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Given all the genome variation information we have accumulated from resequencing human genomes up until now (early 2018), how much variation is left that hasn't been sequenced?

EDIT: given one of the answers, and the fact that 99% of the SNPs at 1% or more are found, is there a quantitative measure of remaining variation?

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  • $\begingroup$ I don't think this is answerable. Do you mean single nucleotide variants? Copy number changes? In healthy individuals only? Only living individuals? All possible variants? Pretty much anything is possible. . . $\endgroup$
    – terdon
    Jan 21 '18 at 23:37
  • $\begingroup$ Please clarify "variation". If you limit this to single nucleotide polymorphisms only and to variants above a certain frequency threshold, as the answer you have received has done, then it might indeed be answerable. $\endgroup$
    – terdon
    Jan 22 '18 at 9:02
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In theory, almost any base in the human genome may mutate, so you have billions of variants to go. Ok, this is not so useful.

A related and potentially useful question is: given a human, what is the fraction of his/her variants seen in the the previously sequenced samples? For a Wright-Fisher population, there is an analytical answer: x% of variants on a haplotype has frequency below x%. Replace "x" with "1": 1% of variants on a haplotype have frequency below 1%. The 1000 genomes project concluded that 99% of SNPs at frequency 1% or higher have been called by the project. If we all came from a Wright-Fisher population, 99% of of SNPs have been called in 1000g. Given that the project also calls SNPs at lower frequency, nearly all SNPs in a newly sequenced sample are present in 1000g.

The above is a theoretical analysis. In practice, there are two major complications. First, we are not a Wright-Fisher population. Due to recent population expansion, each haplotype harbors more new mutations than the Wright-Fisher model would predict. Given a known population history, it is actually possible to numerically compute $f(x)$, the fraction of variants with frequency below x (for Wright-Fisher, $f(x)=x$). I don't have this result, though. Second, 1000g and many other genome projects didn't call SNPs in repetitive regions and missed a significant portion of high-frequency indels and structural variations. With Illumina, you can only call ~30% of long deletions callable with PacBio data, but we only have a dozen of PacBio human genomes in public. There are still a lot we don't know.

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