From roman.lustrik at biolitika.si  Sat Dec  2 12:02:37 2017
From: roman.lustrik at biolitika.si (Roman =?utf-8?Q?Lu=C5=A1trik?=)
Date: Sat, 2 Dec 2017 12:02:37 +0100 (CET)
Subject: [adegenet-forum] Question about seploc error: "Error in
 dimnames(x) <- dn : length of 'dimnames' [2] not equal to array extent"
In-Reply-To: <CAEf4xgevU+2LWO=5TWNbBtsKae-kp0_G2fZYUdwam1pkwNr1OA@mail.gmail.com>
References: <CAEf4xgevU+2LWO=5TWNbBtsKae-kp0_G2fZYUdwam1pkwNr1OA@mail.gmail.com>
Message-ID: <1851487191.521659.1512212557605.JavaMail.zimbra@biolitika.si>

Sorry for the late reply. Can you make a small subset of your data which demonstrates this problem? 

---- 
In god we trust, all others bring data. 


From: "Rob Syme" <rob.syme at gmail.com> 
To: adegenet-forum at lists.r-forge.r-project.org 
Cc: "muhammadqudratullah farooqi" <muhammadqudratullah.farooqi at uwa.edu.au> 
Sent: Monday, November 20, 2017 10:41:11 AM 
Subject: [adegenet-forum] Question about seploc error: "Error in dimnames(x) <- dn : length of 'dimnames' [2] not equal to array extent" 

In trying to run seploc on a genind object (output from gl.read.silicodart from dartR v0.93), I get the error: 
>is.genind(gl) 
[1] TRUE 
> seploc(gl) 
Error in dimnames(x) <- dn : length of 'dimnames' [2] not equal to array extent 
10. 
	
`colnames<-`(`*tmp*`, value = seq(ncol(tab))) 
9. 
	
.local(.Object, ...) 
8. 
	
initialize(value, ...) 
7. 
	
initialize(value, ...) 
6. 
	
new("genind", ...) 
5. 
	
FUN(X[[i]], ...) 
4. 
	
lapply(kX, genind, pop = x at pop, prevcall = prevcall, ploidy = x at ploidy, type = x at type) 
3. 
	
.local(x, ...) 
2. 
	
seploc(gl) 
1. 
	
seploc(gl) 

Is there any way we can track down what peculiarity of our input data is causing the error? 

Thanks 

Rob Syme 
Curtin University 

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From jason at joines.org  Wed Dec  6 05:00:51 2017
From: jason at joines.org (Jason Paul Joines)
Date: Tue, 5 Dec 2017 23:00:51 -0500 (EST)
Subject: [adegenet-forum] what does 'd = ' mean in pca plots
Message-ID: <alpine.DEB.2.00.1712052259560.28791@joines.org>

adegenet Users,

         I used the scatter function to plot the glPca of a genlight object 
as shown in tutorial-genomics.pdf.  The plot includes a small inset 
barplot of Eigenvalues in the bottom left corner.  The top right corner 
has the text "d = n" where n is a number that differs from one plot to the 
next.  What does "d = n" represent?


Thanks,

Jason
===========

From roman.lustrik at biolitika.si  Wed Dec  6 15:10:00 2017
From: roman.lustrik at biolitika.si (Roman =?utf-8?Q?Lu=C5=A1trik?=)
Date: Wed, 6 Dec 2017 15:10:00 +0100 (CET)
Subject: [adegenet-forum] what does 'd = ' mean in pca plots
In-Reply-To: <alpine.DEB.2.00.1712052259560.28791@joines.org>
References: <alpine.DEB.2.00.1712052259560.28791@joines.org>
Message-ID: <1510117891.578847.1512569400724.JavaMail.zimbra@biolitika.si>

Following the code, I can trace it to ade4::scatter.grid (https://github.com/cran/ade4/blob/d571403a7ed08b2649c44901014aeb9e480ac1b0/R/scatterutil.R#L506).
`xaxp` is a vector of coordinates and number of intervals between tick marks (see ?par). The code takes second and first coordinate and divides it by the number of intervals. And `a`, which is `d = a`, appears to be the minimum of this for x and y. Sorry for not being less technical.

HTH,
Roman


----
In god we trust, all others bring data.

----- Original Message -----
From: "Jason Paul Joines" <jason at joines.org>
To: adegenet-forum at lists.r-forge.r-project.org
Sent: Wednesday, December 6, 2017 5:00:51 AM
Subject: [adegenet-forum] what does 'd = ' mean in pca plots

adegenet Users,

         I used the scatter function to plot the glPca of a genlight object 
as shown in tutorial-genomics.pdf.  The plot includes a small inset 
barplot of Eigenvalues in the bottom left corner.  The top right corner 
has the text "d = n" where n is a number that differs from one plot to the 
next.  What does "d = n" represent?


Thanks,

Jason
===========
_______________________________________________
adegenet-forum mailing list
adegenet-forum at lists.r-forge.r-project.org
https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/adegenet-forum

From jason at joines.org  Wed Dec  6 15:49:41 2017
From: jason at joines.org (Jason Paul Joines)
Date: Wed, 6 Dec 2017 09:49:41 -0500 (EST)
Subject: [adegenet-forum] what does 'd = ' mean in pca plots
In-Reply-To: <1510117891.578847.1512569400724.JavaMail.zimbra@biolitika.si>
References: <alpine.DEB.2.00.1712052259560.28791@joines.org>
 <1510117891.578847.1512569400724.JavaMail.zimbra@biolitika.si>
Message-ID: <alpine.DEB.2.00.1712060946310.28791@joines.org>

         Interesting.  Then it seems that 'd = a' only describes 
properties of the plot and says nothing about the analysis.

         Thanks for digging that out of the code.


Jason
===========



---------------------------------Original-Message---------------------------------
> Date: Wed, 6 Dec 2017 09:10:00
> From: Roman Lu?trik <roman.lustrik at biolitika.si>
> To: Jason Paul Joines <jason at joines.org>
> Cc: adegenet-forum at lists.r-forge.r-project.org
> Subject: Re: [adegenet-forum] what does 'd = ' mean in pca plots
> 
> Following the code, I can trace it to ade4::scatter.grid (https://github.com/cran/ade4/blob/d571403a7ed08b2649c44901014aeb9e480ac1b0/R/scatterutil.R#L506).
> `xaxp` is a vector of coordinates and number of intervals between tick marks (see ?par). The code takes second and first coordinate and divides it by the number of intervals. And `a`, which is `d = a`, appears to be the minimum of this for x and y. Sorry for not being less technical.
>
> HTH,
> Roman
>
>
> ----
> In god we trust, all others bring data.
>
> ----- Original Message -----
> From: "Jason Paul Joines" <jason at joines.org>
> To: adegenet-forum at lists.r-forge.r-project.org
> Sent: Wednesday, December 6, 2017 5:00:51 AM
> Subject: [adegenet-forum] what does 'd = ' mean in pca plots
>
> adegenet Users,
>
>         I used the scatter function to plot the glPca of a genlight object
> as shown in tutorial-genomics.pdf.  The plot includes a small inset
> barplot of Eigenvalues in the bottom left corner.  The top right corner
> has the text "d = n" where n is a number that differs from one plot to the
> next.  What does "d = n" represent?
>
>
> Thanks,
>
> Jason
> ===========
> _______________________________________________
> adegenet-forum mailing list
> adegenet-forum at lists.r-forge.r-project.org
> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/adegenet-forum
>
>

From thibautjombart at gmail.com  Wed Dec  6 18:50:04 2017
From: thibautjombart at gmail.com (Thibaut Jombart)
Date: Wed, 6 Dec 2017 17:50:04 +0000
Subject: [adegenet-forum] Grouping crossvalidation DAPC
In-Reply-To: <CAFSGzmvqP2O0asJ5=2xp2J+uPEvKqrfAuTeuaeGRPMevU3ajwg@mail.gmail.com>
References: <CAFSGzmvqP2O0asJ5=2xp2J+uPEvKqrfAuTeuaeGRPMevU3ajwg@mail.gmail.com>
Message-ID: <CANPRA+rJaoDK_w9BNJfW_nW=MUJdEszrR5+1dOh+UgGVtzSnvg@mail.gmail.com>

Hi Flo,

sorry about the late reply. I'd make an excuse, but it won't bit "been
busy". In short:

There is no proper solution to the group labelling issue you mention, at
least none that I know if. A workaround I have used alongside other
colleagues uses two statistics, relying on all pairwise comparisons of
individuals in the clusters:
- % of times 2 indiv are in the same cluster when they should
- % of times 2 indiv are in different clusters when they should

The average of the two quantities is I think the rand index:
https://en.wikipedia.org/wiki/Rand_index

For the second, simple answer: DAPC is *bad* at finding hybrids. For this,
consider using the soon-to-be-published (hopefully) method 'snapclust',
also in adegenet. Doc for this is hidden there:
https://github.com/thibautjombart/adegenet/raw/master/tutorials/tutorial-snapclust.pdf

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 21 November 2017 at 18:45, Florian Leplat <leplat.florian at gmail.com>
wrote:

> Dear Adegenet user,
>
>
> I was previously using adegenet package for genetic applications.
>
> Since I started to use the DAPC function. The methods is very informative.
> However there are some details that I would like to understand better.
>
>
>
> The main objective of my use is to group a certain number of plant
> genotype regarding to their genotypic background. Each genotype are
> homozygous lines.
>
> I have no prerequisite information for any genotype. Therefore the main
> idea is to attribute a ?group number? for each of my plants.
>
>
>
> I does work fine with a good comprehensiveness regarding to the
> information that I have for each plants (origin, parents...)
>
> However, one of the limitations that I face is the repeatability of the
> grouping. If running several time, a certain number of plant will be
> attributed to a different group. Is there a cross-validation procedure at
> this step in order to look at the percentage of plant always grouped
> together for each run ?
>
>
>
> Furthermore, even if my grouping are quite consistent ?group wise? from
> one run to the other, the grouping number will change. Is there a way to
> solve that (for instance give a group number to the founder genotype of our
> population) ?
>
>
>
> Then I have a second issue. After the first step which define my groups, I
> would like to plot hybrids genotypes which should (could) be an admixture
> between 2 groups. Therefore I cannot use them to build my groups as they
> add some noise to the model. I wanted to use the procedure described in the
> tutorial using supplementary individuals. I realized that it only works if
> the supplementary individuals have already grouping information, however I
> don?t have this information. Indeed I only want to see (mostly visually)
> where the hybrids are positioned in relation to the other groups that I
> previously defined. Is there a way to use the script to do that ?
>
>
>
> Thanks in advance for your help.
>
> Best regards.
>
>
> *Flo*
>
> _______________________________________________
> adegenet-forum mailing list
> adegenet-forum at lists.r-forge.r-project.org
> https://lists.r-forge.r-project.org/cgi-bin/mailman/
> listinfo/adegenet-forum
>
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From jnwang at ksu.edu  Tue Dec 12 18:41:00 2017
From: jnwang at ksu.edu (Jianan Wang)
Date: Tue, 12 Dec 2017 17:41:00 -0000
Subject: [adegenet-forum] Large data set problem for DAPC
Message-ID: <7C3FB9D6-5919-402F-A810-A963F46CE593@ksu.edu>

Dear Thibaut,

I?m running DAPC for a genomic data set including 400,000 SNPs and about 2000 individuals.

I converted my vcf genomic data set to the genlight format, and used multiple cores.

The major command line is as below:

dapc1 <- dapc(GBSgenlight, combine_race, n.rep = 3, n.pca=10, parallel = "multicore", ncpus = 4)


If I run a data subset including about 1000 individuals and pre-defined subpopulation names, the DAPC runs very well. However, when I run the full data set (2000 individuals), the DAPC job in the High Performance Cluster always quit automatically and no any result returned, after a long calculating or frozen.

It will be appreciated if anyone would like share any suggestions or solutions to address my problem.

In addition, can DAPC run a whole genome re-sequencing SNP data set? Or what?s the maximum data set can the DAPC cope with?


Thanks in advance.

Jianan

From andrew.j.veale at gmail.com  Wed Dec 13 14:08:53 2017
From: andrew.j.veale at gmail.com (Andrew Veale)
Date: Wed, 13 Dec 2017 13:08:53 -0000
Subject: [adegenet-forum] POV in DAPC
Message-ID: <AF5DED5D-FFBF-4218-82ED-5C400F61A105@gmail.com>

Hey!

I have been asked to add the percentage of variance explained by each axis in the DAPC scatter plot.  I?m not sure how best to do this, and I think it isn?t the most meaningful thing to do as it isn?t a straight PCA.  The POV of a PCA is fine, and I can see how to get the Eigen-values for each PC retained - just not the then combined ones for the DAPC.

Any thoughts on this?

Thanks!