You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I'm trying to compare the TCR repertoires from a bunch of samples, and the number of cells per sample vary from ~350 to ~4000. I tested powerTCR on these samples, and to my understanding this works, I understand that the distances between samples are not biased by the number of cells per sample. So, I can see that samples group the way I expected, but I also want to do a statistical test of a metric that represents something that people know what it is, such as Shannon Entropy. What I don't get is if that is sensitive to sequencing depth, or if that somehow is compensated for in your model? Could you give some advice on a suitable metric?
The text was updated successfully, but these errors were encountered:
Hi @hillarykoch,
I'm trying to compare the TCR repertoires from a bunch of samples, and the number of cells per sample vary from ~350 to ~4000. I tested powerTCR on these samples, and to my understanding this works, I understand that the distances between samples are not biased by the number of cells per sample. So, I can see that samples group the way I expected, but I also want to do a statistical test of a metric that represents something that people know what it is, such as Shannon Entropy. What I don't get is if that is sensitive to sequencing depth, or if that somehow is compensated for in your model? Could you give some advice on a suitable metric?
The text was updated successfully, but these errors were encountered: