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Manhattan plot

Source: vignettes/articles/tracks_manhattan.Rmd
tracks_manhattan.Rmd
library(ezGenomeTracks)
#> Warning: replacing previous import 'AnnotationDbi::select' by 'dplyr::select'
#> when loading 'ezGenomeTracks'
#> ezGenomeTracks v0.0.1
#> Easy and flexible genomic track visualization
#> Use citation('ezGenomeTracks') to see how to cite this package
#> For documentation and examples, visit: https://github.com/zmu/ezGenomeTracks

ezGenomeTracks allows for two type of Manhattan plots. First, a genome-wide Manhattan when more than one chromosome is involved. This is very typical for GWAS results. Second, a region-level Manhattan plot, which is more similar to a LocusZoom plot.

Genome-wide Manhattan plot

We use the example GWAS data from qqman package to demonstrate genome-wide Manhattan.

library(qqman)
#> 
#> For example usage please run: vignette('qqman')
#> 
#> Citation appreciated but not required:
#> Turner, (2018). qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots. Journal of Open Source Software, 3(25), 731, https://doi.org/10.21105/joss.00731.
#> 
head(gwasResults)
#>   SNP CHR BP         P
#> 1 rs1   1  1 0.9148060
#> 2 rs2   1  2 0.9370754
#> 3 rs3   1  3 0.2861395
#> 4 rs4   1  4 0.8304476
#> 5 rs5   1  5 0.6417455
#> 6 rs6   1  6 0.5190959
ez_manhattan(
  input = gwasResults,
  chr = "CHR",
  bp = "BP",
  p = "P",
  color_by = "CHR",
  colors = c("grey", "skyblue")
)

Region-level Manhattan plot

You can use r2 option to color the dots with LD information.

region <- "chr3:200-500"
locusResults <- gwasResults |> 
  dplyr::filter(CHR == 3 & BP > 200 & BP < 500)

ez_manhattan(
  input = locusResults,
  region = region,
  snp = "SNP",
  lead_snp = "rs3057",
  r2 = -log10(locusResults$P) / max(-log10(locusResults$P)),
  size = 1
)