1 current sample ID:1 Error in FUN(X[[i]], ...) : argument "seed" is missing, with no default

[vincent1715]

Hello
I have some problem when running function "learn.embedding.Kcls()" as follows:

tcga.ebd.res.k4 <- learn.embedding.Kcls (ted.res = tcga.ted,

•                                      K.vec = 4,
  

•                                      EM.maxit=50,
  

•                                      n.cores =1)
  

current.K= 4
[1] "starting EM cycles #..."
1 current sample ID:1 Error in FUN(X[[i]], ...) : argument "seed" is missing, with no default

I set the argument "n.cores =1" as i am running this on windows which Tom suggested before, the inputs is the example data you provide. can you give me some suggestion? thanks .

Regards,

vincent

[tinyi]

Hi Vincent, I have now fixed this issue - something I forgot to do after adding the random seed that addresses Tom's request. In our BayesPrism paper, we provided phi.tum and K by first running NMF on inferred tumor expression. This might provide a more sensible way to choose K and initialize phi.tum. I have now updated our vignette to include this. Feel free to let me know if you have any questions. Best, Tinyi

…

On Fri, Apr 15, 2022 at 6:07 AM vincent1715 ***@***.***> wrote: Hello I have some problem when running function "learn.embedding.Kcls()" as follows: tcga.ebd.res.k4 <- learn.embedding.Kcls (ted.res = tcga.ted, - K.vec = 4, - EM.maxit=50, - n.cores =1) current.K= 4 [1] "starting EM cycles #..." 1 current sample ID:1 Error in FUN(X[[i]], ...) : argument "seed" is missing, with no default I set the argument "n.cores =1" as i am running this on windows which Tom suggested before, the inputs is the example data you provide. can you give me some suggestion? thanks . Regards, vincent — Reply to this email directly, view it on GitHub <#18>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB4NHSYNUDZB4ZE366ZZCDDVFE5VFANCNFSM5TQDFA2Q> . You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>

[vincent1715]

Hi Tinyi,
very appreicate for your advice and corresponding help, and sorry for replying so late as i was testing the code you provide, and its really need so long time to test.
The modification you've made is feasible to solve my problem,but i would continually do more test with other data, and i might ask for more help if any other problem happen.
thanks for your timely help.

Best,

Vincent