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Q-Q plots with GWAS p-values using R (needs confidence band)

I'm trying to create Q-Q plots with GWAS p-values using R but it hasn't really been working out. I need for them to be on a -log10 scale, and for them to have a confidence band/interval.

I tried out:

  • qqman - works great and it's simple but it does not provide a confidence interval function> code: qq(*P-values*)
  • snpStats - has the confidence interval but the X and Y axis are chi-squared values. I'm not sure if there's a way to get -log10 P-values? The plots look great though. code: qq.chisq(-2 * log(*P-values*), df = 2, pvals= TRUE, conc=c(0.05, 0.95))​
  • car - the plot looks a little....odd. Maybe I'm just using it wrong but I don't like the distribution of the dots. Why does the X-axis start at -4 instead of 0? code: qqPlot(-log10(*P-values*), envelope=0.95)

I'm hoping the colorful examples would help me get a detailed answer lol

r q-q plots gwas
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updated by Kevin Blighe Kevin Blighe • written by joshf • joshf

1 answer

Old thread but some tips for others arriving here:

There is indeed something wrong with your distribution. Possible problems:

  • your dataset is unbalanced
  • your dataset is under-powered
  • the statistical test that you employed is not suited to the data distribution that you have
  • any combination of the above

Kevin

PS - the bottom plot has X-axis starting at -4 because it is plotting quantiles.

• 1 views • link
written by Kevin Blighe Kevin Blighe

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