A small list of useful cytometry resources
Generalized links (not private) have been converted as far down as the Docker tag.
Spectral Flow Cytometry
200416 Gardner Full Spectrum Cytometry - More introductory overall.
OpenFlow: Full Spectrum Flow Cytometry with the Cytek Aurora Crick/MSK walkthrough of the unmixing process
Full Spectrum Profiling │ Adam Davison │ Babraham Institute Spectral Symposium 2022
ChUG Cytometry Presents: Introduction to Spectral Unmixing - David Novo talks about unmixing paper
ChUG Podcast #15: Spectral Flow - What You Don’t Know Is Out To Kill You
Panel Design
Full spectrum panel optimisation │ Laura Ferrer Font │ Babraham Institute Spectral Symposium 2022
Just Because You Don’t See It Doesn’t Mean It Isn’t There: Improved Assay Resolution with…
Alexis Gonzales talks autofluorescence
Staining
Overnight staining of flow cytometry samples │ Oliver Burton
Spectral Unmixing
Mathematics of spectral unmixing │Peter Mage │ Babraham Institute Spectral Symposium 2022
Unmixing on traditional instruments │ Christopher Hall │ Babraham Institute Spectral Symposium 2022
Spectral Unmixing - (Short video)
Autofluorescence
Advanced Tips for Organizing Unstained controls within SpectroFlo (Cytek Aurora)
ChUG #8 - Dealing with autofluorescence in spectral flow cytometry
Deciding on an Approach for Mitigating Autofluorescence
ChUG #8 - Dealing with autofluorescence in spectral flow cytometry
Heterogeneous Autofluorescence
Episode #23 - How does cell size affect autofluorescence?
The Power of Autofluorescence Extraction Using Full Spectrum Profiling™
Analysis
2021 Flow Cytometry Data Analysis
Enabling and Optimizing High Quality Spectral Cytometry Analysis
Tutorial on tSNE and FlowSOM Step-by-Step tool usage in FlowJo V10
Flow Cytometry General
Flow Basics 2.1: The Basic Staining Protocol
Flow cytometry staining buffers
Flow Cytometry & FACS | Beginner Data Interpretation Tutorial
OpenFlow: Experimental Voltage Optimization in Diva
Flow Cytometry Basics: How To Use Gates (floreada.io)
Laura Johnston How to decide which software and tool is best for calculating compensation (with bonus FlowJo tips)
Cytometry in R
Introduction to Flow Cytometry in R
Cytometry on Air: Analyzing Flow Cytometry Data using R
flow cytometer data analysis in RStudio
Flow Cytometry Data Analysis in R- Installation and loading data
FlowJo FCS Express
How to use Plugins in FlowJo v10 Webinar
High-dimensional Analysis
2022 MetroFlow Annual Meeting Sofie Van Gassen
Normalization Advanced Webinar with Jack Panopoulos April 2022
Webinar: Using CytoNorm with FlowJo
20220517 Crossentropy test talk
Using Tercen To Run Bioconductor Pipelines: Save Time And Share Data Easy With Collaborators
Integration, exploration, and analysis of high-dimensional single cell cytometry data using Spectre
Dimensionality Visualization
PaCMAP: An algorithm for dimension reduction
Neighbour embeddings for scientific visualization | Dmitry Kobak
Introduction to dimensionality reduction | Statistics for proteomics
Machine Learning General
Machine Intelligence - Lecture 1 (methods, history, definitions, Turing Test)
Machine Intelligence - Lecture 7 (Clustering, k-means, SOM)
General Data Science Intro
Hunter Glanz | The Five Principles of Data Science Education | RStudio (2020)
Linear Modeling
Linear Models
Canada series, simple linear model, 2 continous variables. Introduction to R 2023 | 04: Linear Models
Generalized Linear Models
Chloe’s Intro GLM. How to interpret (and assess!) a GLM in R
Annoying voice-over guy but still. Big view, ehh Understanding Generalized Linear Models (Logistic, Poisson, etc.)
Canadas very basic may not be worth it. Analysis Using R 2023 | 03: Linear Mixed Models and Evaluation
Annoying voice-over guy, interaction two predictors. GLM Part 6: Interaction effects: How to interpret and identify them
Mixed Models
Annoying voice-over guy, but decent. Mixed Models, Hierarchical Linear Models, and Multilevel Models: A simple explanation
Decent explanation of what your numbers mean Linear mixed effects models - the basics
Annoying Voice Guy How to decide whether an effect is fixed or random in mixed models
Lecture 9.1 Introduction to Mixed Effects Models
Keith Legit Mixed Factorial Mixed Effect Regression for Factorial Designs
Longitudinal Mixed
Keith Legit Mixed effect Longitudinal Mixed Effects Models for Longitudinal Data
Longitudinal Multilevel Modeling in R Studio (PART 1)
Introduction to Bayesian Multilevel models
Paul Bürkner: An introduction to Bayesian multilevel modeling with brms
Differential Analysis
Over an hour long MIT video. 21. Generalized Linear Models
Lior Pachter Day 5 - Introductory Lecture: Single Cell Hypothesis Testing
This one!!!! Differential Abundance Analysis in Proteomics
And this one! Linear Models for Differential Abundance Analysis
Statistical significance of differential protein abundance | Statistics for proteomics
Differential Expression for RNA-Seq Part 1: Using the limma Bioconductor package
Differential abundance and correlation analysis of microbiome data: Challenges and some solutions
Contrast and Design Matrices
It’s in EXCEL, why?!?!?! Visualize Dummy Variables for Regression Statistics 101: Model Building, GLM Relationships Between ANOVA and Linear Regression
Design Matrices For Linear Models, Clearly Explained!!!
Day 6: Contrasts in linear models
Statistical Contrasts for Addressing Specific Scientific Hypotheses
This one!!! Introduction to this channel and what I hope to achieve here
Rat Study Part II: Orthogonality and Planned Comparisons - by hand
EPY 8214: A Priori and Post Hoc Comparisons
Lab 8 Contrasts for Two Way MANOVA
Docker
Learn Docker in 7 Easy Steps - Full Beginner’s Tutorial
Part 1 - An Introduction to Docker for Windows
GitHub
Git and GitHub Tutorial for Beginners
Best git/GitHub practices when adapting code
First Steps in Learning the Use of Git & GitHub in RStudio
Quarto
Introducing R Markdown Notebooks
R Markdown Advanced Tips to Become a Better Data Scientist & RStudio Connect | With Tom Mock
Dr. Thomas Mock - Higher, Further, Faster with Marvelous RMarkdown
Beautiful reports and presentations with Quarto | Led by Tom Mock, RStudio
R-Ladies Freiburg (English) - Getting to know Quarto
Blogging with Quarto: a 10 minute getting started tutorial
Building a Blog with Quarto | Led by Isabella Velásquez, RStudio
Create beautiful documents with Quarto and R
Get started with Quarto | Mine Çetinkaya-Rundel
Daniel Chen - Moving to Quarto from RMarkdown and Python Jupyter Notebooks
Automated analysis, reporting and presentations using R and LaTex
Styling and Templating Quarto Documents - posit::conf(2023)
Reproducible Manuscripts with Quarto - posit::conf(2023)
Parameterized Quarto Reports Improve Understanding of Soil Health - posit::conf(2023)
Parameterized Reporting with Quarto, R by Jadey Ryan
Using Quarto for revealjs slides
Using Quarto with R and Python for reports, slides, and web publishing
R for Begginers
Tutorial on 80% of everything you will EVER need to know in R (for ecology) [IN ONE HOUR]!
HTML in R
HTML and CSS for R Users with Albert Rapp
Carson Sievert || Using tagQuery() from {htmltools} to modify HTML snippets in R || RStudio
Quickly get your Quarto HTML theme in order - posit::conf(2023)
Parallelization in R
Henrik Bengtsson | Future: Simple Async, Parallel & Distributed Processing in R | RStudio (2020)
How to run your R code in parallel with the furrr package (CC127)
Bryan Lewis | Parallel computing with R using foreach, future, and other packages | RStudio (2020)
Speeding up computations in R with parallel programming in the cloud
Cloud Computing
00 1 intro - aws-for-bioinformatics
AWS In 10 Minutes | AWS Tutorial For Beginners | AWS Training Video | AWS Tutorial | Simplilearn
Cytoverse
Workshop: Reproducible and programmatic analysis of flow cytometry experiments with the cytoverse
Tidyverse in R
Join data frames in R with inner_join and anti_join (CC254)
Stats in R
Chapter 1, Part 1: Introduction
Creating and tidying linear models in R with “broom” | R Tutorial (2020)
Hadley Wickham: Managing many models with R
Longitudinal Time Series Data
Introduction to Longitudinal Data Analysis
The Bayesians are Coming to Time Series
ACRM 2022 IC17: Longitudinal Data Analysis Using R: Part I Introductory Topics
GAMs and Spline
Generalized Additive Models: Allowing for some wiggle room in your models
Statistical Methods Series: Generalized Additive Models (GAMs)
Noam Ross - Nonlinear Models in R: The Wonderful World of mgcv
Polynomial Regression and Splines
Introduction to Generalized Additive Models with R and mgcv
Dataframes and Tibbles
What’s the difference between a matrix, data frame, and tibble in R? (CC180)
Using nest, mutate, map, and unnest in R to analyze data frames within data frames (CC056)
R List Columns: purrr map and nesting (STAT 545 Episode 2-B)
Tidy Data
Stat 412 6: Advanced Data Wrangling with dplyr
R-Ladies Freiburg (English) - Tidy data: Wrangling for statistical analysis in R - Kyla McConnell
George Mount | R for Excel Users - First Steps | RStudio Meetup
Tidy Data and tidyr – Pt 2 Intro to Data Wrangling with R and the Tidyverse
R-Ladies Freiburg (English) - Tidy data: Wrangling for statistical analysis in R - Kyla McConnell
Shiny and Dashboards
Tutorial: Create and Customize a Simple R Shiny Dashboard
eCharts4r - Your New Favourite R Package for Interactive Visualization
TidyTuesday: Flexdashboard vs Shinydashboard
Animated Data Visualizations with {gganimate} for Science Communication during the Pandemic
ggplot2 in R
Level Up Your Plots with Cara Thompson
June Choe | Cracking open ggplot internals with {ggtrace} | RStudio (2022)
Oikos Workshop: Data visualization in R using ggplot2
Stylish Scatter Plot using ggplot2 in R
Lines, scales and labels | Data on display: visualizing data with ggplot2 in R (lesson 3)
Data visualization with R in 36 minutes
Adding lines and asterisks of statistical significance on a figure with ggplot2 (CC093)
patchwork: The ggplot2 plot combiner
GGPLOT2: Publication Quality Figures
How to Export High Quality Image from R
Creating a stacked barchart in R with ggplot2 (CC102)
Scatterplots in R with geom_point() and geom_text/label()
Improving the appearance of a stacked barchart with ggplot2, dplyr, and forcats (CC103)
How to create a relative abundance barplot with ggplot2
How to make Stacked Bar Chart in R | RStudio
Use these five easy steps on every chart
Master Boxplot Visualization in R with ggplot and ggpubr | Your Ultimate Guide to the ggplot Package
Plotting interactive visualizations with Plotly in R
R-Ladies Rome (English) - Ten tips for better text: typography meets ggplot and friends
Summer Workshop Series: Crafting Publication Quality Data Visualizations With ggplot2
Summer Workshop Series: Exploring the Wide World of ggplot2 Extensions
How to create a heatmap in R with geom_tile and geom_text from ggplot2 (CC105)
Tables in R
Making high-quality tables in R with the gt package: a conversation with Tom Mock
Publication-ready tables using gtsummary + Rmarkdown - Part 2: creating Table 1
Creating Publication-Ready Summary Tables with {gtsummary}
R package reviews {gtsummary} Publication-Ready Tables of Data, Statistical Tests and Models!
Presentation-ready Summary Tables with {gtsummary}
Iteration in R
Iteration Without Loops in R: The apply Family
How to Use lapply, sapply and mapply in R
Functional Programming
Hadley Wickham | {purrr} 1.0: A complete and consistent set of tools for functions and vectors
Write R functions like a pro in 6 minutes
Using the purrr and broom R packages to easily perform thousands of statistical tests (CC112)
Functional Programming using the Purrr Package webinar
R advanced functions that will make your life easier
A tutorial for writing functions in R (CC177)
“The Joy of Functional Programming (for Data Science)” with Hadley Wickham
R-Ladies Rabat (English) - Iterating well with purrr! - Shannon Pileggi, PhD
TidyTuesday: A Brief Overview of Functional Programming with Purrr
R Ladies Baltimore | Make your R code purr with purrr
Intro to Functional Programming with R
Intro to R Programming - Writing Functions
Ch 7, Video 11: More on nesting and mapping
R and Python
Sean Lopp & Lou Bajuk | R & Python: A Data Science Love Story | RStudio (2020)
Combining R & Python with reticulate
R-Ladies Baltimore | Reticulate RStudio and your R code with Python | Timbers
ds.rpy: Running Python code from RStudio
R with C++/Rust
Jared P. Lander - Taking R From Hours to Seconds
Claus Wilke - The extendr project: Integrating R and Rust
A Data Scientist’s Guide to the Rust Programming Language | Sussex Data Science
Make your R code 18,878 times faster! (Abridged) | R Programming
YEGRUG 2023/11: R and Rust, like a match made in heaven with Andrés Felipe Quintero
Extending R with C++: Motivation, Introduction and Examples - Part 1
Jim Hester - cpp11 - welding R and C++ - SatRday Columbus 2020
Epidemiology Lingo
Benedicte Colnet: Risk ratio, odds ratio, risk difference… Which measure is easier to generalize?
Niels Richard Hansen: Cyclic graphical models and causal learning
Epidemiology for Bioinformaticians
Github Actions
R-Ladies Cologne & Paris (English) - GitHub Actions and Quarto - Angelica Becerra
How to Use GitHub Actions with R to Run Code Automatically
GitHub Actions Tutorial | From Zero to Hero in 90 minutes (Environments, Secrets, Runners, etc)
Running code while we’re sleeping: Introduction to GitHub Actions for R Users by Beatriz Milz
rworkflows: taming the Wild West of R packages
Getting into the flow with rworkflows: an introductory tutorial
Statistical Soapbox
How to get your article rejected by the BMJ: 12 common statistical issues
Andrew Gelman and P-value critique
Keynote 2: Weakly Informative Priors – Andrew Gelman
Prof. Andrew Gelman: the Most Important Statistical Ideas in the Past 50 Years
Andrew Gelman - Solve All Your Statistics Problems Using P-Values
Causal Inferance
Sander Greenland at Judea Pearl Symposium
Introduction To Causal Inference And Directed Acyclic Graphs
Power in Statistics
Distribution and Probabilities
Computing normal probabilities: examples
Lecture 1: Probability and Counting | Statistics 110
All About that Bayes: Probability, Statistics, and the Quest to Quantify Uncertainty
Topology Manifolds AI
Geometry & Topology in Machine Learning
Stan
#6 A principled Bayesian workflow, with Michael Betancourt
Bayesian Modeling with R and Stan (Reupload)
Why R? Webinar 035 - Paul Buerkner - brms: Bayesian Regression Models using Stan
Some Bayesian Modeling Techniques in Stan
Introduction to Bayesian Statistics - A Beginner’s Guide
R-Ladies Amsterdam: Intro to Bayesian Statistics in R by Angelika Stefan
BDA course 1.1 Introduction to uncertainty and modelling
Stan and probabilistic programming introduction
How to write your first Stan program
Getting started with Stan in R
Linear regression made easy with Stan
Linear Algebra
The Big Picture of Linear Algebra
Least Squares Approximation | MIT 18.06SC Linear Algebra, Fall 2011
Linear Algebra Video #48: Overdetermined Systems & Least Squares
Introduction to Linear Algebra and Statistics for Data Science
Eigenvectors and eigenvalues | Chapter 14, Essence of linear algebra
Gil Strang’s Final 18.06 Linear Algebra Lecture
Geometry of Linear Algebra | MIT 18.06SC Linear Algebra, Fall 2011
1. The Geometry of Linear Equations
21. Eigenvalues and Eigenvectors
Lecture 1: The Column Space of A Contains All Vectors Ax
Open Source Licenses
Open Source Software Licensing Basics for Corporate Users
Felix Crux What You Need to Know About Open Source Licenses PyCon 2016
CppCon 2015: Kevin P. Fleming “A Crash Course in Open Source Licensing”
How to Choose an Open Source License | HackBeanpot 2018
Software and Research
Bob Carpenter - 0 to 100K in 10 years: nurturing an open-source software community (June 10, 2022)
Science as Amateur Software Development (2023 edition)
The Problem with Research Software Engineering
Scientific Software Design 101
How do we measure success for Open Data in academia? | Lauren Cadwallader | SOOCon23 Open Data
Nicholas Tierney - Recognising research software in academia
Creating R Packages
Field Guide to Writing Your First R Package - posit::conf(2023)
How to Make a Custom R Package
Building R packages with devtools and usethis | RStudio
OOP in R
Mastering the S3 Object System: Advanced R for everyone
Reproducibility in Open Science
Irina Gaynanova | Replicability, Reproducibility, Reviewing, and Optimism for the Future of Science
Garrett Grolemund | R Markdown The bigger picture | RStudio (2019)
Robustness and Transparency in Scientific Methods, Statistics, study design by Daniel Lakens
Statistical Rethinking
Scientific Soapboxes
Science Before Statistics: Causal Inference
What makes a great math explanation? | SoME2 results