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stephenslab / susieR

R package for "sum of single effects" regression.
https://stephenslab.github.io/susieR
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PIP tends to 1 by increasing sample size. #218

Open harryyiheyang opened 4 months ago

harryyiheyang commented 4 months ago

Hi there, I found a very strange performance that the PIP would tends to either 1 or 0 by increasing the sample size when using the susie_suff_stat(). An example is shown below:

fit$pip [1] 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 [38] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [75] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 [112] 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 [149] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 [186] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Is this not type-I error or based on the variance of residual is 1?

Thank you

pcarbo commented 4 months ago

@harryyiheyang Without more information it is hard to say if this result is expected or not, but, generally speaking, we would expect greater confidence in identifying the causal SNPs as the sample size increases.