pkg>
    <pkg>readODS</pkg>
    <pkg>RefManageR</pkg>
    <pkg>renv</pkg>
    <pkg>repo</pkg>
    <pkg>RepoGenerator</pkg>
    <pkg>reportfactory</pkg>
    <pkg>reporttools</pkg>
    <pkg>represtools</pkg>
    <pkg>reproducible</pkg>
    <pkg>Require</pkg>
    <pkg>rmarkdown</pkg>
    <pkg priority="core">rms</pkg>
    <pkg>rprintf</pkg>
    <pkg>rtf</pkg>
    <pkg>sparktex</pkg>
    <pkg>stargazer</pkg>
    <pkg>storr</pkg>
    <pkg>styler</pkg>
    <pkg>suRtex</pkg>
    <pkg>switchr</pkg>
    <pkg>tables</pkg>
    <pkg>targets</pkg>
    <pkg>texreg</pkg>
    <pkg>tikzDevice</pkg>
    <pkg>tinyProject</pkg>
    <pkg>trackr</pkg>
    <pkg>tth</pkg>
    <pkg>tufterhandout</pkg>
    <pkg>unrtf</pkg>
    <pkg>usethis</pkg>
    <pkg>worcs</pkg>
    <pkg>workflowr</pkg>
    <pkg>xaringan</pkg>
    <pkg priority="core">xtable</pkg>
    <pkg>zoon</pkg>
    <pkg>ztable</pkg>
  </packagelist>
  <links>
    <a href="https://github.com/jdblischak/reproducible-research-ctv">GitHub repository for editing this task view</a>
    <a href="https://doi.org/10.1007/978-3-642-57489-4_89">Sweave: Dynamic Generation of Statistical Reports Using Literate Data Analysis</a>
    <a href="http://yihui.name/knitr/">knitr: Elegant, flexible and fast dynamic report generation with R</a>
    <bioc>weaver</bioc>
    <a href="http://en.wikipedia.org/wiki/Literate_Programming">Wikipedia: Literate Programming</a>
    <a href="https://hbiostat.org/rr">Harrell: Reproducible Research (Biostatistics for Biomedical Research)</a>
    <a href="http://www.econ.uiuc.edu/~roger/research/repro/">Koenker, Zeileis: On Reproducible Econometric Research</a>
    <a href="https://doi.org/10.1093/biostatistics/kxp014">Peng: Reproducible Research and Biostatistics</a>
    <a href="https://biostats.bepress.com/uwbiostat/paper194">Rossini, Leisch: Literate Statistical Practice</a>
    <a href="http://dx.doi.org/10.1214/09-AOAS291">Baggerly, Coombes: Deriving Chemosensitivity from Cell Lines: Forensic Bioinformatics and Reproducible Research in High-Throughput Biology</a>
    <a href="http://www.R-project.org/doc/Rnews/Rnews_2002-3.pdf">Leisch: Sweave, Part I: Mixing R and LaTeX</a>
    <a href="http://www.R-project.org/doc/Rnews/Rnews_2003-2.pdf">Leisch: Sweave, Part II: Package Vignettes</a>
    <a href="http://www.R-project.org/doc/Rnews/Rnews_2005-1.pdf">Betebenner: Using Control Structures with Sweave</a>
    <a href="http://www.R-project.org/doc/Rnews/Rnews_2006-2.pdf">Garbade, Burgard: Using R/Sweave in Everyday Clinical Practice</a>
    <a href="http://www.R-project.org/doc/Rnews/Rnews_2008-1.pdf">Gorjanc: Using Sweave with LyX</a>
    <a href="http://www.R-project.org/doc/Rnews/Rnews_2003-3.pdf">Lecoutre: The R2HTML Package</a>
    <a href="https://github.com/pditommaso/awesome-pipeline">List of pipeline toolkits</a>
    <a href="https://github.com/o2r-project/ctv-computational-environments#readme">Computational Environments and Reproducibility</a>
    <a href="https://www.tidyverse.org/articles/2017/12/workflow-vs-script/">Bryan: Project-oriented workflow</a>
    <a href="https://ropensci-archive.github.io/reproducibility-guide/">rOpenSci: Reproducibility in Science</a>
    <a href="https://doi.org/10.1198/106186007X178663">Temple Lang, Gentleman: Statistical Analyses and Reproducible Research</a>
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    <a href="https://yihui.org/rlp/">Xie: Write An R Package Using Literate Programming Techniques</a>
  </links>
</CRANTaskView>