Hi, I have a .vcf containing 1 million SNPs for a subset of a population (80 individuals) and what I would like to do is select SNPs that are informative for building pedigree and then redesign a probe set to target those SNPs for the rest of the population. 

I am not quite sure how to determine which SNPs out of the 1 mil are actually kinship informative. I do know parent-offspring and full/half sib relationships for this subset of individuals but will need to be able to build a pedigree out to 4th degree relatives for the entire population. Does anyone have any suggestions on a good approach for selecting these SNPs? Would it be something similar to how I would select ancestry informative (which I have already mined out of this SNP dataset)?

Thanks!
I'd suggest LD pruning/clumping to retain the unlinked SNPs (PLINK?), followed by identifying IBD (Identity-By-Descent) using PLINK. Pruning essentially finds representative SNPs in LD blocks to capture genotype information for the entire blocks and reduces the amount of variant data to analyze. 

https://privefl.github.io/bigsnpr/articles/pruning-vs-clumping.html

https://www.cog-genomics.org/plink/1.9/ld#indep

https://www.cog-genomics.org/plink2/ibd

This would result in relatedness (kinship) measures. See this:

https://www.biostars.org/p/58663/

But sometimes the relatedness measure could be a bit different from pedigree/parentage relationships you're after, as relatedness measures are also affected by population histories like genetic drift in small populations and/or bottlenecks. 

