Last updated: 2019-12-05

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Knit directory: reproducible_bioinformatics/

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Rmd 0b04728 davetang 2019-12-05 wflow_publish(files = "analysis/*.Rmd")
html 5dc4fe0 davetang 2019-12-05 Build site.
Rmd 179c2bb davetang 2019-12-05 wflow_publish(files = c(“analysis/conda.Rmd”, “analysis/docker.Rmd”, “analysis/index.Rmd”,
html 9aa9aa4 davetang 2019-12-05 Build site.
Rmd ec7204f davetang 2019-12-05 wflow_publish(files = c(“analysis/about.Rmd”, “analysis/conda.Rmd”, “analysis/docker.Rmd”,
html 2f6c2fd Dave Tang 2019-12-05 Build site.
Rmd f19271d Dave Tang 2019-12-05 wflow_publish(files = c(“analysis/docker.Rmd”, “analysis/index.Rmd”))
html 7b114c5 First Last 2019-12-04 Build site.
Rmd a4180a4 First Last 2019-12-04 wflow_publish(files = c(“analysis/conda.Rmd”, “analysis/index.Rmd”))
html 60a5900 First Last 2019-12-04 Build site.
html d83e8cb davetang 2019-12-03 Build site.
Rmd 88b592b davetang 2019-12-03 New workflowr project
Rmd 4e0dfff davetang 2019-12-03 Start workflowr project.

My aim for this workshop is to introduce computational tools and demonstrate how they can be used to help promote reproducibility when performing bioinformatic analyses. Many of these tools help adhere to these Ten Simple Rules for Reproducible Computational Research:

• Rule 1: For Every Result, Keep Track of How It Was Produced
• Rule 2: Avoid Manual Data Manipulation Steps
• Rule 3: Archive the Exact Version Versions of All External Programs Used
• Rule 4: Version Control All Custom Scripts
• Rule 5: Record All Intermediate Results, When Possible in Standardised Formats
• Rule 6: For Analyses That Include Randomness, Note Underlying Random Seeds
• Rule 7: Always Store Raw Data behind Plots
• Rule 8: Generate Hierarchical Analysis Output, Allowing Layers of Increasing Detail to Be Inspected
• Rule 9: Connect Textual Statements to Underlying Results