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jean997 / cause

R package for CAUSE
https://jean997.github.io/cause/
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How many SNPs is enough for est_cause_params? #22

Closed zichengwang98 closed 2 years ago

zichengwang98 commented 2 years ago

Hi,

I am conducting CAUSE analysis between a large number of traits(thousands of combinations), thus the speed of the analysis is very important. Generally, is the 1 million random sampled SNPs enough for the est_cause_params function? How many SNPs do I need to get relatively accurate estimates? I tried to include all SNPs(~ 5 million SNPs) and it is somewhat slow.

Zicheng

jean997 commented 2 years ago

Hi Zicheng, For parameter estimation, 1 million has worked well for us. That usually takes something like 2-8 minutes. For estimating posteriors, I usually use a threshold of p < 0.001 for the exposure. I think you will get a warning if you use something larger. Typically this is around 1-3k SNPs and doesn't usually take very long. Don't forget to prune for LD, that step is important.

A few days ago I made a small change that should speed up the posterior fitting step in some situations. You can try the latest version and see if that is faster.

Jean

msolerartigas commented 2 years ago

Hi Jean,

Is LD pruning required as well for the parameter estimation step (est_cause_params) or just for fitting the model (cause)?

Thanks! María

jean997 commented 2 years ago

LD pruning is only required for model fitting. We found it didn't make a difference for parameter estimation and you can lose accuracy due to having fewer SNPs.

On Thu, Dec 9, 2021 at 9:02 AM msolerartigas @.***> wrote:

Hi Jean,

Is LD pruning required as well for the parameter estimation step (est_cause_params) or just for fitting the model (cause)?

Thanks! María

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