Useful links
Here we provide some additional links
A practical workflow for spectral flow cytometry data analysis with R
We found inspiration for this course in this publication
den Braanker et al, 2021, Frontiers in Immunology
The workflow presented in day 5 was inspired by Melsen et al, 2020
Another R workflow proposed for data analysis of CyTOF data
Comparative analysis of dimension reduction methods for cytometry by time-of-flight data
From the abstract:
” Here, we benchmark the performances of 21 DR methods on 110 real and 425 synthetic CyTOF samples. We find that less well-known methods like SAUCIE, SQuaD-MDS, and scvis are the overall best performers. In particular, SAUCIE and scvis are well balanced, SQuaD-MDS excels at structure preservation, whereas UMAP has great downstream analysis performance. We also find that t-SNE (along with SQuad-MDS/t-SNE Hybrid) possesses the best local structure preservation. Nevertheless, there is a high level of complementarity between these tools, so the choice of method should depend on the underlying data structure and the analytical needs. “
Orchestrating single-cell analysis with Bioconductor
Code mostly developed for single-cell RNA seq analysis, but some of the concepts explained apply to flow cytometry data analysis also, such as the singleCellExperiment object described in Chapter 4.
Understanding UMAP
A website where you can play with the parameters and see how the 2D projection of an original data set changes
https://pair-code.github.io/understanding-umap/
Understanding tSNE
A website where you can play with the parameters and see how the 2D projection of an original data set changes
https://distill.pub/2016/misread-tsne/
R for Data Science Book
Book (2nd edition) by Hadley Wickham (a very active R developer), Mine Çetinkaya-Rundel and Garrett Grolemund. The book makes heavy use of the tidyverse, which is a collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures. ggplot2 is part of the tidyverse packages.
ggplot2 tutorial
https://ggplot2.tidyverse.org/
R-charts
A site that has been created to be a reference for learning how to create charts in R as well as a place to look for inspiration. Code examples to create plots with base R, ggplot2. Color charts with R color name vs HEX equivalent.
R Markdown
A useful resource is RStudio’s R Markdown tutorial.
For tweaking your reports, such as chosing different output formats, or hiding or showing the code within the report, we recommend that you consult the R markdown documentation provided in this Definite guide eBook.
Go further with the R Markdown Cookbook.
Cheatsheets
Several cheatsheets available for different packages, eg R Markdown, ggplot2, RStudio,…