Our plans for 2010 and beyond are to continue to provide outstanding software for the biological sciences, across the world, and specifically to assist in areas where funding is limited – the developing world and education. As the Copenhagen talks come to a close we are mindful of all our responsibilities to support scientists and researchers working to understand and suggest solutions to the issues, by providing the best and most appropriate data analysis software.

To find out more about our software, and how it assists scientists and researchers visit our webpages, or email us for a free 60 day trial at support, with your name and organisation quoting reference VISION17CB, and we will arrange one for you.

We wish you all a very happy Christmas and successful New Year. This year we have opted not to send any Christmas cards, and to support the World Food Programme, Gift of Hope .

Please note our offices will be closed from 25th December to 28th December 2009, and on 1st January 2010 – we look forward to meeting and talking with you in the new year.

Best wishes,

Stewart Andrews
CEO, VSN International

ASReml 3, the outstanding data analysis software designed for fitting linear mixed models is now available for download.

Already widely used by scientists and researchers in the biosciences the new procedures and functionality added to version 3 further extend ASReml’s ability to analyse large datasets and complex statistical models. Since its original launch ASReml has enabled scientists to investigate and understand relevant factors in breeding and genetics leading to for example, the identification of superior grain varieties for farmers in Australia (based on the National Variety Trials system) and generating herd heritability estimates (based on research at the Pennsylvania State University).

ASReml is vital for researchers with very large datasets, who may need to apply complex statistical models. Unlike other software systems ASReml can easily and efficiently handle large datasets. ASReml is unique in that it uses the Average Information (AI) algorithm for the fitting of linear mixed models and it is optimised for working with genetics data and hence performs considerably faster than other generic data analysis software. The superior range of variance models are specifically suited to the analysis of data arising from genetic applications in animal and plants, so ASReml is chosen by researchers and scientists who need these specific analysis tools provided in ASReml. It also has an in-built link with R for scientists and researchers who prefer to use the r programming environment rather than more generic windows based systems.

It was and continues to be developed by researchers working in bioscience, so the statistics are sound, valid and most importantly relevant to the needs of bioscientists. Users are supported by VSNi (if they have a support contract), a range of tutorials and user guides and by an active user community through the ASReml Forum, available through the VSNi webpages.

For a free 60 day trial of ASReml please email support with your name and organisation quoting reference VISION16CB, and we will arrange one for you.

For more details on ASReml, look at the new features.

Technical tip – New supported platforms for ASReml 3

ASReml has now been updated to run on both 32 bit and 64 bit applications of Linux both as the stand alone command driven ASReml and as the ASReml-R add on. Additionally Apple Macintosh users can run also run ASReml in a batch mode.

Windows (32 and 64 bit) users can use ASReml 3 as the command driven version, Windows interface or as an add-on to R.

For a more detailed explanation see the ASReml webpages.

Latest training courses

VSNi run training courses throughout the year on a variety of topics, and we are currently planning the schedule for 2010. Please email support with any specific training requests or go to the training pages on our website to keep updated on the latest courses.

Out and about with VSNi

From 29th November to 3rd December, the GenStat developer Dr David Baird will be presenting at the International Biometric Society Australasian Region Conference. Dr Alison Smith, a keen ASReml user, based at Wagga Wagga Agricultural Institute is also presenting her work on grain quality testing with ASReml at the conference.

If you would like to meet with VSNi staff at one of these events please email Carey Biggs to arrange the details.

We’re always updating the list of events we can support and sponsor – so please send us details of any events you are organising or involved in, and as we decide on more events for the future we’ll list them here.

The latest version of GenStat, the pioneering data analysis tool for bioscientists, is now available for download. This latest edition has been updated and enhanced to include a host of new and improved statistical techniques of particular use and interest to plant breeders and scientists working in genetic research.

Specific new features include the addition of stability co-efficients and genotype + genotype-by- environment biplots for use in variety trials, quantile regression and a suite of menus for QTL analysis. Enhancements to the GenStat graphics features include facilities to allow interactive selection between plotting components, which will assist with the interpretation of data – see the Technical Tip below for more details. GenStat’s existing core areas such as regression, REML and multivariate analysis have also been enhanced ensuring GenStat’s statistical techniques remain relevant, reliable and current.

“GenStat 12 is an outstanding achievement in terms of statistical capability,” says Stewart Andrews, CEO, VSNi, “and, importantly, demonstrates VSNi’s appreciation of the need to assist with solving the issues we all face. In an era of climate change, food shortages and food security, we have upgraded GenStat with statistical routines needed by scientists working to solve problems in world agriculture today.”

“One of the guiding principles behind GenStat’s development from its conception has always been careful consideration for scientific validity,” says Professor Roger Payne, CTO, VSNi, “GenStat’s history and pedigree provides users with the security of knowing that the results from GenStat analysis are founded on sound statistical principles. GenStat’s intelligent and well-planned menu system and comprehensive suite of diagnostic messages work together to guide users to the most correct and appropriate analyses for their data. In short, you can use GenStat with complete confidence.”

Also new in the 12th Edition is an interface to CycDesigN, the package for computer generation of experimental designs which constructs optimal or near-optimal block and row-column designs, via the GenStat menus. CycDesigN has been developed for scientists and researchers conducting experiments in field, glasshouse or laboratory trials, incorporating the latest research developments in experimental design. To obtain the CycDesign interface download the relevant files from the VSNI website, or for more information on CycDesign go to the CycDesign website.

For more details on GenStat, including a full list of new features and capabilities look at the VSNi website.

Technical tip – Interactive graphics in GenStat 12

Amongst the myriad of new features for the 12th Edition of GenStat, one of the more exciting is the ability to use the graphics interactively by making use of the ‘HOT’ components within the command DGRAPH, which allow the user to start with a basic plot and add elements to aid interpretation.

For example, the graph below shows a canonical variates biplot (figure 1) which makes use of another new feature for the 12th Release, the ability to plot oblique axes (see the command AXIS for further details).

Of the four groups here, we may be interested in plotting some extra features around one, or more, of the groups. For this, a hotmenu can be created and displayed in the Graphics toolbar giving you a drop-down menu of extra features that can be plotted (figure 2).

For this example we have several options, namely plotting the convex hulls or group means. If we select ‘Convex hull West’, ‘Group mean North’ and ‘Group mean South’ they will be added to the existing plot, as seen below. (figure 3)

Another element of the ‘hot’ components is the ability to select a point and plot extra information about that point. For this, we would use the hotdefinition parameter of DGRAPH. Selecting Hotchoice mode (the, new, rightmost button in the Graphics toolbar) (figure 4) allows us to select any hotpoints.

In the example we selected points 1 and 22 and we can now see the orthogonal projections from those points onto the four oblique axes. (figure 5)

More information about the ‘hot’ components can be found in the help for DGRAPH.

Latest training courses

On 15th September we’ll be running a course on REML and multi-level models in GenStat. The course is designed to introduce the user to REML in GenStat, and provide the underlying knowledge and confidence to use it correctly and effectively. It highlights how the REML menus guide the user through very complicated analysis and explains the REML commands so that users can program any non-standard analyses.

The course covers 4 main sessions:

• Analysis of variance
• Meta analysis
• Spatial analysis
• Repeated measurements

For more details on both courses and to book email support or go to the training pages on our website.

Out and about with VSNi

From 22-25th September Stewart Andrews (CEO) and Carey Biggs (Commercial Director) will be in Bangkok at the ABIC Conference 2009.

From 27th September to 2nd October we are back in Australia at the Barossa Valley for the Association for the Advancement of Animal Breeding and Genetics Conference.

Professor Roger Payne, our Chief Technical Officer is speaking at the ASA-CSSA-SSSA, in Pittsburgh between 1st and 5th November.

If you would like to meet with VSNi staff at one of these events please email Carey Biggs to arrange the details.

We’re always updating the list of events we can support and sponsor – so please send us details of any events you are organising or involved in, and as we decide on more events for the future we’ll list them on our website.

Since starting work at VSNi it’s no surprise to find so many applications of our software, be it GenStat or ASReml, are working within some aspect of agricultural research; projects that range from development of new plants to new herbicides or pesticides. But this isn’t just a race to find the best, most productive type of grain, or the most effective pesticide, in so many cases this is linked to the welfare of the local ecology. More and more agricultural producers can now see a benefit of using the earth’s natural resources to assist in crop production.

Researchers at the New South Wales Department of Primary Industry in Australia highlight the complexities of farming using one of the more traditional methods of crop production. Southern Australian farms have long used annual legumes in the pasture phase of crop rotation methods. These act as natural disease breaks and restore soil structure and nitrogen in the soil, as well as providing valuable, high quality feed for livestock. Fantastic! In the panic of today’s world on pesticide poisoning this seems an ideal solution, and has certainly been a good one – here we are using the earth’s natural resources and traditional crop rotation methods to help increase production, and as a bonus create livestock feed.. however it is not that straightforward.

The problem with annual pastures and crops, is that they are often shallow rooted and therefore use less rainfall than the deeper rooted perennial species. This has led to a significant increase in groundwater recharge with higher water tables and dry land salinisation in parts of Australia where the agricultural production has meant a change from perennial deep-rooted species to annual crops and pastures. Simple answer! Surely we just swap the annual pastures and crops for perennial ones… but which one? Australia is a big country with a diverse range of climates. How then do you determine which perennial legumes and herbs are best suited to Australian conditions, with so much variation between regions?

A team of researchers headed by Guangdi Li took on the challenge. The purpose of their study was to evaluate a wide range of herbaceous perennial species as potential new species for incorporation into the farming system of Southern Australia. Guangdi Li’s team needed to identify species with an ability to adapt to a broad range of environments, and species which are particularly suited to specific soil conditions, environments and climatic patterns. They evaluated 91 perennial legumes and herbs (entries) at 10 sites across Southern Australia. There were originally 17 sites but 7 were abandoned because of weeds or poor establishment leaving 4 in Western Australia, 1 in South Australia and 5 sites in New South Wales. Only a subset of the 91 was sown at each site, local conditions not being conducive to the successful establishment of many of the varieties. In fact only a handful of the entries were sown at all the sites. Some of the sites were chosen because they posed environmental constraints to plant growth and hence could be used to identify alternate species that may be better adapted to these more demanding environments. Those constraints were saline or waterlogged soils, although drier than usual conditions minimised the effects of waterlogging. Over the three years of the experiment there were a number of occasions that herbage mass and plant frequency was assessed across the ten sites, creating 67 and 21 ‘environments’. Each environment provides information about the performance of the varieties, but of course successive samplings from the same site are not independent of each other, and a high correlation was expected.

ASReml was chosen to analyse this data because it can handle the estimation of the genetic correlations between pairs of environments. The analysis involves a mixed model in which the variance-covariance matrix of the entries in different environments is modelled using a factor analytic (FA) structure. The FA model facilitates the accurate prediction of entry means for individual environments using best linear unbiased prediction. Selection across a range of environments, be it the saline or waterlogged sites or even for those samplings taken in Summer for instance, is easily achieved by using the Predict facility in ASReml. Entries that showed potential in saline or waterlogged conditions can be targeted for inclusion in future breeding programs.

The complexities of this study very much reflect the complexities faced by the agricultural producers. In farming there are often no straightforward, obvious answers to the questions posed and the problems faced. This is why research and studies such as Guandi Li’s are so important; they give evidence based on sound science and statistical analysis techniques which show the importance of specific types of plants; in this instance Lucerne, which performed well over a broad range of environments. This in itself suggests projects are needed to fully exploit this plant so that its limiting factors (susceptibility to acid conditions and heavy grazing) can be overcome. Additionally Guangdi Li and his team showed that there is a range of deep-rooted perennial legumes and herbs which could be used in the Southern Australian farming system, rather than relying on a narrow range. The impact of the results of this and future trials are huge, it is yet another step closer to even better planned farming policies and methods, and hence to a true understanding of how we best feed ourselves and the world.

There is no doubt that sound scientific research is needed on which to base future crop, farming methods or policy decisions; research that is built using proven scientific tools. VSNi are a key provider of these tools; we know this because many agricultural scientists rely on us to continue providing high quality, relevant statistical analysis software built by statisticians who understand the complexities of agricultural research and data.

For more details on ASReml, its capability and why over 41% of papers presented at the last meeting of the Australian Association for the Advancement of Breeding and Genetics cited ASReml look at the VSNi website.

Technical tip – New Guide for Analysing Climatic Data in GenStat

We are delighted to announce a new guide which is available for download from the VSNi website. The new guide titled Analysing Climatic Data using GenStat, covers an introduction to GenStat, data input and basic data manipulation, simple statistical inference, including the use of boxplots and comparison of means and basic regression. After mastering the basics, the guide explains the summary and presentation of climatic data and then more detailed explanation of statistical methods including linear, non-linear, multiple regression and multivariate analysis. Finally, the guide assists users with GenStat programming for those who want to move from menus to more complex modelling and analysis.

Our thanks to the Statistical Services Centre at the University of Reading for this guide.

Latest training courses

New courses coming over the summer include:

• Introduction to ANOVA, 9th-10 July, Apsley, Hertfordshire, UK
• Introduction and Intermediate ASReml, 12-13 August, Apsley, Hertfordshire, UK
• REML and multi-level models in GenStat, 15 September, Apsley, Hertfordshire, UK

GenStat users who are looking for assistance with Analysis of Variance should book onto the Introduction to ANOVA on 9th to 10th July, in Apsley, Hertfordshire, UK.

The aim of the course is to introduce ANOVA techniques and develop the fundamental knowledge and skills to use them correctly and effectively. The basic principles of experimental design will also be included to aid the effective planning of experiments and investigations.

By the end of the course users will be able to:

• Select an experimental design appropriate to the requirement of your investigations.
• Use randomization to avoid bias in the allocation of units to treatments, to ensure that results are reliable and unaffected by any systematic patterns in the units.
• Determine how many replicates are required for your designs.
• Use blocking to increase the accuracy of an experiment by forming the basic units (e.g. plots or subjects) into groups with similar properties.
• Analyse simple to sophisticated designs, explaining ideas such as balance, and to recognise the GenStat features available for the analysis of unbalanced designs.
• Compare several types of treatment in the same experiment.
• Interpret experimental results and produce relevant tables, graphs and figures for publication in reports and papers.

Dr Arthur Gilmour is running Introduction and Intermediate ASReml Courses on 12-13 August again in Apsley, Hertfordshire. Participants will gain an insight into the concepts underlying ASReml and hands on experiences relevant to their own applications. Participants are welcome to prepare examples they would like analysed during the workshop and forward them before the end of July to support, so that the courses can be tailored to include specific user examples.

Day one will cover an Introduction to ASReml and simple univariate models. On day two participants will cover variance structures and be able to bring their own examples for discussion.

On 15th September we’ll be running a course on REML and multi-level models in GenStat. To take advantage of the early bird discount book before 31st July 2009. The course is designed to introduce the user to REML in GenStat, and provide the underlying knowledge and confidence to use it correctly and effectively. It highlights how the REML menus guide the user through very complicated analysis and explains the REML commands so that users can program any non-standard analyses.

The course covers 4 main sessions:

• Analysis of variance
• Meta analysis
• Spatial analysis
• Repeated measurements

For more details and to book email support or go to the training pages on our website.

Out and about with VSNi

We are delighted to be sponsoring two events in Italy – the ICORS 09 (International Conference on Robust Statsitics) in Parma from 14-19 June, and then later the EUCARPIA conference in Bergamo on 21-24 June.

This year we are looking forward to visiting old and meeting new friends when our CEO Stewart Andrews speaks on GenStat Discovery and the importance of agricultural research in Africa at the ISI 2009, in Durban (16-22nd August). Stewart will also lead a session on data analysis software for the developing world; more details to follow.

August is looking a busy time as we are also speaking and sponsoring the 14th Australasian Plant Breeding & 11th SABRAO Conference from 10-14th August at Cairns Convention Centre in Queensland.

From 2-4th September we’ll be in Dundee at the EUCARPIA 2009 XIV meeting of the Biometrics in Plant Breeding Section.

If you would like to meet directly with a VSNi attendee at these events please email Carey Biggs to make the arrangements.

We’re always updating the list of events we can support and sponsor – so please send us details of any events you are organising or involved in, and as we decide on more events for the future we’ll list them on our website.

The links between GenStat and NAG go back many years, but did you know that you can now access many of NAG’s numerical algorithms from within GenStat?

For example, to solve the polynomial in Figure 1 (poly1) for y = 0, set the NAG option name equal to c02agf, the algorithm for solving zeros of polynomials.

Bee Breeding Secrets.

There is something about bees that trigger happiness in people. Whether it’s the thought of honey dripping on toast or admiration for the organisation and industry of the little insects, you don’t have to be a bee keeper to like these pretty and industrious insects. Honey in itself is also highly regarded, be it for the taste, or the health-giving properties that are increasingly being assigned to it. But bees are also important for the pollination in nature and therefore agriculture.

But a bee is not just a bee; different strains and species of bee have different characteristics and behaviour patterns, so bee keepers and breeders need to be able to identify specific strains in order that they breed the most suitable bees for their requirements. There are obvious physical aspects that can be used such as size, colour or shape, but these methods are not foolproof and often hide specific strain differences. Another option is DNA testing, but this is an expensive and time consuming exercise, therefore a method first identified and introduced before the 1960’s can be used, known as morphometry.

Morphometry is a study of bee anatomy to establish race or strain characteristics, that are otherwise difficult to ascertain. The types of anatomy studied are the wings, tongue length, Tomentum width (width of the band of hair on the body segments) and hair length. The most common test and study is on the bee wings, looking at vein formation. Specifically bee breeders look at the “cubital index”, which is the ratio between two vein segments of the cubital cell in a bee’s wing, and the “discoidal shift”, which measures the position of the discoidal joint in relation to the perpendicular through the distal lower joint in the radial cell.

The concept of understanding which bee strain or race is important for bee breeding; as the more purer bee strains can have a better temper (this is not always true, as some inbred bees can be very cross), and therefore there is a less chance of being stung, likewise they seem to keep cleaner and more organised hives than their hybrid cousins. Beyond these “housekeeping” issues there is the bees actual performance, for example researchers have found that certain strains of bee respond quicker to Spring stimulation than others, this is important if the bees are being used for pollination, as it means some strains of bees are more active earlier than others.

The more a bee keeper or bee breeder knows about his bees the more sure he can be about how they will perform and behave. And it seems beewing morphometry can give an indication of the strain or subspecies of Apis mellifera.

The Dark European honey bee, or Apis mellifera mellifera, is defined by having a cubital index of no more than 1.9 and the discoidal shift angle of no more than 0 (although these are ideal standards and not always attainable). Results from the measurements from any hive or colony are displayed on a scattergram and bee keepers and breeders can see how pure their bees are. Jacob Kahn has taken this research further and used GenStat to analyse the measurements more in keeping with quantitative population genetics. He doubled the sample size of 30, normally used by honey bee morphometrists, to a sample size of 60 . 10 of these have had their measurements checked for goodness of fit of normal distribution, and the results showed that only one did not conform to normality. He then looked at any correlation between the cubital index and discoidal shift and found that 6 samples displayed correlation. Jacob hopes that further research and work on this will verify his findings, which would suggest that any correlation indicates genetically purer samples. Jacob suspects that there is a misconception, especially among amateurs, as to what is pure and what is a hybrid. “The term hybrid is generally misunderstood by beekeepers,” says Jacob, “We can talk here about two levels of hybridization: a cross between species can be termed hybridization, but a cross between two strains within a subspecies carrying different alleles of particular loci can also be said to be hybrids. and it is this aspect of population genetics which I am hoping to clarify with the help of GenStat.”

At the moment bee keepers and breeders are content with looking at simple scattergrams to check for bee purity, however Jacob’s work shows that there maybe even more details to discover about bee species or strains. Either way GenStat’s sound statistics has enabled Jacob to dig deeper into the data and initial analysis to find out more about the bees. This additional level of information should allow better definition of variants of Apis m. mellifera which in turn gives bee keepers and breeders greater information on their hives and colonies so they can breed better performing bees.

For more details on GenStat and its capability look at the VSNi website.

Likewise to integrate the polynomial between the values -4 and 3, set the option name to d01ahf, the algorithm for simple integration.

At present many of the algorithms with regards linear programming problems, differentiation, integration and ordinary differential equations have been included. Integral equations and partial differential equations will be included in the 12th edition.

Go to the Help menu, select Examples, then Commands and open the NAG topic to see the full list of routines available as well as examples for each one.

For more information on this, look at Simon Harding’s (VSNi software developer) talk at the Australasian GenStat User Conference.

Latest training courses

For the more advanced GenStat users who are looking for assistance with Analysis of Variance, book onto the Introduction to ANOVA on 9th to 10th July, in Apsley, Hertfordshire, UK. For more details and to book email support or go to the training pages on our website.

The aim of the course is to introduce ANOVA techniques and develop the fundamental knowledge and skills to use them correctly and effectively. The basic principles of experimental design will also be included to aid the effective planning of experiments and investigations.

By the end of the course users will be able to:

Out and about with VSNi

We’re always looking for events we can support and sponsor – so please send us details of any events you are organising or involved in, and as we decide on more events for the future we’ll list them on our website.

Elephants – their sheer size, incredible looks combined with intelligence, shyness and gentle nature are awe inspiring to most people; indeed is there a child in the world who is not wowed by them…so can you imagine a world without them?

It’s not news that elephants are endangered; for literally thousands of years ivory has driven hunters to kill these magnificent beasts. Combine this deliberate destruction with increased land use change and habitat transformation by private enterprise, international aid and government expansion across Africa and these magnificent beasts are still under threat even within the national parks and other protected areas set aside for them.

However, before we get too carried away with horrific idea that elephants may well become extinct; there is another side to this. Two separate taxa, or races, of elephants exist in Africa today: the savannah elephant, which is well known and has been studied and valued by the international tourist trade for decades, and the diminutive forest elephant, which until recently has remained in obscurity beneath the trees. In the Congo Basin, an area noted for being one of the great wilderness areas with the second largest rainforest on earth – it is home to an outstanding range of biological diversity; forest elephants have until recent decades thrived. These types of wildernesses have always been recognised for their high conservation value, being home to a wide variety of flora and fauna, and as such provide invaluable resources of timber, minerals and other natural resources. The Congo Basin is a typical case where the resources available are in high demand in rich, industrial nations and are also critical to the economies of poor nations. And it is at this point we in the Western developed world need to be very careful about conservation and conservation techniques; the international conservation efforts are aimed at managing and promoting sustainable natural resource exploitation and functional ecosystems. It is incredibly important that we recognise the needs of people in the developing world, and try to ensure they are able to exploit their natural resources in ways that do not fundamentally alter the ecology of the environment, upon which millions of rural people still depend.

The high value of resources in these wilderness areas means that it is only fair that Africans have an opportunity to exploit and benefit from them and are encouraged to do so legally, ethically and with an eye on their own local ecology.

Complications occur as industrial expansion pushes into the wildernesses to obtain these natural resources, an expansion that relies on a network of roads and rail infrastructure. It is this increase in roads that appears to be causing some of the biggest threats to the forest elephants. Illegal elephant killings tend to occur close to roads, since these areas are easily accessible, so the density of forest elephants in the protected areas is determined, not by the size of the area but by how many roads criss-cross through the wilderness.

Elephants are by their nature, shy and avoid human contact as much as possible, so how are they reacting to the increasing number of roads across their home ranges? Will they adopt a “siege” mentality and reduce their home range to avoid roads, or a “skirmish” strategy, where they will continue to range widely, irrespective of the number of roads?

I spoke with Stephen Blake of the Wildlife Conservation Society and Max Planck Institute of Ornithology who has recently headed up a study into this very issue. His team fitted a large sample of forest elephants in the Congo Basin with GPS telemetry collars, so that they could track their roaming behaviour. They collected data from 28 elephants located in conservation areas in the Congo, Central African Republic and Gabon.

Figure 1: Relationship between area of MCP home range and the area of road-less polygon; y axis – Home range size (kmsq), x axis roadless polygon size (kmsq).

Figure 2:Maximum linear displacement versus area of road-less polygon; y axis maximum linear distance moved (km), x axis roadless polygon size (kmsq).

“The data we collected covered the sex of the elephant, the site (the protected area in which the elephants were collared, the number of roads in the area, the number of days the elephants were collared,” explained Stephen, ” I initially analysed the result collected in GenStat, using linear regression for data exploration followed by fitting standard curves to the data (Figures 1 and 2). GenStat was vital in the research programme as I can trust the statistical procedures, I was able to talk directly with developers when I came up against any queries. I have found the Genstat support team to be extremely helpful, I usually get a response to a query within 24 hours and often much sooner. We could have gone much further with the analysis, but in order to understand the influence of roads on forest elephant ranging, the regression options in the Genstat menu showed us clear statistical patterns.”

Results indicated that the forest elephants routinely crossed protected roads, however only 1 elephant crossed an unprotected road, and of these one did so, as far away from the nearest village as she could, and her speed increased as she crossed the road.

“Our study showed that elephants seem to adopt a siege mentality with the encroaching roads”, said Stephen Blake, “and the issue with this is that over time the elephants will have less and less access to food, in quantity and variety, leading to food competition and aggression; both of which are likely to lead to a reduction in population.”

The main issue seems to be that elephants are risk averse, hence why they avoid roads where they can…so here we have a problem…central African states need the income earned from the natural resources found in their countries; but not only do we not want to see the elephants themselves to disappear, a change like that to any ecosystem is likely to have more wide ranging impacts.

“There are options for policies to overcome the issues, before it is too late,” says Stephen, “based on our research, we recommend that no new roads are built on existing forest elephant conservation areas, but to access the natural resources near these sites temporary roads should be built, so that once the resources are exhausted the area can easily return to natural wilderness. The other option is to try to reduce the elephants fear of roads, by preventing settlements on the roads, enforcing anti-poaching. These are of course expensive options, but without addressing this we face losing these beautiful creatures.”

More information on the Wildlife Conservation Society and its forest elephant project visit the Wildlife Conservation Society; and for more details on GenStat and its capability.

Find out more about the role GenStat plays in understanding elephants and their behaviour – this time in Kenya with Save the Elephants – as featured on the BBC, January 2009.

Technical tip – GGEbiplot procedure

A recent enquiry to VSNi’s forum asked about a procedure for GGEbiplot, based on GGE Biplot Analysis (2003) by W Yan and M S Kang (CRC Press). The procedure will be included in GenStat 12th edition, but several users have requested and received a sneak preview.

The procedure carries out a principal components analysis, to examine genotype (G) and genotype-by-environment interaction (GE) effects. Many different forms of plots are available to help determine how genotypes perform in certain environments. A simple scatter plot can have convex hulls added, which then can be used to divide the plot into sectors (Figure 1).

Alternatively, a comparison plot can plot many concentric circles, to ascertain the best performing genotypes in certain environments (Figure 2).

To obtain an advance copy, mail Support or register your interest on the Forum.

Out and about with VSNi

Look out for us at the World Potato Congress, from 22nd to the 25th March at Christchurch, New Zealand.

We’re always looking for events we can support and sponsor – so please send us details of any events you are organising or involved in, and as we decide on more events for the future we’ll list them on our website.

With all the complexities facing the world from climate and environment changes to how we feed the world, one thing is clear – we need research in order to plan effectively. And research needs well trained researchers; people who understand agricultural issues and concerns, and who know how to research effectively. GenStat is known as a key research tool for many agricultural and other bioscience researchers, but we were delighted to find GenStat also has an important role to play in the teaching of these areas.

A key user of GenStat is the IAMZ in Zaragoza, Spain, whose main aim is to train people in how to do research. The IAMZ stands (in Spanish) for the Mediterranean Agronomic Institute of Zaragoza, it is one of the 4 sites of the CIHEAM (International Centre for Advanced Mediterranean Agronomic Studies). The main purpose of the CIHEAM is “to develop cooperation between Mediterranean countries through postgraduate training and promotion of cooperative research in the field of agriculture and natural resources.” As a part of this the IAMZ develops Master programmes and advanced courses for professionals designed to update and further the training of researchers in agriculture and its related sciences.

Students come from all over the world to study for the Master programmes, some are straight from their first degree and wish to complete their education, and some are already at work and wish to update their knowledge and understanding of agricultural research. I spoke with Dr Ramzi Belkhodja from the IAMZ, who heads up the Master in plant breeding. The programme covers several areas, one of which being statistics and the use of statistics in plant breeding research. Dr Belkhodja and his colleagues recognised the need for anyone either in plant breeding research or planning on entering the field, to have a good understanding and grounding in statistical methods.

Currently the team teach their statistics course using GenStat. Given GenStat’s history in agricultural research it is perhaps no surprise that it is used as the phraseology and terminology reflects the language used in the biosciences. GenStat contains a huge range of statistical techniques; in fact you would be hard pushed to find a statistical test or routine not included in GenStat. However, it isn’t just GenStat’s inherent statistical strength or its history that makes it so useful to Dr Belkhodja and his colleagues.

GenStat’s straightforward Windows menu system means that the statistics is easy to teach and importantly easy for the students to pick up and understand, indeed Dr Belkhodja told me that the students are up and running with GenStat and statistical techniques within 3 teaching sessions. The self-explanatory menu system means that the statistical methods and concepts are easy to manage and understand. Combined with the speed and ease of importing any data from Excel (for example) into GenStat, and the lecturers at IAMZ can spend less time on the complicated syntax and more time on the analysis itself.

Given the students come from all over the world; GenStat also provides an added advantage for those coming from the developing world. When the students return, they can obtain a free copy of GenStat – as GenStat Discovery, to continue their research. So, in a world where “time is money”, students don’t need to learn a new package in their work environment; they can implement their learning and statistical understanding in a package they already know and trust.

More information on GenStat is available on the VSNi website and for more details on the work and courses of the IAMZ look here.

Product News

ASReml, now at version 2, offers free add-ons for supported ASReml licenses, for S and R. Details on how to download this can be found on the VSNi website. Users will need to install their existing asreml.lic license key in C:\program files\Common Files\VSN International\Licenses which will enable the R and S add on to work, once downloaded. If they do not have this directory then they will need to install the asreml.lic file in the Bin directory within R and or S.

Technical tip – User Support

Whether you are installing a new license key for the first time or a replacement license key because you have changed your PC, you may come across the below error message:

The reason for this error message is generally due to the following:

Sometimes neither of the above has occurred, which means that your PC may be generating a new MAC address each time you reboot, which keeps changing the Host ID every time you use the machine.

The only way that users can overcome the problem if this keeps occurring is by sending us their machine details. The way to display these is by opening up a command Prompt and typing in ipconfig/all and selecting enter. This will display their machine details which they then will need to send us, the Host name and Physical address, for us to send them a license key. This will then solve the problem of the Host ID error message appearing regularly.

Out and about with VSNi

Another successful Australian GenStat User Conference is underway; this year the agenda covers a variety of presentations from developers and users alike based on “Biometrics in Primary Industries and the Environment”. Thank you to the organisers; and all those attending who will help to make a successful event.

We’re always looking for events we can support and sponsor – so please send us details of any events you are organising or involved in, and as we decide on more events for the future we’ll list them on our website.

Latest training courses

The next training course is for Regression, nonlinear and generalized linear models in GenStat, scheduled for 5th and 6th March 2009 at The Paper Trail in Apsley, UK. To find out more or to book please look at the training page on our website.

As a part of our continued update and development of our courses, please let us know if you have any suggestions or topics for future training.

Don’t forget that we also offer specific on-site training if our current schedule doesn’t fit with your requirements. Please email the training team for prices and further information.

As a leading supplier to agricultural research it’s fascinating to watch the stir being created by articles on GM crops and the use of pesticides, especially with the proposed EU legislation. But it’s not necessarily clear which route governments and the industry should be taking…

From fears of poisoning the earth with misuse of pesticides versus the potential reduction in Europe’s food production and food price increases if some pesticides are banned, to the ethical and moral issues over genetically modifying crops at one end of the spectrum to the real need and ability to provide crops that can withstand pests, diseases, droughts or other climatic conditions. And now recent research suggests that some GM crops may even protect neighbouring non GM crops (American
Association for the Advancement of Science (2008 September 19) “Genetically Modified Crops Protect Neighbors from Pests”). Each side of the argument seems compelling, so what should we do?

One thing is clear, sound reliable research is required for sensible future planning. And that is something we at VSNi can help with. By providing outstanding data analysis software, specialising in the biosciences, throughout the world we can assist researchers in each area to come up with results and projections based on solid data analysis.

VSNi software is firmly rooted in the biosciences and agriculture. GenStat, originally developed by statisticians at Rothamsted Research in the UK, is still extensively used there today. Projects range from developing strategies to reduce the use of pesticides, improving production and quality of crops or by using the earth’s natural biodiversity to help improve production or crop yields and
reduce the need for pesticides.

Improving yields covers the simple definition of “more” to the quality of the crop and the ability of the crop to adapt to different environments. For example, researchers in a plant breeding department work on developing hybrids, which then need testing in large multi-year, multi-locations trials. The purpose of these trials is to select the hybrids which have the highest yield potential, and the best adaptation to particular environments. Here it’s clear that whilst crop yields can be
improved, there is very little purpose in doing so if they do not adapt well to their targeted environments. In these analyses GenStat’s REML has been particularly useful for spatial analysis of trials conducted on uneven soils and for meta-analysis of large trial datasets; this allows researchers to evaluate genetic gain and the general and specific combining ability. The crucial issue in this
instance is the ability of the chosen data analysis package to provide complex statistical approaches, in an easy to use way; i.e. experimental design, analysis of variance and mixed model approaches (REML), but in a menu system.

“The experimental design tools of GenStat are really excellent and user-friendly. I think that it is the only statistical program that offers complex statistical approaches that are extremely useful in agricultural research in a friendly, easy-to-use way.”Abelardo de la Vega, Advanta Semillas

Another aspect of increasing yields is how herbicides are used. Researchers in Latvia are testing for the effectiveness of different herbicides to control weeds and maintain crop safety. One such research project centred around surveys on flora in five arable fields in five regions of Latvia aims to assess the effects of crop rotation and crop husbandry practices. These projects are aimed at providing scientifically based information to help agronomists and farmers determine the need for
weed control.

GenStat’s REML techniques were key as the number of contributing factors varied and using this technique allows for the analysis of unbalanced datasets, and produces output equivalent to the analysis of variance. Researchers were able to include over sixty species of weed, and analyse the effect of the use of different herbicides, on different crops including the effect previous crops have on the
trials.

Another customer of VSNi’s is The Organic Research Centre at Elm Farm in the UK. The centre is designed to look at providing solutions that develop and support sustainable agriculture and land use. Based upon organic principles to ensure the environment’s health is as protected as possible, the research programs are conducted at the farm in Berkshire and across 25 other farms in the
UK. GenStat is primarily used in the wheat breeding trials, looking at how Composite Cross Populations (rather than specific varieties) perform under fluctuating environmental conditions.

“The great aspect of this new analysis is that we can use data from all 12 experiments, i.e. 3 years over 4 sites, to work out which of the varieties and populations are both yielding and reliable,” says Sarah Clarke, ORC, “we can also split the experiments into those that are organic and those that are non-organic, to see if the populations differ between systems.”

The aim is to produce wheat that performs well year after year in differing environments. It is therefore vital that the tools used by these researchers are reliable and provide sound statistical analysis techniques, so that the results from the trials are as trustworthy as possible.

ASReml is another such trusted product. Again born out of agricultural research requirements, this time in the analysis of 12 years of data from over 1000 wheat variety trials, today ASReml is used across the world by plant and animal breeders to help solve some of the big puzzles found in these areas. Its ability to handle the large datasets so often found in agricultural research is one of its main
strengths; indeed the National Variety Trials in Australia, handling data from around 600 trials across Australia in over 250 distinct geographical locations, rely on the results from their trials using ASReml to give reliable predictions on genetic value of different crops in different locations.

“ASReml is the package that helps farmers, breeders and crop variety evaluators obtain the most reliable predictions of genetic value for a range of crops grown in different environments; farmers can get the best information available about performance of varieties in their own location and make an informed decision,” says Professor Brian Cullis, Research
Leader for DPI Biometrics and leader of the SAGI (Statistics for the Australian Grains Industry) project.

Another key strength of ASReml is the accuracy, speed and flexibility of the complex two-stage linear models used in these trials.

But it isn’t just the big Western companies that benefit from our software. Since 2003 we have provided GenStat Discovery, (now at edition 3) to research and teaching institutes across the developing world. As Stewart Andrews, VSNi CEO says “there is no justification for poorer countries to not have access to high quality research tools. Their need for research based on solid,
reliable data analysis tools is as great, if not greater than the West’s; assistance to these countries should come in the form of providing opportunities for self help and self determination, not just aid or gifts.”

GenStat Discovery has become a key tool in the researchers kit bag; relied on by many agricultural institutes throughout the developing world; many of these researchers would not otherwise have access to data analysis software, nor would they be able to share their results and ideas with colleagues around the world.

“I have spent money on other software packages that fall short of my needs.” Ugwu Kenneth Okonkwo, University of Nigeria, Nsukka

For the CGIAR centres this is important, as they work closely with institutes in the developing world such as ILRI, ICRISAT or ICRAF, and need to be able to collaborate on research activities. It is the concept of trust that is so important in these types of trials and research projects; something that VSNi prides itself on. Our software is and has been trusted by
researchers for over 30 years. Trusted because of our history in agriculture – we understand the types of data and the analysis needs within this industry and trusted because of the sound statistical principles on which the software is based.

Technical tip – User Support

Felix Grant’s recent review of GenStat 11th edition mentioned many new features, including the ability to carry out partial or full canonical correspondence analysis (CCA) using a menu based system. Included on the menu is an option to plot a biplot of the results, showing how site or species scores are related to one (or two) of the environmental variables.

Another option could be to run the command CRTRIPLOT to see a plot of species scores, site scores and biplot scores of the environmental variables in a single plot. The user has many options including being able to plot the scores in a three-dimensional environment, add convex hulls and other graphics for grouped data and set the dimensions to be plotted. See the help file for a full list of options.

Read Felix’s full review of GenStat 11th edition, or download your trial copy of the 11th edition.

Out and about with VSNi

As we enter the last quarter of the year, the travel doesn’t stop for VSNi. A key event we are looking forward to is the Australasian GenStat User Conference, from 2-5th December at Marysville, Victoria. A packed agenda on Biometrics in Primary Industries and the Environment, and with many of our developers attending, it’s your chance to share ideas and quiz us face to face. More information and to register is available at their website.

Roger Payne once again attended the Joint Annual Meeting of the GSA, SSSA, ASA, CSSA, GCAGS, and HGS, this year, held in Houston on 5 – 9th October; this year speaking on “A Guide to Analysing Counts and Proportions in Complex Situations”, and specfically covering the methods of analysing counts and proportions from the experiments often found in agriculture and biology. It described the types of biological investigation that have led to the development of methods such as generalized linear
mixed models and hierarchical generalized linear models. His talk also showed how these methods extend the more familiar generalized liner models to allow you to take account of additional sources of error variation. For wrap up information on this event go to the event website.

If you are involved in organising an event which may be of interest to VSNi and our users please let us know.

Latest training courses

The next training course is for REML and multi-level models in GenStat, scheduled for 14th November at The Paper Trail in Apsley, UK. To find out more or to book please look at the training page on our website.

As a part of our continued update and development of our courses, please let us know if you have any suggestions or topics for future training.

Correction

In the last Newsletter we focussed on Dr Brian Miller, of the IOM, and his work in epidemiology; VSNi would like to make a correction to the report number listed, which should have read:IOM research report TM/07/06. Read the article again “http://www.vsni.co.uk/case-studies/the-institute-of-occupational-medicine/”>here.

As a part of VSNi’s on-going commitment to supporting educators across the world, we have launched GenStat for Teaching – a free version of GenStat for educators and students. In today’s world of tightening budgets and justification of spending it’s vital that those at the forefront of teaching and coaching the next generation of scientists can access the best tools for in statistical analysis. With GenStat for Teaching now available free to all students and teachers world-wide, there is no reason why students cannot be taught using the best.

GenStat is known across the globe for its world class statistical tools and data analysis capability; from linear modelling to ANOVA and REML, in fact all that teaching requires. GenStat does, after all, stand for General Statistics! Its history and pedigree provides its users with reliability, trust and security.

On top of this, GenStat is one of the easiest data analysis packages on the market, with a clear and straightforward menu system to guide users through their analyses, backed up with dialogue boxes providing hints and alerts. A Save Session facility allows GenStat to be tailored around teaching sessions, breaking down the steps to fit with the learning path. A snapshot of a session can be taken at any time, and restarted at a later date, with no need to run through all the analyses again. These two benefits alone make GenStat an ideal tool for teaching; couple this with extensive statistical tests included in the software and you have a powerful tool to aid the teaching of statistics and data analysis techniques.

Additionally all users have access to the resources on our website with training available and tutorials for regression and ANOVA.

Download your free copy of GenStat for Teaching here .

New edition dispatch changes

All supported users should by now have received their CD for the GenStat 11th edition, and we hope you are enjoying and benefitting from the new developments.

In an attempt to reduce our carbon footprint, we are hoping to limit the amount we physically dispatch. As such we would like to make future upgrades available as download only from our secure website, and no-longer send out CD’s where possible. Should you still require a CD to be sent please could you email us, otherwise we will email details of any new upgrade and send you the download link.

We hope you see this as a positive step, as we do.

Technical tip – User Support

For more support and assistance don’t forget our on-line user guides for both GenStat and ASReml. These guides have also been updated and revised to include help on GenStat Discovery and GenStat for Teaching. The guides have everything from getting started to detailed statistical analysis, including reviews on the underlying methodology, explaining the output and describing the GenStat commands. Look at the full list of available documentation on our website.

Out and about with VSNi

A list of where VSNi will be this year is on our website.

On 21st July 2008 an enthusiastic group of GenStat users and developers gathered at the Agri-Food & Biosciences Institute (AFBI) in Belfast for the 14th European GenStat Applied Statistics Conference.

The programme of 12 talks was split evenly between developments and applications, with topics ranging from forest fires and salmonella in Australia to sea birds in Scotland. More locally, Irish subjects involved tuberculosis in dairy cattle and sex ratio bias in gall midges. Other application areas included microarrays, microneurography, environmental assessments and the attraction of pollen beetles to oilseed rape flowers.

A broad range of statistical topics were covered, including generalized linear mixed models, hierarchical generalized nonlinear models and meta analysis, in addition to the more usual ANOVA, REML and regression analyses. New GenStat facilities were also described, with talks on survey analysis and the new facilities in the 11th Edition for canonical multivariate analyses, graphics environments and for using mathematical algorithms from the NAG Library.

We enjoyed excellent weather, and those staying on for the Advanced Linear Models workshop on the following day also enjoyed the excellent food, drink and ambiance of Belfast during the intervening evening.

We would like to thank AFBI for hosting the meeting, and especially the local organiser Alan Gordon (on the right in the picture below with Roger Payne).

On 5-9th October, Roger Payne is again speaking at the Joint Annual Meeting of the GSA, SSSA, ASA, CSSA, GCAGS and HGA in Houston, Texas. Roger will be presenting on A Guide to Analysing Counts and Proportions in Complex Situations, during a session on New Statistical Techniques for the Analysis of Agricultural Experiments. Roger’s talk will describe the types of biological investigation that have led to the development of methods such as generalized linear mixed models and hierarchical generalized linear models. It will show how these methods extend the more familiar generalized linear models to allow you to take account of additional sources of error variation, such as blocking in a field experiment, or parental effects in animal experiments.

If you are involved in organising an event which may be of interest to VSNi and our users please let us know by emailing us.

Latest training courses

We have an ASReml course on 24-25th September. This will be held by Dr Arthur Gilmour and will include an Introduction to Mixed Models and ASReml and on the second day Genetic Analyses for plants and animals. Participants are encouraged to bring their own examples, which can be sent direct to Dr Gilmour a month before the workshop for preparation. A similar workshop will also be taking place in Buenos Aires, Argentina 9-12th September to include the following areas:

An applied workshop on Mixed Models for Plant Improvement using ASReml and r is planned for 2-5th November 2008, at the University of Western Australia, Perth. The workshop will present advanced statistical methods for the design and analysis of data arising from plant improvement programmes. Topics will include the design and analysis of single/multi environment and single/multi-phase experiments. Methods will also be presented for the integration of molecular marker and pedigree information into the analysis (and design) of these experiments.

As a part of our continued update and development of our courses, please let us know if you have any suggestions or topics for future training.

GenStat in Epidemiology

GenStat is well known and highly regarded throughout the world in its historical core area of biosciences, and specifically in agricultural research. The breadth of statistical analysis covered is well documented on websites, review articles and the like. As are the importance of its pedigree, developed, tried, tested and used by agricultural statisticians; the birthplace of GenStat (Rothamsted Experimental Station) being also the birth place of modern statistics with the likes of Sir Ronald Fisher, Frank Yates and Professor John Nelder all giving GenStat a certain kudos in statistical circles and the bioscientist’s world.

More and more disciplines are relying on statistics to uncover trends, causes and to better understand relationships between various factors. One area that has always understood the importance of statistics is epidemiology – the study of factors affecting the health and well-being of populations. Epidemiology is a vital discipline underpinning evidence-based medicine, for identifying risk factors for diseases and health effects.

The epidemiologist’s work ranges from investigations into disease outbreaks, clusters and exposure-response relationships, which may include the development of regression models to test hypotheses and estimate risk coefficients. The epidemiologist’s work at the Institute of Occupational Medicine in Edinburgh is designed to provide reliable information about health effects and risks for occupational and environmental hazards, with a view to addressing public and industry concerns, and providing a scientific basis for policies to limit disease. So it’s easy to see how a statistical analysis system such as GenStat is a vital tool for these researchers.

The IOM has been using GenStat for several decades in their studies on public health in the UK. Originally set up as a charity in 1969 to research coalminers’ lung disease, to continue a research programme set up by the National Coal Board’s medical service, the charity has been independent since 1990, and now provides research, consultancy, laboratory and measurement services in relation to potential health problems caused by occupational and environmental exposures. All the research reports published by the IOM since 1969 are available for free download from the on-line library.

GenStat has been used in a variety of different analyses, including epidemiological or observational data, which typically requires a regression model of some kind (linear, GLM, GAM, LMM, GLMM etc). It is also used for analysing data sets from designed toxicology experiments and for analysing cause-specific mortality data in comparison with reference rates.

A recent study looked at mortality rates in a group of almost 18,000 coalworkers from 10 collieries recruited from the 1950s onwards and followed up until the present time, of whom about two thirds are now deceased. One aim of the study was to compare the observed rates from certain causes of death with the male population rates for those causes in the regions where the coal pits are located. The calculations produce standardised mortality ratios (SMR’s) and their standard errors, using standard epidemiological methods.

GenStat used each individual’s entry and death or censoring dates to amass the person-years in the cohort, tabulating them by region, year and age (using GenStat’s option for sequential tabulation). The SMR calculations then used GenStat’s table manipulation functions to organise observed deaths and calculate expected numbers, ratio of observed to expected (SMR) and its standard error, etc. The outputs included overall SMR, plus a breakdown on 5 year-time groups that show how the healthy worker effect exists in the early part of the follow-up. The study has also been able to show that the risks of developing certain respiratory diseases increase with increased exposure to dust. Detailed results are available in a final report.

The summary results of comparisons of mortality in cohort with external reference rates are shown below. The table shows, for chosen cause groups, numbers of deaths, age- year- and region-standardised mortality ratios (SMR) and 95% confidence interval.

The graph shows the Standardised Mortality Ratio (SMR) for all internal causes over the length of the follow-up period, with years grouped. The solid line is the SMR while the dashed lines represent the 95% confidence interval. The dotted line shows the SMR equal to 100%.

For any complex statistical calculations a software programme that is easy to use and reliable is crucial, but specifically in this instance GenStat’s table functions make the SMR calculations “beautifully simple to program.” (Dr Brian Miller).

The ability to understand the causes of health issues, what factors may lead to ill health or mortality in populations are of critical importance world-wide: so a sound, reliable data analysis system such as GenStat is vital to assist with analysis and help produce scientifically based recommendations and policies.

Our thanks to Dr Brian Miller of The Institute of Occupational Medicine for his help in producing this feature. More information on the IOM can be found here.

Images/Tables with permission from IOM research report TM/07/06.

We’re delighted to announce the release of the 11th Edition of GenStat, proving once again that GenStat is still at the forefront of statistical computing. As the choice for bioscientists around the world, GenStat 11 boasts increased statistical and mathematical modelling capabilities with the inclusion of the NAG routines.

New statistical facilities include canonical correspondence analysis, factor analysis and a new design algorithm to form optimal factorial and fractional designs. Existing facilities have been extended too, for example to provide multinomial regression, robust variogram estimates and least significant differences between REML means. There is a full list of the new features on our website.

Existing supported users can upgrade via our website now and a CD will be sent to the software site representative within 2-3 weeks. For information on upgrading to a supported license please email support .

Why not download and trial a free copy of GenStat 11th Edition.

New website launched

Phase 3 of the VSNi website is here.The driving aim behind this new phase is to be relevant content, we want to make the site an invaluable resource for GenStat users, and you can help. Take a look to see how you can get involved .

Technical tip – User Support

Trouble viewing your help files?

If you are running GenStat from a network server sometimes help pages may not display correctly within the GenStat help system. Instead of the help page an error message saying that the page cannot be found is displayed. This is a known Microsoft security problem and can be easily rectified by altering settings on the local client PC. The Microsoft knowledge base article no. 896054 provides a full description of the problem and a solution for how to configure the local PC to display the help pages.

Out and about with VSNi

Preparations for the 2008 European GenStat Applied Statistics Conference are well under way. The conference is being held at the Agri-Foods and Bioscience Institute (AFBI) in Belfast on Monday 21st July. The conference will focus on developments in the theory and practice of statistics in the context of GenStat. The programme covers a wide range of application areas as well as the development of new methodology. The key themes of the conference are:

• New statistical methodology in GenStat
• Statistical applications and consultancy
• Visualization and graphics

This event provides an excellent opportunity for statistics users with varied backgrounds to share experiences and to explore applications and advances in statistics. It will also bring current and potential users into direct contact with the developers of GenStat from VSN International, and enable them to influence future developments. The conference is followed immediately by a workshop on Advanced Linear Models, also to be held at AFBI on 22nd July 2008, the topics covered include:

• Extensions to generalized linear models such as GLMMs and HGLMs
• REML modelling of spatial and temporal variation
• New methods for design and sample-size calculation

To find out more about the events VSNi are attending in 2008 visit our website.

Agronomix are running an AGROBASE Generation II training course at the University of the Free State, Bloemfontaine, South Africa from 25-29th August. Click here to find out more about this event.

If you are involved in organising an event which may be of interest to VSNi and our users please let us know by emailing us.

Royal Statistical Society

On 3rd April the Royal Statistical Society’s Statistical Computing Section held a half-day meeting on Hierarchical Generalized Linear Models (a GenStat speciality!). John Nelder introduced the session with an overview of the theory.

Then our own Roger Payne showed their implementation (in GenStat), and explained his extension to Hierarchical Generalized Nonlinear Models.

He also ran through some examples to show their use in practice. Finally Mike Kenward of London School of Hygiene and Tropical Medicine talked about his collaboration with Youngjo Lee and colleagues on the use of hierarchical likelihood for missing data problems.

If you would like to know more, Roger and Youngjo will be presenting a short course on HGLMs at University College Dublin on 13th July, before the International Biometric Conference there.

Or you can look here to see Roger’s slides.

Latest training courses

Having invested in the best in data analysis, it’s vital that our users know how to make the most of the functionality in our products. With this in mind we are continually developing our training programme to cover both guidance on our software and statistical topics; these now include an Introduction to GenStat, Advanced Course for GenStat, ANOVA and Linear Modelling. In addition VSNi offer bespoke training to cover areas which our existing courses do not include. These courses are often designed around your actual data, helping to provide additional insight to the use of GenStat in your organisation and can be held either in our training rooms or onsite. One such example of this is a recent course held at Rothamsted for Rothamsted International fellows on GenStat Discovery:

“The course went very smoothly and the Fellows were all very appreciative and full of praise. Darren (Murray) did a really good job at getting them to practice tasks rather than just talk to them and this went down very well.”

As a part of the continued update and development of our courses, please let us know if you have any suggestions or topics for future training.

Planned training dates for later this year include an ASREML course on 23-24 September by Dr Arthur Gilmour, consisting of an Introduction to Mixed Models and ASReml, and on the second day Genetic Analyses in ASReml for plants and animals. Participants are encouraged to bring their own examples, which can be sent direct to Dr Gilmour a month before the workshop for preparation. A similar workshop will also be taking place in Buenos Aires, Argentina 9-12 September to include the following areas:

• Introduction to Mixed Models
• Introduction to ASReml
• Spatial Analysis Theory and Practise
• Start OWN analyses
• Factor Analytic Model
• Repeated Measures
• Multi Environment trials
• Basic QTL Theory and practise
• Completion of own analyses

Following the announcement of the opening of our Australian office in March, we’re delighted to announce the latest training courses being run in that region; details can be found on the website.

An applied workshop on Mixed Models for Plant Improvement using ASREML and R is planned for 2-5th November 2008, at the University of Western Australia, Perth. The workshop will present advanced statistical methods for the design and analysis of data arising from plant improvement programmes. Topics will include the design and analysis of single/multi environment and single/multi-phase experiments. Methods will also be presented for the integration of molecular marker and pedigree information into the analysis (and design) of these experiments.