For this tutorial series, we will be using the genlight object that we created in the previous tutorial. Original data in HapMap format used in TASSEL was converted to genlight object.

Install package

devtools::install_github("dpaudel/dpaudelR")

Load required package

library(LDcorSV)
library(adegenet)
library(ggplot2)
library(scales)
library(tidyverse)
library(dpaudelR)

Download data

For this tutorial, we will be using hapmap data that comes with TASSEL. The data can be downloaded from this link:

https://raw.githubusercontent.com/dpaudel/TASSELtutorial/master/data/mdp_genotype_subset.hmp.txt

Save the data in your computer.

Import data

mygeno=hapMap2genlight2(file.choose()) # Choose the hapmap file that you just downloaded

Get the genlight object for DAPC

mygeno1 <- mygeno[[1]]

Remove NA

toRemove <- is.na(glMean(x, alleleAsUnit = FALSE)) # TRUE where NA when Error in glPca(flu) : NAs detected in the vector of means
which(toRemove) # position of entirely non-typed loci
b <- x[, !toRemove]

Plot the eigen values

glPca(b) 
# Select the number of axes as 20

Plot the PCA

pca1 <- glPca(b)
scatter(pca1, posi="bottomleft")

Colorplot

myCol <- colorplot(pca1$scores,pca1$scores, transp=TRUE, cex=4)
abline(h=0,v=0, col="grey")
add.scatter.eig(pca1$eig[1:20],2,1,2, posi="bottomleft", inset=.18, ratio=.2)