Abstract
GENES is a software package used for data analysis and processing with different biometric models and is essential in genetic studies applied to plant and animal breeding. It allows parameter estimation to analyze biological phenomena and is fundamental for the decision-making process and predictions of success and viability of selection strategies. The program can be downloaded from the Internet (http://www.ufv.br/dbg/genes/genes.htm or http://www.ufv.br/dbg/biodata.htm) and is available in Portuguese, English and Spanish. Specific literature (http://www.livraria.ufv.br/) and a set of sample files are also provided, making GENES easy to use. The software is integrated into the programs MS Word, MS Excel and Paint, ensuring simplicity and effectiveness in data import and export of results, figures and data. It is also compatible with the free software R and Matlab, through the supply of useful scripts available for complementary analyses in different areas, including genome wide selection, prediction of breeding values and use of neural networks in genetic improvement.
Highlights
To breed genetically superior plants, the selected individuals must simultaneously unite a series of properties to produce a comparatively higher yield and to meet consumer demands
The development of software in the field of plant Genetics and Breeding is crucial due to the scarcity of such resources available to the scientific community. The availability of such tools would supply the increasing demand of users in numerous research institutions who deal with an enormous volume of data, requiring adequate ways of processing to accurately estimate statistical and biological parameters
The software GENES has 205 executable projects involving the modules of experimental statistics, biometrics, multivariate analysis, genetic diversity, and simulation matrices
Summary
To breed genetically superior plants, the selected individuals must simultaneously unite a series of properties to produce a comparatively higher yield and to meet consumer demands. Based on an adequate processing of these data, genetic parameters can be estimated and biological phenomena interpreted. The availability of such tools would supply the increasing demand of users in numerous research institutions who deal with an enormous volume of data, requiring adequate ways of processing to accurately estimate statistical and biological parameters.
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