## 2009-12-19

### Packgoats

Pack goats? Look here.

## 2009-12-13

### Galton's quincunx in R

Andrej Blejec has a very nice R demo of Galton's quincunx (link1, link2). It is a bit tedious to copy the code from PDF to R console, but it is worth the effort as the demo simulation clearly shows the nature of quincunx. After a bit of search I also found a similar function quincunx in the animation R package by Yihui Xi.

Image source: Wolfram MathWorld

## 2009-11-20

### Components of genetic improvement

I caught a quote (by Blasco) at the ACTEON maling list: "The genetic improvement applied is 15% science and 85% sociology." - translated by Google

## 2009-11-16

### Phenotype MicroArrays - building the hierarchy in biology

I got an e-mail in my box about the presentation of Phenotype MicroArrays (PM) at our department. I will not be able to attend it, but this site describes the idea behind it. This "tool" is a nice addition to a set of DNA/RNA and protein arrays. Adding PM means that we can move one layer above the gene-protein layer. However, as my interest often lies in ultimate phenotype of an individual that we observe, we are still some layers far from deciphering the role of genes on the ultimate phenotype.

Source: http://www.biolog.com

## 2009-11-15

### Slick correlation "plots"

Slick correlation "plots" in Wikipedia entry for correlation. I just wonder if correlation should really be zero for the (3,2)-th case. I woukd say it should be slightly more than zero.

## 2009-11-12

### Sweave-Lyx from terminal on Mac

Mark Heckmann writes:
In your paper "Using Sweave with Lyx" (great work bty) you pointed out that one can see the sweave error code when processing when starting lyx from the terminal. I just changed from Windows to Mac so that's new for me. Could you send me a few lines how to do that, that is how to operate lyx from terminal and sweave the content from the terminal.
I am not familiar with Mac, though would be happy to own one;) Since Mac OS is build on top of some linux/unix like system you need to start the terminal (console) with shell and find the lyx binary. Perhaps something like this on my linux box (text following $are shell commands) # Find the lyx binary$ which lyx
/usr/bin/lyx

# Start lyx from console

## 2009-07-30

Euston Grove Press offers to interested users a free download of the book "Sewall Wright Taught Me. 2. Genetics". Here is the link. For me this is interesting, but impossible to read.

## 2009-07-16

### LyX-Sweave: mandatory use of control+enter in code chunks

A user of LyX-Sweave is asking:
My embarrassingly simple question is this: For class notes, I often have lots of code to include. I develop code in R, & paste code into a scrap section. But then I have to step through it all and find the spots to insert control-enter to terminate lines. Inevitably I miss a few, then the code breaks (without a clue as to where). So, is there a simple way to move the code into a scrap that bypasses the control-enter problem?
First of all, you can easily see where Sweave has problem by launching LyX from the terminal. Then you will see the output of R CMD Sweave in the terminal and you can easily spot the problematic chunk. This works on MS Windows as well as on Linux! There is some development going on with LyX and it seems that it will be possible in the future to see the Sweave log in LyX directly as it is possible for LaTeX log.

I agree that mandatory the use of cotnrol+enter in scrap (code chunk) environment is suboptimal. I also hate it! But that is the way LyX is created. One way you can avoid this for now is to not use the "scrap" environment at all - you can insert the code chunks (starting with <<>>= and ending with @) in the LaTeX code (use shortcut control+l). I tried this on my laptop and works without problems. In future versions of LyX this resctriction might be lifted.

For me e-mail and RSS are two really important components of world-wide-web. However, some sites do not publish RSS, which is a pitty given that I do not have time to visit them often. In such cases Page2RSS service can be used to be informed about sites changes. I find this service today and I hope it will work fine.

## 2009-07-14

Lep primer, kako lahko s kozami uspešno "saniramo" zaraščeno površino s pleveli. Uspeh na slikah je kar preveč dober. Če bi imeli bistveno večjo površino, uspeh najbrž ne bi bil tako dober - pri tem je ključna obtežba - za "čiščenje" mora biti obtežba ZELO velika.

## 2009-07-06

### 9th WCGALP - next year

The website for the 9th WCGALP (World Congress on Genetics Applied to Life Stock Production) is online. There is not much there yet, but this will surely change with time.

Here is a link to previous WCGALP in Brasil in 2006. I can not find the website of the 7th anymore - it was held in Montpellier (France).

## 2009-07-03

### Evaluation of different approaches for the estimation of daily yield from single milk testing scheme in cattle

Janez finnished and submitted the paper "Evaluation of different approaches for the estimation of daily yield from single milk testing scheme in cattle". He did the majority of job! I improved his work a bit with the comments and restructuring/rewritting some parts of the paper.

Evaluation of different approaches for the estimation of daily yield from single milk testing scheme in cattle

## 2009-06-27

### SGLPGE Symposium videos

are now on-line!

P.S. I hope they will fix the link/filename for the presentation of Augstin Blasco.

## 2009-06-19

### bugsparallel

bugsparallel is a Metrum Institute project to run BUGS (via R2WinBUGS) in parallel - McMC is an application, where parallel runs can be used very efficientlly. Here is the code for one example using bugsparallel.

## 2009-06-16

### Samanthina valeta

Samy je včeraj imela valeto in tukaj prilagam nekaj slik, ki jih je naredila naša prijateljica Polona K.

## 2009-06-12

### European Summer Institute in Statistical Genetics 2009

... will take place at Univeristy of Liege from Aug. 31 to Sep. 9. The Graphical model for genetics module looks particularly interesting to me, but there are also other very fine modules!

### Computational aspects in Animal Breeding

Here is a nice presentation by Misztal and Rekaya about computational aspects in animal breeding.

## 2009-06-11

### Fun picture of genetic experiments with cattle

Source: Cécile Dumas, AUG Liege

## 2009-06-09

### Loking for cattle genetics presentations?

Go here - courtesy of Kent A. Weigel.

## 2009-06-04

### Posters from SGLPGE Symposium.

... are available here. I hope they will also publish the presentations of the talks - the list of presented issues is overwhelimng.

## 2009-05-27

### Embeding fonts in figures produced by R

Some publishers insist that we embed (include) the fonts in each figure. Here is a set of links regarding this issue for figures produced by R:

### Generation interval calculation example

Here is a nice sheet with example of generation interval calculation in a flock of sheep.

## 2009-05-25

### Fitting pedigree based mixed models in BUGS software

Bellow is my abstract for talk at joint congress of SBD and SGD at Otočec. I will show how BUGS (Bayesian Using Gibbs Sampling) software can be used to fit the so called animal model. Now I need to prepair the talk and perhaps even write a short communication for some journal. Added 2009-09-20: The talk is available here.
Pedigree based mixed model (commonly called animal model) is an important class of statistical models for inference of quantitative genetic parameters in various fields such as animal and plant breeding, evolutionary biology and human genetics. In last years Bayesian statistics has been introduced to a set of standard statistical procedures of a quantitative geneticists' toolbox, due to the ever increasing complexity of fitted models. While several specific programs can be used to fit animal model using Bayesian approach, none of them provide and easy to use and flexible environment for the development and testing of models. It is common to use favourite programming language to develop the needed programs, but this requires a considerable amount of programming and statistical skills. A viable alternative is to use general purpose statistical packages. BUGS (Bayesian Using Gibbs Sampling) is a popular and fairly flexible program for the Bayesian analysis of complex statistical models using Markov Chain Monte Carlo methods. Recently two reports of fitting animal model in BUGS were given, but both failed to provide a generic procedure that can be used independently of the collected data. Here, a generic description of animal model is presented using the concept of graphical models. This description was translated to BUGS language and fitted to a small example. Comparison with other programs revealed the validity of a new procedure. Tests with other data sets showed that BUGS can be used to efficiently fit animal model for medium sized data sets. Using these results quantitative geneticists can now easily use Bayesian approach to fit animal model in BUGS.

## 2009-05-02

### Genetic architecture of quantitative traits in mice, flies, and humans

Flint and MacKay published a paper: "Genetic architecture of quantitative traits in mice, flies, and humans". I think it is now is clear that revolutionary ideas that were spured by the field of molecular genetics are still far from reality. There surely is a lot of progress, but also at considerable investments.

Those interested in quantitative genetics might also be interested in:

## 2009-04-30

### SAS goes with sparse matrices

SAS has introduced experimental procedure HPMIXED (High Performance MIXED) in version 9.2. This is a welcome addition and now SAS could probably solve the problem I encountered lately with a large mixed model described here. I really like R and its community (which is getting bigger and bigger and more and more connected to other communities!), but I must say that for me SAS has made quite some important moves lately - see here, here, and here.

## 2009-04-23

### Statistics for Molecular Genetics

Nice notes about Statistics for Molecular Genetics by Karin Dorman.

## 2009-04-21

### Genes for cowboys

I rally like the title of this "material": Genes for cowboys. I still need to parse the content.

## 2009-04-19

### Video posnetki povezani s čebelami

Danes sem naletel na zgledno urejeno spletno stran ČEBELARSTVO Grega Lužar - tipa sploh ne poznam, tako da mu ne delam reklame. Na spletni strani je kar nekaj zanimivih video posnetkov opravil/dogodkov, ki jih sam še nikoli nisem videl:

## 2009-04-08

### Inference for R

I got a message from Inference for R team. Their work is interesting, especially if you are bound to MS Excel and Word environment! It would be great if they would also support OpenOffice. They "benefit" from open source R and it would be great if they would also provide a solution for open source "office".

See here.

## 2009-04-01

### Sweave.sh update

A local version of Sweave.sh has been updated:
• fixed a buglet that caused weaving the file twice when --weaver option was used --> this led to a change how caching is now invoked (--cache invokes cacheSweave package, while --cache --weaver or --weaver invokes weawer package)
• quoting *APP variables to ensure that things work in case of "bad" filenames, i.e., spaces in filenames etc.
• small changes in the documentation
I will take this opportunity to show how PDFAPP and PSAPP environmental variables can be used "open" options. This is an example from the help, which shows that these two variables need to be exported in order to have any effect. I am still fiddling whith how to provide any meaningfull defaults. My defaults are 'acroread' for PDF and 'gv' for Postscript, but I am happy to set any other more meaningfull defaults if there will be enough demand!
# Create PDF via the texi2dvi (latex) tool and open
# a produced file
Sweave.sh -otld file.Rnw

# Create PDF via the texi2dvi (latex) tool and open
# a produced file with a "non-standard" viewer
Sweave.sh -otld=acrobat file.Rnw

# ... or
export PDFAPP=acrobat
Sweave.sh -otld file.Rnw
This is an example of launcing Acrobat Reader installed on MS Windows, while Sweave.sh is launched within Cygwin X-terminal:
Sweave.sh -otld file.Rnw

## 2009-03-31

### Semiparametric regression via penalized splines literature

Interested in semiparametric regression via penalized splines? Take a look here.

## 2009-03-24

### Kako ravnajo s poginulimi živalmi čez lužo

Glej "Dealing With Deadstock". Pri nas pa v določenih pogledih pretiravamo do skrajne mere. Se povsem strinjam, da mora biti ta segment živinoreje primerno urejen, a za to izvajati "vesoljske" procese ni razumno.

### Genomic selection in beef cattle

Stephen P. Miller has wrote two short articles about application of genomic selection in beef cattle:

## 2009-03-21

### Progress bar in R

Nice summary on how to use progress bars in R. I am posting this here in order to have a note for later searches.

## 2009-03-20

### Weather change - shit!

See here what kind of problems are Australian farmers facing due to weather changes.

## 2009-03-17

### Describing genetic variability

An example: we have two populations A and B (this could also be two different traits!), with means 5 and 10, additive genetic variance 5 and 5, heritabilities 0.2 and 0.2. Based on heritabilities we could conclude that selection will have the same effect in both populations, but this is not true in relative meaning. In population A the additive genetic variance is euqal to the mean, whereas it is only half of the mean in population B. The additive genetic coefficient of variations would be 0.45 and 0.22 for population A and B, respectively. This means that we can achive relatively greater response to selection in population A than in population B.

## 2009-03-14

### Video lectures about genetics (biology)

In addition to YouTube videos about genetics there is also a huge number of video lectures at http://videolectures.net/. There is a lot of material on machine learning, statistics, ..., but also biology - see Introduction to Biology which is a course from MIT. Bellow is a link to first lecture on Genetics given by Lander.

### Slick spline plot in SAS

Here is an example of a slick spline (using penalized b-splines) plot in SAS. The plot is created with SGPLOT procedure. I hope SAS will add such "functions" also to model based procedures such as GLM, MIXED, GENMOD, ...

## 2009-03-13

### European Master in Animal Breeding and Genetics

Posredujem novico o štipendijah za študij "European Master in Animal Breeding and Genetics". Kratek pregled predmetnikov (Course contents) na spletni strani http://www.emabg.eu pokaže, da je večina predmetov na temo genetike in selekcije na splošno in ločeno po vrstah živali, ki so pomembne za živinorejo. Je pa na voljo tudi nekaj bolj splošnih predmetov, ki bi lahko bili zelo zanimivi - psi in mačke!

Dear all
Scholarships are available for students from EU countries that want to participate in the European Master in Animal Breeding and Genetics (EMABG) starting in August 2009. Deadlines for applications: May 1st 2009. The deadline for non-EU students that want to participate in course starting this year has passed but they can applied before January 15th 2010 for the next academic year. Information on program and scholarships can be found at www.emabg.eu

The European Master in Animal Breeding is accepted by the European Union as an Erasmus Mundus MSc programme for a five-year period starting in 2007. In 2007, 24 students started the program followed by 21 students in 2008. The universities participating in the EM-ABG are Wageningen University (the Netherlands), University of Natural Resources and Applied Life Sciences (Austria), Christian-Albrechts-Universität (Germany), AgroParisTech (France), Swedish University of Agricultural Sciences (Sweden) and The Norwegian University of Life Sciences (Norway). These groups have a long tradition of collaboration and a strong profile in the area of Animal Breeding and Genetics.

EM-ABG secretary, Animal Breeding and Genomics Centre, Wageningen University, PO Box 338, NL 6700 AH Wageningen, The Netherlands, emabg@wur.nl

Kindest regards

Johan van Arendonk
Co-ordinator of EMABG

## 2009-03-12

While browsing for SNP chips for sheep I found out that there are some very nice videos on YouTube about genetics. Here is a list of some, but be free to explore further on!

### Chip for sheep

There is a lot of work in the area of SNP-chips for sheep. See:
However, genomic selection with "standard" chips might not be so successful in all sheep populations since there is a lot of variation in a sense that that the linkage disequilibrium is not so strong as in cattle - though I am saying that without having much experience!

## 2009-03-11

### 3D health card

This is cool! Click on video if you do not speak Slovenian.

### Growth performance of station tested rams in Slovenia

This is our short communication for ASD 2009.

Update 2009-03-13: We had to shorten the manuscript to three pages. This of course lead to the exclusion of some results that will be published elsewhere.
Growth performance of station tested rams in Slovenia

## 2009-03-10

### Substantial update of "Evolution and Selection of Quantitative Traits"

Bruce Walsh send an e-mail to AGDG list about the substantial update of their forthcoming book "Evolution and Selection of Quantitative Traits". After very successful volume 1, we are all eagerly waiting for this volume!

### Armidale Animal Breeding Summer Course 2009 Materials

UNE in Armidale organizes each year an Animal Breeding Summer Course. This year they hosted Bruce Walsh (Quantitative Genetic Theory and Analysis: Selection Theory) and Pieter Bijma (Quantitative Genetic Models for social interaction and GxE and inherited variability). What I really like about this course is that all the materials are posted on the website (follow this link for materials for this year). Therefore, all of us that did not had the opportunity to go down under can still study!

## 2009-03-06

### Genomska selekcija

Danes sva imela s Potočnik Klemnom predstavitev o genomski selekciji. Jaz sem na splošno predstavil "klasično" selekcijo in v čem se razlikuje genomska selekcija, medtem ko je Klemen predstavil vtise in informacije z Interbull delavnice. Moj del predstavitve je na voljo tukaj, za pregled stanja pa lahko sledite tej povezavi.
Genomska selekcija

## 2009-02-22

### R graphics: margins are way to large

For me R has a very nice and powerfull capabilities for graphics (for example see this gallery). However, I dislike the default setting for margins and placement of axis numbers and labels. Since I always forget the setting of parameters I prefer I am adding this post. For example:
library(package="MASS")Sigma <- matrix(c(10, 10, 10, 20), nrow=2)mu <- c(100, 100)tmp <- mvrnorm(n=200, mu=mu, Sigma=Sigma, empirical=TRUE)plot(tmp, xlab="X variable (unit)", ylab="Y variable (unit)")
Now compare this plot to the version I prefer much more:
par(bty="l", pty="m", mar=c(3, 3, 1, 1), mgp=c(1.75, 0.75, 0))plot(tmp, xlab="X variable (unit)", ylab="Y variable (unit)")

### Illinois long-term selection experiment for oil and protein in corn

Researchers at the University of Illinois are conducting one of the longest experiments in biology - Illinois long-term selection experiment for oil and protein in corn. The experiment started in 1896 and is still active! In esence they are selecting lines for higher or lower concentration of protein or oil in the kernel. This experiment is very important for a test of the theory of genetics, especially quantitative genetics (link1, link2, link3, link4, link5). I have seen several times the trends from this experiment and I wanted to include them in a talk I am prepairing. A brief search on the web lead me to this site with generation means by line. Bingo! This is all I needed. Bellow is a graph of trends and at the end of the post the R code used to produce the plot.

The theory states that genetic variance and consequently also the genetic gain should diminish after several generations of selection. There are experiments that confirmed that, but in the Illinois corn experiments the limit is not yet reached. Crow (2008) propose the following reasons (verbatim copy!):
1. "The environment is continually changing so that what was formerly most fit no longer
is."
2. "There is an input of genetic variance from mutation, and sometimes from migration."
3. "As intermediate-frequency alleles increase in frequency towards one, producing less variance (as p → 1, p(1 − p) → 0), others that were originally near zero become more common and increase the variance. Thus, a roughly constant variance is maintained."
4. "There is always selection for fitness and for characters closely related to it."
First point is a bit to general, but it sure is relevant. The second point is well known and an important source of new variation (e.g. see this work in mice for some estimates of mutational variance). I am very glad I came across this paper by Crow, because I never thought about the issue that he raises in third point. To me this is very simple and obvious explanation for maintenance of genetic variance over a relative short period with selection in action. I can not say much about fourth point, but this surely is relevant, especially in animals, where inbreeding (a consequence of selection) has greater effect on fitness than in plants.

Now the R code. First I tried to use read.table(file=url(...)), but the data-file had an error - there was a typo on line 68 or 86 - I do not remember anymore. I downloaded the file, fixed the typo and used the following code:

podatki <- read.table(file="corn.txt", na.strings=".", header=TRUE)cols <- c(rgb(red=204, blue=0,   green=0,   max=255),          rgb(red=0,   blue=153, green=0,   max=255),          rgb(red=0,   blue=0,   green=204, max=255),          rgb(red=204, blue=0,   green=153, max=255))par(bty="l", pty="m", mar=c(5, 4, 1, 1))matplot(x=podatki\$YR, y=podatki[, c("IHP", "ILP", "IHO", "ILO")], type="l", lty=1,        xlab="Year", ylab="Concentration (%)", col=cols[c(1, 1, 2, 2)], lwd=2)legend("topleft", c("Protein", "Fat"), lty=1,       lwd=2, col=cols[c(1, 2)], bty="n")

## 2009-02-20

### ATLAS

ATLAS (link1, link2) is a Java based tool to manage genotypes. It is handy, but notoriouslly frustrating to install, since there are several different instructions about how to install it - I am not talking about different instructions at different places (say on the net), but in the distribution package. This is very very confusing. I have just spent more than half an hour to install it and I remember I had the same problem last time I tried to install it. The correct instructions are in the ATLAS.html file and this should be done:
1. Create ATLAS directory in your user home directory, say "C:\Documents and Settings\GGorjan"
2. Add the following files to this folder (Atlas.jar, atlas.ini, chr.atl, ATLASman_v1.4.pdf, ATLAS.html)
3. Create directory ATLAS_files such as "C:\Documents and Settings\GGorjan\ATLAS\ATLAS_files" and put all figures and html files in there

## 2009-02-16

### Chromosome - DNA figure

National Human Genome Research Institute has a nice talking glossary of genetic terms. I especially this figure that shows a chromosome and how is it organized, i.e., DNA is wrapped with histones etc. However, there is only one chromosome and this is suboptimal if one wants to show the relationship between the genotype and DNA. Therefore I picked one version from the net (I do not remember where) and changed it a bit. I am publishing it here so that others might benefit as I did. There is plenty of place to annotate it.

## 2009-02-15

### R in SAS

Another "proof" that R definitely is one of mainstream statistical packages is the news that SAS will provide an interface to R via SAS/IML Studio (today known as SAS Stat Studio).

## 2009-02-11

### Fitting Legendre (orthogonal) polynomials in R

Frederick Novomestky packaged a series of orthogonal polynomials in the orthopolynom R package. However, his functions can not be used "directly" in a statistical model, say in lm(). There is no need to use functions from orthopolynom package, since there is a poly() function in stats package that is shipped with R. Nevertheless, I played with class of Legendre polynomials. (Wikipedia, Wolfram) This class of polynomials is very popular in my field since the introduction of so called random regression models (e.g. link1, link2, link3, ..., and some of our work), though the splines (Wikipedia, Wolfram) are making their way through (see this link and follow references). Let's go to orthopolynom package. Say we want to use Legendre polynomial of 4th order for a variable x. First we need to get the coefficients for basis functions:
library(package="orthopolynom")
(leg4coef <- legendre.polynomials(n=4, normalized=TRUE))
[[1]]0.7071068[[2]]1.224745*x[[3]]-0.7905694 + 2.371708*x^2[[4]]-2.806243*x + 4.677072*x^3[[5]]0.7954951 - 7.954951*x^2 + 9.280777*x^4
To use this polynomial in a model, we need to create a design matrix with sensible column names and without the intercept:
x <- 1:100leg4 <- as.matrix(as.data.frame(polynomial.values(polynomials=leg4coef,                                                  x=scaleX(x, u=-1, v=1))))colnames(leg4) <- c("leg0", "leg1", "leg2", "leg3", "leg4")leg4 <- leg4[, 2:ncol(leg4)]
Now we can use this in a model, e.g., lm(y ~ leg4). I made this whole process easier - with the functions bellow, we can simply use lm(y ~ Legendre(x=scaleX(x, u=-1, v=1), n=4)). I contacted Fred and I hope he will add some version of these functions to his package.

Update 2009-03-16: If we want that the intercept has a value of 1, we need to rescale the polynomial coefficients by multiplying with sqrt(2).
Legendre <- function(x, n, normalized=TRUE, intercept=FALSE, rescale=TRUE){  ## Create a design matrix for Legendre polynomials  ## x - numeric  ## n - see orthopolynom  ## normalized - logical, see orthopolynom  ## intercept - logical, add intercept  tmp <- legendre.polynomials(n=n, normalized=normalized)  if(!intercept) tmp <- tmp[2:length(tmp)]  polynomial.values(polynomials=tmp, x=x, matrix=TRUE)}polynomial.values <- function(polynomials, x, matrix=FALSE){  ## Changed copy of polynomial.vales from orthopolynom in order  ## to add matrix argument  require(polynom)  n <- length(polynomials)  if(!matrix) {    values <- vector(mode="list", length=n)  } else {    values <- matrix(ncol=n, nrow=length(x))  }  j <- 1  while(j <= n) {    if(!matrix) {      values[[j]] <- predict(polynomials[[j]], x)    } else {      values[, j] <- predict(polynomials[[j]], x)    }    j <- j + 1  }  values}

## 2009-02-10

### Course: Selección genómica

Hayes and Gianola will have a course "Selección genómica" from 25-29 May in Valencia. See here for details.

## 2009-02-06

### Course: Study of resistance mechanisms in animal infectious diseases course

On behalf of Anne-Sophie Lequarré:

A new session of the well quoted course "Study of resistance mechanisms in animal infectious diseases" will be held one last time at the University of Liège, Belgium from the 16 to the 20 of March 2009 .

This one-week course gives a general introduction to the methods for the identification and exploitation of genetic factors in infectious diseases. It explores the interactions between the genetic diversity of the pathogen and the host in their particular environments. The aim is to integrate the insights of the various disciplines to get a better picture of the genetic basis of resistance to major infectious diseases in livestock.

The course can interest breeders in order to optimize the production in presence of harmful pathogens, biologists to better understand the causes and consequences of co-evolution of the host and its pathogens and of course the epidemiologists.

The course will be taught at a level commensurate with a Master of Science's degree but can also serve as an elective course for researchers wishing to better understand analyses found in the scientific literature. Speakers involved are not only renown scientists but also very good teachers.

The course is supported by EADGENE, a European Network of Excellence on Animal Disease Genomics. Registration prices are quite affordable (250 Euros requested for students or academic personnel). More information can be found at (registration dead-line 15th of February):

## 2009-01-29

### More software for statistical/quantitative genetics

Today, there was a message on ACTEON list about the TM site that hosts two programs: TM (threshold and censored models) & GS3 (genomic selection) - see here.

### MCMCglmm package for R

Jarrod Hadfield published MCMCglmm package on CRAN. The package can fit generalised linear mixed models via MCMC methods. Bellow is the abstract from the vignette. The list of supported models is quite impressive. Nice job Jarrod! This is not the first package by Jarrod - there is also interesting (at least to me) package MasterBayes.
MCMCglmm is a package for fitting Generalised Linear Mixed Models using Markov chain Monte Carlo techniques. Most commonly used distributions like the normal and the Poisson are supported together with some useful but less popular ones like the zero-inflated Poisson and the multinomial. Missing values and left, right and interval censoring are accommodated for all traits. The package also supports multi-trait models where the multiple responses can follow different types of distribution. The package allows various residual and random effect variance structures to be specified including heterogeneous variances, unstructured covariance matrices and random regression (e.g. random slope models). Three special types of variance structure that can be specified are those associated with pedigrees (animal models), phylogenies (the comparative method) and measurement error (meta-analysis). The package makes heavy use of results in Sorensen and Gianola [2002] and Davis [2006] which taken together result in what is hopefully a fast and effcient routine. Most small to medium sized problems should take seconds to a few minutes, but large problems (> 20,000 records) are possible. My interest is in evolutionary biology so there are also several functions for applying tensor analysis [Rice, 2004] to real data and functions for visualising and comparing matrices.