[adegenet-forum] Fwd: Individuals for genind not plotting dapc

[Thibaut Jombart]

Dear Philip,

it looks like all individuals from a given cluster are exactly at the same
location, which would be the case if they are identical genotypes.

Assuming your genind object is 'x', can you check what this returns:

 table(table(apply(genind2df(x, sep="", usepop = FALSE), 1, paste, collapse
= "")))

This will derive the frequencies of haplotypes in the data. I think there
is something to do this more elegantly in poppr but I will let Zhian
comment if this is the case.

Best
Thibaut




--
Dr Thibaut Jombart
Lecturer, Department of Infectious Disease Epidemiology, Imperial College
London
Head of RECON: repidemicsconsortium.org
WHO Consultant - outbreak analysis
sites.google.com/site/thibautjombart/
Twitter: @TeebzR
+44(0)20 7594 3658

On 22 July 2017 at 05:19, Phillip Skipwith <pskipwith at gmail.com> wrote:

> Hi,
>
> I'm pretty new to Adegenet, but I have been through the tutorials and have
> been more or less successful getting it to work on my empirical data. This
> is a phylogenomic dataset of 83 individuals from eight clades and 4,268
> loci (I'm using 4,035 SNPs for ordination, etc.).  I realize the sample
> size is small, but this is hard-earned field data. The problem arises when
> I'm trying to use dapc after find.clusters on the below genind object.
>
> gen.struct
> /// GENIND OBJECT /////////
>
>  // 83 individuals; 4,035 loci; 8,341 alleles; size: 4.5 Mb
>
>  // Basic content
>    @tab:  83 x 8341 matrix of allele counts
>    @loc.n.all: number of alleles per locus (range: 2-4)
>    @loc.fac: locus factor for the 8341 columns of @tab
>    @all.names: list of allele names for each locus
>    @ploidy: ploidy of each individual  (range: 2-2)
>    @type:  codom
>    @call: read.structure(file = "final_Struct_good_maybe.str", n.ind = 83,
>     n.loc = 4035, onerowperind = F, col.lab = 1, col.pop = 2,
>     row.marknames = 0, ask = F)
>
>  // Optional content
>    @pop: population of each individual (group size range: 2-27)
>
> grp <- find.clusters(gen.struct, max.n.clust=35)
>
> Choose the number PCs to retain (>=1):
> 80
> Choose the number of clusters (>=2:
> 9
>
> dapc1 <- dapc(gen.struct, grp$grp)
>
> dapc1
> #################################################
> # Discriminant Analysis of Principal Components #
> #################################################
> class: dapc
> $call: dapc.genind(x = gen.struct, pop = grp$grp)
>
> $n.pca: 60 first PCs of PCA used
> $n.da: 4 discriminant functions saved
> $var (proportion of conserved variance): 0.946
>
> $eig (eigenvalues): 182000 71010 34130 20710 16790 ...
>
>   vector    length content
> 1 $eig      8      eigenvalues
> 2 $grp      83     prior group assignment
> 3 $prior    9      prior group probabilities
> 4 $assign   83     posterior group assignment
> 5 $pca.cent 8341   centring vector of PCA
> 6 $pca.norm 8341   scaling vector of PCA
> 7 $pca.eig  82     eigenvalues of PCA
>
>   data.frame    nrow ncol content
> 1 $tab          83   60   retained PCs of PCA
> 2 $means        9    60   group means
> 3 $loadings     60   4    loadings of variables
> 4 $ind.coord    83   4    coordinates of individuals (principal components)
> 5 $grp.coord    9    4    coordinates of groups
> 6 $posterior    83   9    posterior membership probabilities
> 7 $pca.loadings 8341 60   PCA loadings of original variables
> 8 $var.contr    8341 4    contribution of original variables
>
> Choose the number PCs to retain (>=1):
> 60
> Choose the number discriminant functions to retain (>=1):
> 4
>
> scatter(dapc1, scree.da = T)
>
> The end result is a plot with the centroid points for each of the clusters
> but not the individuals. I know there is probably something simple that I'm
> missing or there's something intrinsically wrong with my code and or data.
> I've perused the forum for similar issues and nothing is quite spot on to
> what I'm asking here.
>
> Any help would be greatly appreciated.
>
> Best,
>
> Phillip
>
>
>
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