=c( "red ", "blue ", "green "), threshold = 0.05 /nrow( pig60K), threshold.lty = 2,Īmplify = FALSE, file = "jpg ", memo = " ", dpi = 300, file.output = TRUE, verbose = TRUE, width = 14, height = 6) l =c( "red ", "blue ", "green "), highlight.cex = 1, highlight.pch =c( 15 : 17), highlight.text = genes, > CMplot( pig60K, plot.type = "m ", LOG10 = TRUE, col =c( "gre圓0 ", "grey60 "), highlight = SNPs, rMVP: A Memory-efficient, Visualization-enhanced, and Parallel-accelerated tool for Genome-Wide Association Study, Genomics, Proteomics & Bioinformatics (2021), doi: 10.1016/j.gpb.2020.10.007. Total 50~ parameters are available in CMplot, typing ?CMplot can get the detail function of all parameters.ĬMplot has been integrated into our developed GWAS package rMVP, please cite the following paper: Now CMplot could handle not only Genome-wide association study results, but also SNP effects, Fst, tajima's D and so on.
Note: if plotting SNP_Density, only the first three columns are needed. data( pig60K) #calculated p-values by MLM > data( cattle50K) #calculated SNP effects by rrblup > head( pig60K)