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akdess / CaSpER

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CaSpER for bulk RNA-seq data #44

Open dreammxy opened 3 years ago

dreammxy commented 3 years ago

Dear akdess: I have some problems about bulk RNA-seq data.

  1. Is there a limitation with the sample size? how many samples does it work well at least?
  2. If I have more than one cohort from public database, should I run CaSpER separately, and then combined the result for further analysis? because the deviation of depth in different projects is always high. Thank you very much!
akdess commented 3 years ago

Hi @dreammxy, I am very sorry for the late reply. Thanks a lot for your interest!

Those are great questions. I was able to run it in as little as n=3 samples. If the expression signal is not noisy and good quality you should be able to get good results with low sample size.

About the second question, my first guess would running it on combined results, but seperate should also be fine. I would appreciate your feedback on this if you have already tried both. I would love to hear your comments.

Please let me know if you have further questions. Best, Akdes

dreammxy commented 3 years ago

Dear akdess：I am very glad to receive your email. About the first question,I have tried the data of yale meningioma, I also get the expression all above 0. I guess there is some problem of the R package? And as you mentioned that you run it used 3 samples, do you think it's not applicable to large samples? I have tried combine and separate data, and it showed some differences. But I am not sure it is due to the first question. Thanks a lot!Best wishes!Xinyi发自我的iPhone------------------ Original ------------------From: Akdes Serin Harmanci notifications@github.comDate: Thu,Feb 25,2021 4:26 AMTo: akdess/CaSpER CaSpER@noreply.github.comCc: dreammxy mengxy@tmu.edu.cn, Mention mention@noreply.github.comSubject: Re: [akdess/CaSpER] CaSpER for bulk RNA-seq data (#44) Hi @dreammxy, I am very sorry for the late reply. Thanks a lot for your interest! Those are great questions. I was able to run it in as little as n=3 samples. If the expression signal is not noisy and good quality you should be able to get good results with low sample size. About the second question, my first guess would running it on combined results, but seperate should also be fine. I would appreciate your feedback on this if you have already tried both. I would love to hear your comments. Please let me know if you have further questions. Best, Akdes

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