UMGCCCFCSR · ATL0368 · Apr 5, 2026 · Apr 7, 2026 · Apr 7, 2026 · Apr 7, 2026
diff --git a/.vscode/settings.json b/.vscode/settings.json
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+{
+    "githubPullRequests.ignoredPullRequestBranches": [
+        "main"
+    ]
+}
diff --git a/Announcements.qmd b/Announcements.qmd
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+---
+title: "Announcements"
+format: html
+toc: TRUE
+toc-location: right
+sidebar: false
+---
+
+![](/images/WebsiteBanner.png)
+
+For previous course announcements emails, see the links below. 
+
+- January 21, 2026 [Cytometry in R - Start Date, Livestream Times, Pre-Course Materials](https://github.com/UMGCCCFCSR/CytometryInR/discussions/7) 
+
+- February 01, 2026 [Cytometry In R - Week #1 - Installing R packages](https://github.com/UMGCCCFCSR/CytometryInR/discussions/11) 
+
+- February 09, 2026 [Cytometry in R - Week # 2 - File Paths](https://github.com/UMGCCCFCSR/CytometryInR/discussions/41) 
+
+- February 16, 2026 [Cytometry in R - Week #03 - Inside an FCS File](https://github.com/UMGCCCFCSR/CytometryInR/discussions/65) 
+
+- February 22, 2026 [Cytometry in R - Week #4 - Introduction to Tidyverse](https://github.com/UMGCCCFCSR/CytometryInR/discussions/85) 
+
+- March 01, 2026 [Cytometry in R - Week #5 - Gating Sets](https://github.com/UMGCCCFCSR/CytometryInR/discussions/103) 
+
+- March 10, 2026 [No Class This Week](https://github.com/UMGCCCFCSR/CytometryInR/discussions/128) 
+
+- March 17, 2026 [Cytometry in R - Week # 6 - Visualizing with ggplot2](https://github.com/UMGCCCFCSR/CytometryInR/discussions/132) 
+
+- March 24, 2026 [Cytometry in R - Week # 07 - Applying Transformations](https://github.com/UMGCCCFCSR/CytometryInR/discussions/145) 
+
+- March 30, 2026 [Cytometry in R - Course Feedback Survey #1](https://github.com/UMGCCCFCSR/CytometryInR/discussions/151) 
+
+- April 07, 2026 [Cytometry in R - Week # 08 - Manual and Automated Gating](https://github.com/UMGCCCFCSR/CytometryInR/discussions/159) 
+
+- April 12, 2026 [Cytometry in R - Week # 09 - It's Raining Functions!](https://github.com/UMGCCCFCSR/CytometryInR/discussions/162) 
+
+- April 21, 2026 [No Class This Week](https://github.com/UMGCCCFCSR/CytometryInR/discussions/174)
+
+- April 28, 2026 [Cytometry in R - Week # 10 - Downsampling and Concatenation](https://github.com/UMGCCCFCSR/CytometryInR/discussions/179)
+
+- May 05, 2026 [Cytometry in R - Week # 11 - Data for Statistics](https://github.com/UMGCCCFCSR/CytometryInR/discussions/186)
+
+![](images/YouTubeHex.png)
diff --git a/ExistingResources.qmd b/ExistingResources.qmd
@@ -13,17 +13,29 @@ sidebar: false
 [![CC BY-SA 4.0][cc-by-sa-shield]][cc-by-sa]
 </div>
 
+<<<<<<< HEAD
 We are not the first "Cytometry in R" course, nor will we be the last. This page is linking to the already existant online Cytometry in R resources that we have encountered and benefited from during our own learning journey. May they prove useful to you as you progress your way through yours! 
+=======
+We are not the first "Cytometry in R" course, nor will we be the last. If this is your first R course, now that we are about a third of the way through the course (and you have some general R knowledge, context, and troubleshooting skills), exploring how others approached some of these same initial subjects may be useful if you want to dive deeper. 
+
+This page links to existing online Cytometry in R resources that I have encountered and benefited from during my own learning journey. Not all the code as presented may still work, as R packages evolve over time, so some troubleshooting may be necessary on your end to replicate what they show. Good luck, and may you find some useful concepts to further help you along on your own journeys! 
+
+![](images/ExistingResources.png)
+>>>>>>> e277891a345df446c1e406e18bbff78126d26c90
 
 <br>
 
 ---
 
 # Christopher Hall - Flow Cytometry Data Analysis in R
 
+<<<<<<< HEAD
 [Cytometry-R-Scripts: R scripts to help with your flow cytometry analysis](https://github.com/hally166/Cytometry-R-scripts)
 
 [R_flowcytometry_course: The files and presentation from the Cytometry Core Facility flow cytometry data analysis course in R](https://github.com/hally166/R_flowcytometry_course)
+=======
+[Christopher Hall](https://uk.linkedin.com/in/christopher1hall) (currently at University of Edinburgh) created a series of YouTube videos on how to implement flow cytometry analysis in R. In the course of an hour, he provides an overview of many of the same topics we looked at over the first 8 weeks. I first encountered these videos late 2021/early 2022, and they were immensely helpful in getting started. 
+>>>>>>> e277891a345df446c1e406e18bbff78126d26c90
 
 ### Installation and Loading Data
 
@@ -41,7 +53,10 @@ We are not the first "Cytometry in R" course, nor will we be the last. This page
 
 [(3) Flow Cytometry Data Analysis in R: gating with flowWorkspace](https://youtu.be/ijHOGHP82EY?si=87OB8t8wynJNnTf3)
 
+<<<<<<< HEAD
 
+=======
+>>>>>>> e277891a345df446c1e406e18bbff78126d26c90
 <iframe width="560" height="315" src="https://www.youtube.com/embed/ijHOGHP82EY?si=-kAM2ExNW4Og0y3U" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
 
 ### Visualization
@@ -57,7 +72,11 @@ We are not the first "Cytometry in R" course, nor will we be the last. This page
 
 # Ozette Technologies - BioC 2023 Workshop
 
+<<<<<<< HEAD
 Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew McDavid. 
+=======
+During the [Bioc2023](https://bioc2023.bioconductor.org/) conference in Boston, Arpan Neupane and Andrew McDavid, who were working at [Ozette](https://ozette.com/) gave a workshop on how to use flowWorkspace and the other R packages that they maintain. I didn't make it to the workshop (misread the room number and ended up in an interesting parallel computing talk), but went through the material on the train ride back to Baltimore. In the process, I found out about the memory benefits of using "cytosets" and how to implement `openCyto` gates, which fast forward a few years has led to much of the general workflow showcased throughout the Cytometry in R course. 
+>>>>>>> e277891a345df446c1e406e18bbff78126d26c90
 
 [Workshop: Reproducible and programmatic analysis of flow cytometry experiments with the cytoverse](https://youtu.be/_8x-prIxJgw?si=Tm-QoBQ3qc568xXD)
 
@@ -67,6 +86,7 @@ Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew
 
 ---
 
+<<<<<<< HEAD
 # Pritam Kumar Panda - Flow Cytometry Data Analysis & Visualization in R using CytoExploreR
 
 [Flow-Cytometry-analysis-in-R](https://github.com/pritampanda15/Proteomics/tree/main/Flow-Cytometry-analysis-in-R-main)
@@ -86,6 +106,12 @@ Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew
 
 # Bioinformatics DotCa - Introduction to Flow Cytometry in R
 
+=======
+# Bioinformatics DotCa - Introduction to Flow Cytometry in R
+
+One of the older Cytometry in R series on YouTube compromising a workshop series by [Ryan Brinkman](https://www.bccrc.ca/dept/tfl/people/ryan-brinkman)'s group. While I didn't encounter them until much later, they influenced many of the other video series you can see on this page. Some of the code is starting to show its age, as quite a few of the R packages have been superseeded (especially when it comes to gating and visualization), but still worthwhile watching. 
+
+>>>>>>> e277891a345df446c1e406e18bbff78126d26c90
 ### Introduction to Flow Cytometry in R
 
 [Introduction to Flow Cytometry in R](https://youtu.be/0_dN8VKhOJ0?si=Mn7UB0Gps5twqAqK)
@@ -116,8 +142,60 @@ Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew
 
 <iframe width="560" height="315" src="https://www.youtube.com/embed/xnvNCsu56Vo?si=botz0swIm31W5340" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
 
+<<<<<<< HEAD
+# Tulika Rai - Learn Innovatively With Me
+
+=======
+
+# Givanna Putri and Thomas Ashhurst - Introduction to Cytometry Data Analysis in R workshop
+
+One of Givanna Putri and Thomas Ashurst Zoom-era workshops, provides a good overview of some of the R knowledge and concepts that are needed to subsequently be able to use their [Spectre](https://immunedynamics.io/Spectre/) R package to setup a pipeline. 
+
+[ACS 2021 Workshops - Introduction to Cytometry Data Analysis in R workshop](https://youtu.be/-0QrXgk_NRw?si=GqcjU-_MQ3UvYwvI)
+
+<iframe width="560" height="315" src="https://www.youtube.com/embed/-0QrXgk_NRw?si=GqcjU-_MQ3UvYwvI" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
+
+<br>
+
+---
+
+# Ryan Duggan - Cytometry on Air
+
+Also in the older one-off workshops category, this presentation TJ Chen and Greg Finak is similar to the Bioinformatics DotCa videos in the timeline, and has been the introduction to CytometryInR for many of the authors of the other video tutorials. 
+
+[Cytometry on Air: Analyzing Flow Cytometry Data in R](https://www.youtube.com/live/_B7mo6dB3BU?si=eW20X4YWgaCoYnfw) Presentation by ,
+
+<iframe width="560" height="315" src="https://www.youtube.com/embed/_B7mo6dB3BU?si=eW20X4YWgaCoYnfw" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
+
+<br>
+
+---
+
+# Pritam Kumar Panda 
+
+One of the more recent tutorial series I encountered in the last year, while relying on a couple different packages, shares a lot of packages with our course toolchain, so worth checking out to see how the topics are approached from another angle. 
+
+### Complete Guide
+
+[Flow Cytometry Data Analysis & Visualization in R using CytoExploreR: Complete Guide](https://youtu.be/AvIvRorrh8c?si=MVViua5fSBrahtzv)
+
+<iframe width="560" height="315" src="https://www.youtube.com/embed/AvIvRorrh8c?si=QektorbguSVJ_lP-" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
+
+<br>
+
+### Flow Cytometry Data Analysis & Visualization in R using CytoExploreR
+
+[Flow-Cytometry-analysis-in-R](https://github.com/pritampanda15/Proteomics/tree/main/Flow-Cytometry-analysis-in-R-main)
+
+[CytoExploreR-Interactive-visualization](https://github.com/pritampanda15/Proteomics/tree/main/CytoExploreR-Interactive-visualization-main)
+
+---
+
 # Tulika Rai - Learn Innovatively With Me
 
+One of the more recent tutorial series I encountered in the last year, while a bit more focused on a particular application than the other video series, once you have some additional R context it is worth checking out. 
+
+>>>>>>> e277891a345df446c1e406e18bbff78126d26c90
 ### flowAI Flow Cytometry Data Cleaning using R
 
 [flowAI Flow Cytometry Data Cleaning using R: A Step-by-step Tutorial](https://youtu.be/PvB37SEe7lI?si=X3iYcGT7A3G603oP)
@@ -134,6 +212,7 @@ Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew
 
 ---
 
+<<<<<<< HEAD
 # Givanna Putri - Introduction to Cytometry Data Analysis in R workshop
 
 [ACS 2021 Workshops - Introduction to Cytometry Data Analysis in R workshop](https://youtu.be/-0QrXgk_NRw?si=GqcjU-_MQ3UvYwvI)
@@ -145,6 +224,14 @@ Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew
 ---
 
 # Timothy Keyes - 
+=======
+# Others
+
+The additional resources below are ones that I encountered while building this Existing Resources page, but have not had time to fully watch yet. 
+
+
+### Timothy Keyes - 
+>>>>>>> e277891a345df446c1e406e18bbff78126d26c90
 
 [{tidytof}: Predicting Patient Outcomes from Single-cell Data using Tidy Data Principles](https://youtu.be/5NhpC836aSc?si=QqoeW31cQcHFzu5W)
 
@@ -154,6 +241,7 @@ Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew
 
 ---
 
+<<<<<<< HEAD
 # Ryan Duggan - Cytometry on Air
 
 [Cytometry on Air: Analyzing Flow Cytometry Data in R](https://www.youtube.com/live/_B7mo6dB3BU?si=eW20X4YWgaCoYnfw) Presentation by TJ Chen and Greg Finak,
@@ -176,12 +264,21 @@ Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew
 # Hong Qin - flow analysis in R
 
 ### Flow Analysis in R
+=======
+### Hong Qin - flow analysis in R
+
+#### Flow Analysis in R
+>>>>>>> e277891a345df446c1e406e18bbff78126d26c90
 
 [flow analysis in R, bio125, Spring 2015](https://youtu.be/r7Mf6joCNzM?si=5j9Fy8fn6d7o0Z-u)
 
 <iframe width="560" height="315" src="https://www.youtube.com/embed/r7Mf6joCNzM?si=5j9Fy8fn6d7o0Z-u" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
 
+<<<<<<< HEAD
 ###  Flow Cytometer Data Analysis
+=======
+####  Flow Cytometer Data Analysis
+>>>>>>> e277891a345df446c1e406e18bbff78126d26c90
 
 [BIO233 demo, flow cytometer data analysis, simple example](https://youtu.be/BN5Ldu1AFgk?si=FV2K7jJGe9H6na08)
 
@@ -192,7 +289,11 @@ Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew
 
 ---
 
+<<<<<<< HEAD
 # Swayam Prabha - Flow cytometry data analysis in R/Bioconductor
+=======
+### Swayam Prabha - Flow cytometry data analysis in R/Bioconductor
+>>>>>>> e277891a345df446c1e406e18bbff78126d26c90
 
 [Lecture 15 : Flow cytometry data analysis in R/Bioconductor](https://youtu.be/g-VUT3riwOM?si=SlX88J3HpsjYaqFI)
 
@@ -202,6 +303,17 @@ Workshop given at the Bioc2023 conference, authored by Arpan Neupane and Andrew
 
 ---
 
+<<<<<<< HEAD
+=======
+### Guillaume Beyrend - Learn Cytometry
+
+[Learn Cytometry](https://learncytometry.com/videos/) Originally appeared to have been pay-walled, doesn't currently appear to be the case. Has a very different teaching approach from my own.
+
+<br>
+
+---
+
+>>>>>>> e277891a345df446c1e406e18bbff78126d26c90
 
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