Hello all,
the title really says it all.
I am analysing T-cells in the context of immune dysregulation and I have developed 5 panels, each with around 10 colors (some, but not all (obviously) shared across panels).
I am struggling to see how I could use some of the tools that help deal with high-dimensional data to analyse my work. PhenoGraph, FlowSOM, viSNE and all those tools are helpful if you have all the "colours" in one panel, such as in mass-cytometry, but less so when they are spread out between different tubes.
What would you recommend?
Thanks for any ideas!
Adam
Hi Adam, as long as you measured your panels separately, you will most likely only be able to also analyze them separately. If I remember correctly, the company Infinicyte (http://www.infinicyt.com/overview/features) at some point tried to develop an approach that would allow to map cells across different panels, but I have never looked into this in great detail.
Having said that, you can still use clustering algorithms, or automated gating pipelines for efficient and unbiased analysis. We wrote a review on that topic two years ago: Article The end of gating? An introduction to automated analysis of ...
and also the group from Yvan Says made an excellent review article: https://www.nature.com/articles/nri.2016.56Depending on the instrument you are using, I would alternatively suggest to combine your panels so that you can instead of 5 with 10 parameters, you are having 3 with 16/17 each.
Good luck with your experiments!
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