stephenturner
commented
10 years ago I see no problem. Run the following code (the part at the beginning just recapitulates your data.
d <- structure(list(CHR = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), SNP = c("1:23187542",
"1:23217117", "1:23226619", "1:23280906", "1:23289961", "1:23327004",
"1:23342555", "1:23396183", "1:23402516", "1:23472663", "1:23541892",
"1:23555692", "1:23615921", "1:23641150", "1:23682442", "1:23711792",
"1:23812059", "1:23821149", "1:23886718", "1:23962323", "1:23974308"
), BP = c(23187542L, 23217117L, 23226619L, 23280906L, 23289961L,
23327004L, 23342555L, 23396183L, 23402516L, 23472663L, 23541892L,
23555692L, 23615921L, 23641150L, 23682442L, 23711792L, 23812059L,
23821149L, 23886718L, 23962323L, 23974308L), NMISS = c(56L, 56L,
56L, 56L, 56L, 56L, 55L, 56L, 56L, 56L, 56L, 56L, 56L, 54L, 56L,
56L, 55L, 56L, 56L, 56L, 55L), BETA = c(-0.00375, -0.0004373,
0.0001129, 0.003209, 0.004241, -0.001758, 0.003464, 0.002054,
0.01103, 0.008913, -0.003914, 0.01103, 0.003649, -0.004567, 0.0003377,
-9.768e-05, -0.002473, 0.004194, 0.001551, -0.001824, 0.01197
), SE = c(0.003287, 0.001809, 0.001978, 0.001849, 0.002476, 0.002224,
0.001687, 0.002069, 0.002603, 0.003017, 0.002447, 0.002603, 0.001715,
0.00162, 0.001867, 0.001778, 0.003811, 0.00295, 0.002557, 0.001807,
0.00292), R2 = c(0.02353, 0.001082, 6.03e-05, 0.05282, 0.05152,
0.01143, 0.0737, 0.01792, 0.2494, 0.1392, 0.04522, 0.2494, 0.0773,
0.1325, 0.0006053, 5.587e-05, 0.007882, 0.03608, 0.006767, 0.01851,
0.2407), T = c(-1.141, -0.2418, 0.05706, 1.735, 1.713, -0.7902,
2.054, 0.9927, 4.236, 2.954, -1.599, 4.236, 2.127, -2.818, 0.1809,
-0.05493, -0.6489, 1.422, 0.6065, -1.009, 4.099), P = c(0.259,
0.8098, 0.9547, 0.08837, 0.09251, 0.4328, 0.04497, 0.3253, 8.911e-05,
0.004632, 0.1156, 8.911e-05, 0.03801, 0.006815, 0.8572, 0.9564,
0.5192, 0.1609, 0.5467, 0.3173, 0.000143)), .Names = c("CHR",
"SNP", "BP", "NMISS", "BETA", "SE", "R2", "T", "P"), row.names = c(NA,
-21L), class = "data.frame")
d$SNP <- as.character(d$SNP)
mysnps <- c("1:23402516", "1:23555692")
library(qqman)
manhattan(d, highlight=mysnps)
If you're using the dev version you can limit the x-axis:
manhattan(d, highlight=mysnps, xlim=c(22187530, 24974320))
isp2
Hello,
I have gwas results from PLINK or in similar formats (with CHR, SNP, BP, and P columns). I've been using qqman to obtain qqplots and manhattan plots and I'm really pleased with this tool.
More recently I've decided to use qvalue R-package to determine the q-values corresponding to each p-value and add a "significant" column to the original gwas results table. Than I select all the SNPs that are significant at the level I chose as a cutoff (0.01 or 0.05 FDR) and generate a snps2highlight list using awk.
I've figured out that I need to make sure that the SNP column is read as a character and not a vector. And I'm using newtable <- rapply(originaltable, as.character, classes="factor", how="replace") to fix this.
However, every time I try to obtain a manhattan plot with the snps in the list highlighted I get the following error: Warning message: In manhattan(newplink3.qassoc, highlight = newsnps2highlight) : You're trying to highlight SNPs that don't exist in your results.
This is not true since I've made sure that the same SNP IDs are in both tables (gwas results and snps2highlight). Do you think this error as something to do with the factor to character transformation?
As an example here is a truncated list of snps to highlight: 1:23402516 1:23555692
And here is a small portion of the PLINK results table: CHR SNP BP NMISS BETA SE R2 T P 1 1:23187542 23187542 56 -0.00375 0.003287 0.02353 -1.141 0.259 1 1:23217117 23217117 56 -0.0004373 0.001809 0.001082 -0.2418 0.8098 1 1:23226619 23226619 56 0.0001129 0.001978 6.03e-05 0.05706 0.9547 1 1:23280906 23280906 56 0.003209 0.001849 0.05282 1.735 0.08837 1 1:23289961 23289961 56 0.004241 0.002476 0.05152 1.713 0.09251 1 1:23327004 23327004 56 -0.001758 0.002224 0.01143 -0.7902 0.4328 1 1:23342555 23342555 55 0.003464 0.001687 0.0737 2.054 0.04497 1 1:23396183 23396183 56 0.002054 0.002069 0.01792 0.9927 0.3253 1 1:23402516 23402516 56 0.01103 0.002603 0.2494 4.236 8.911e-05 1 1:23472663 23472663 56 0.008913 0.003017 0.1392 2.954 0.004632 1 1:23541892 23541892 56 -0.003914 0.002447 0.04522 -1.599 0.1156 1 1:23555692 23555692 56 0.01103 0.002603 0.2494 4.236 8.911e-05 1 1:23615921 23615921 56 0.003649 0.001715 0.0773 2.127 0.03801 1 1:23641150 23641150 54 -0.004567 0.00162 0.1325 -2.818 0.006815 1 1:23682442 23682442 56 0.0003377 0.001867 0.0006053 0.1809 0.8572 1 1:23711792 23711792 56 -9.768e-05 0.001778 5.587e-05 -0.05493 0.9564 1 1:23812059 23812059 55 -0.002473 0.003811 0.007882 -0.6489 0.5192 1 1:23821149 23821149 56 0.004194 0.00295 0.03608 1.422 0.1609 1 1:23886718 23886718 56 0.001551 0.002557 0.006767 0.6065 0.5467 1 1:23962323 23962323 56 -0.001824 0.001807 0.01851 -1.009 0.3173 1 1:23974308 23974308 55 0.01197 0.00292 0.2407 4.099 0.000143