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adegenet (version 1.4-2)

H3N2: Seasonal influenza (H3N2) HA segment data

Description

The dataset H3N2 consists of 1903 strains of seasonal influenza (H3N2) distributed worldwide, and typed at 125 SNPs located in the hemagglutinin (HA) segment. It is stored as an R object with class genind and can be accessed as usual using data(H3N2) (see example). These data were gathered from DNA sequences available from Genbank (http://www.ncbi.nlm.nih.gov/Genbank/).

The data file usflu.fasta is a toy dataset also gathered from Genbank, consisting of the aligned sequences of 80 seasonal influenza isolates (HA segment) sampled in the US, in fasta format. This file is installed alongside the package; the path to this file is automatically determined by R using system.file (see example in this manpage and in ?fasta2genlight) as well.

Usage

data(H3N2)

Arguments

encoding

UTF-8

source

This dataset was prepared by Thibaut Jombart (t.jombart@imperia.ac.uk), from annotated sequences available on Genbank (http://www.ncbi.nlm.nih.gov/Genbank/).

References

Jombart, T., Devillard, S. and Balloux, F. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. Submitted to BMC genetics.

Examples

Run this code
#### H3N2 ####
## LOAD DATA
data(H3N2)
H3N2

## set population to yearly epidemics
pop(H3N2) <- factor(H3N2$other$epid)



## PERFORM DAPC - USE POPULATIONS AS CLUSTERS
## to reproduce exactly analyses from the paper, use "n.pca=1000"
dapc1 <- dapc(H3N2, all.contrib=TRUE, scale=FALSE, n.pca=150, n.da=5)
dapc1

## (see ?dapc for details about the output)


## SCREEPLOT OF EIGENVALUES
barplot(dapc1$eig, main="H3N2 - DAPC eigenvalues")


## SCATTERPLOT (axes 1-2)
scatter(dapc1, posi.da="topleft", cstar=FALSE, cex=2, pch=17:22,
solid=.5, bg="white")




#### usflu.fasta ####
myPath <- system.file("files/usflu.fasta",package="adegenet")
myPath

## extract SNPs from alignments using fasta2genlight
## see ?fasta2genlight for more details
obj <- fasta2genlight(myPath, chunk=10) # process 10 sequences at a time
obj

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