**1.4k**wrote:

I was trying to calculate the IBD values for about 100 individuals all likely to be unrelated. I tried to use plink tool ( http://pngu.mgh.harvard.edu/~purcell/plink/ibdibs.shtml ), but looks like it generates to many false positives (or high IBDs for unrelated individuals). I have one sample with at least 5 other samples with IBD =1 (I am looking at Z0 values). Can someone please explain me what these values mentioned in their website are:

```
Z0 P(IBD=0)
Z1 P(IBD=1)
Z2 P(IBD=2)
PI_HAT Proportion IBD, i.e. P(IBD=2) + 0.5*P(IBD=1)
```

It's possible that your unrelated individuals are actually related, or sample swaps?

9.1kIt's also known that PLINK's IBS calculations aren't that great. The kcoeff paper has some comparisons.

9.1kHave you carefully QC'ed your genotypes like what you would do for GWAS analysis? Poor quality genotypes would give you wrong calculations, but it's not the fault of IBD.

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