YinLiLin / KAML

:bicyclist: Kinship Adjusted Multi-Loci Best Linear Unbiased Prediction

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Problem running binary trait

vunguyen1907 opened this issue · comments

Hi YiLiLin.

Sorry to bother you again.
I am tring to run binary (survival) trait code as 0, 1 and NA in KAML but can not finish the run. It run well with continuous trait. Please see the screenshot.

Do my phenotype data format is wrong?

kaml

I ran this:
iter1test1 <- KAML(pfile="pheno_iter1test1.txt", pheno=1, dcovfile="dcov_tracatfish.txt", qcovfile="qcov_tracatfish.txt", gfile="tracatfish", sample.num=20, crv.num=5)

Regards,

Vu

How is the proportion of case and control at this trait? As KAML uses cross-validation to optimize model parameters, if the distribution of case and control is too extreme, there maybe a risk that all the cases or controls would be allocated into trainings, therefore, all the validations only have one category, which would cause problem to compute prediction accuracy.

Hi YiLiLin
I had a similar problem when using example data.
Here is my code

KAML.Data(bfile="testdata", out="test") KAML.Impute("test") mykaml <- KAML(pfile="testdata.Pheno.txt", pheno=4, gfile="test")

And the error was:
image

Regards,

jimmy

@bigshrimp123 Thank for your feedback. Please try to change another seed by parameter 'theSeed', and also turn on the flag binary = TRUE

Thank for your suggestions. But, it can not solve the problem. Here is my code: mykaml <- KAML(pfile="testdata.Pheno.txt", pheno=4, gfile="test",theSeed=333,binary = TRUE)

and the error was also like this:
QQ截图20210616093051