Last updated: 2019-12-05
Checks: 2 0
Knit directory: reproducible_bioinformatics/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| 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 | 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. |
This workshop will discuss guidelines for ensuring reproducibility in bioinformatic data analysis and demonstrate how we can adhere to these guidelines through the use of various computational tools. You will be introduced to Conda and Docker and shown how they can be used to simplify the deployment of bioinformatics tools and create isolated software environments ensuring that analyses can be reproduced. The workshop will also discuss approaches for organising computational projects using the workflowr R package. By the end of the workshop, you will have learned some ideas behind carrying out reproducible research and can better communicate and share your work in a reproducible manner.