# data

```
set.seed(123)
data22 <- data.frame (snp = 1: 20000*5 , chr = c(rep(1:5, each = 20000)),
pos= rep(1:20000, 5), pval1= rnorm(20000*5, 0.2, 0.3),
pval2 = rnorm(20000*5, 0.2, 0.3) )
# the above simulation produce negative values so the following will replace
# negative values with NA
data22$pval1[data22$pval1 < 0] <- NA
# removal of negative values
dat2 <- data22[!is.na(data22$pval1),]
```

```
```

`# install plantbreeding program from Rforge`

```
require(plantbreeding)
op <- par(mfrow=c(2,1), cex.axis = 0.75, font = 1, family = "serif")
par(op)
```

```
manhatton.plot(dataframe = dat2, SNPname = "snp", chromosome = "chr", position = "pos", pvcol = "pval1", line1 = 4, line2 = 8, ymax = "maximum", ymin = 0, gapbp = 2000)
```

```
title(main = "Mahattan plot of results for trait1", sub = "Method: Linear mixed model")
```

```
```

manhatton.plot(dataframe = dat2, SNPname = "snp", chromosome = "chr", position = "pos", pvcol = "pval2", line1 = 4, line2 = 8, ymax = "maximum", ymin = 0, color = c("gray50", "gray20"), pch = c(19, 1))

```
title(main = "Mahattan plot of results for trait2", sub = "Method: Linear mixed model")
```

data12 <- data.frame (snp = 1: 2000*20 , chr = c(rep(1:20, each = 2000)), pos= rep(1:2000, 20), pval= rnorm(2000*20, 0.001, 0.005))

# adding stripes (color filled rectangles) manhatton.plot(dataframe = data12, SNPname = "snp", chromosome = "chr", position = "pos", pvcol = "pval",ymax = "maximum", ymin = 0, gapbp = 500, color=c("hotpink3","dodgerblue4"), line1 = 3, line2 = 5, pch = c(1,20), stripe= TRUE, stripe.color = c("aliceblue", "cornsilk", "lightgoldenrod") )

# with annotation manhatton.plot(dataframe = data12, SNPname = "snp", chromosome = "chr", position = "pos", pvcol = "pval",ymax = "maximum", ymin = 0, gapbp = 500, color=c("hotpink3","dodgerblue4"), line1 = 3, line2 = 5, pch = c(1,20), annotate= TRUE, threshold= 6, thresholddir = "upper" )

# plot R2 or p-value

# Example 3, plotting simple p-value or R-square data13 <- data.frame (snp = 1: 2000*20 , chr = c(rep(1:20, each = 2000)), pos= rep(1:2000, 20), pval= rnorm(2000*20, 0.15, 0.05)) manhatton.plot(dataframe = data13, pconv= "NULL", ylabel = "R-square", SNPname = "snp", chromosome = "chr", position = "pos", pvcol = "pval",ymax = "maximum", ymin = 0, gapbp = 500, color=c("hotpink3","dodgerblue4"), line1 = 0.6, line2 = 0.2, pch = c(1,20) )

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