Entering edit mode
8 weeks ago
chi.delta ▴ 40
I am trying to cluster single cells using the ADT reads from the CITEseq (generated with the 10x platform). Ideally, I would like to use the information from two ADT features. I have tried the kmeans function on a count matrix of the two antibodies in order to make 3 clusters (number pre-defined) but this doesn't seem to work. Is there any way to do that? Any suggestion would be appreciated. Thanks a lot!
Think about it, how would any clustering with only two genes/features be informative? Is this really what you need? If you break it down, for two features the combinations can basically be low-low, low-high, high-low and high-high, given that these combinations really exist in the data. Also, what does "not work" mean?
Let's say that based on known FACS data, I already know that three populations exist based on the two antibodies staining: single positive for each and double positive. However, I do not want to arbitrarily just set a threshold of what is considered positive and negative in the cite-seq reads of the two antibodies, and also because after normalization, the bimodality of the staining is lost, I am looking for a reliable way to define the populations above in my cite seq data.
If it is really just two genes then why not just plotting logcounts of gene1 vs logcounts of gene2 as in a FACS scatter plot and see whether there is any sort of separation. While automated methods may or may not work you could simply define a few gates by hand or at least decide if there is any separation at all.