Last updated: 2025-03-24
Checks: 2 0
Knit directory: analysis-user-group/
This reproducible R Markdown analysis was created with workflowr (version 1.7.1). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version 30080eb. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for
the analysis have been committed to Git prior to generating the results
(you can use wflow_publish or
wflow_git_commit). workflowr only checks the R Markdown
file, but you know if there are other scripts or data files that it
depends on. Below is the status of the Git repository when the results
were generated:
Ignored files:
Ignored: .DS_Store
Ignored: .Rhistory
Ignored: analysis/.DS_Store
Ignored: analysis/.Rhistory
Unstaged changes:
Modified: analysis/_site.yml
Modified: workflow.R
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were
made to the R Markdown (analysis/202504.Rmd) and HTML
(docs/202504.html) files. If you’ve configured a remote Git
repository (see ?wflow_git_remote), click on the hyperlinks
in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | 1d1c076 | DrThomasOneil | 2025-03-24 | Build site. |
| html | 956ba9b | DrThomasOneil | 2025-03-24 | Build site. |
| Rmd | 6b72e34 | DrThomasOneil | 2025-03-24 | wflow_publish(c("analysis/*.Rmd")) |
| html | d600337 | DrThomasOneil | 2025-03-18 | Build site. |
| html | b537f69 | DrThomasOneil | 2025-03-18 | Build site. |
| Rmd | 2e41666 | DrThomasOneil | 2025-03-18 | wflow_publish(c("analysis/*.Rmd")) |
| html | b7982e9 | DrThomasOneil | 2025-03-16 | Build site. |
| html | fc5dd81 | DrThomasOneil | 2025-03-16 | Build site. |
| Rmd | b50c80e | DrThomasOneil | 2025-03-16 | wflow_publish(c("analysis/*.Rmd")) |
| html | 8e1c1a3 | DrThomasOneil | 2025-03-16 | Build site. |
| Rmd | d75e5ae | DrThomasOneil | 2025-03-16 | wflow_publish(c("analysis/*.Rmd")) |
Flow Cytometry Analysis: Leveraging Software and R for Deeper Insights
This DRSN series explores how both traditional software and R-based approaches can complement each other in flow cytometry analysis. Whether you rely on software, are curious about coding, or want to integrate both approaches, this series will help you expand your analytical toolkit.
Monday 15th April (WIMR Seminar Room & Zoom)
Seminar (11am)
We’ll first compare the strengths of GUI-based tools like FlowJo with
the flexibility of coding.
Speakers: Suat Dervish, Nicole Fewings
(lunch from 12pm)
In-focus Workshop (1 – 3pm)
We’ll hold a discussion on key analytical considerations and available R packages.
Speakers: Givanna Putri, FElix Marsh-Wakefield, Elijah Willie
Monday 28h April (WIMR Room C2.31 & Zoom)
Programming workshop (1 – 3pm)
The final hands-on session will introduce participants to performing flow cytometry analysis in R, providing a practical workflow for data visualization, summarization, and reproducibility.
Demonstrators: Thomas O’Neil, Nicole Fewings
Sign up for these events:
