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ARS Home » Southeast Area » Mississippi State, Mississippi » Crop Science Research Laboratory » Genetics and Sustainable Agriculture Research » Research » Publications at this Location » Publication #131546
Title: COMPUTER SOFTWARE FOR ESTIMATING VARIANCE AND COVARIANCE COMPONENTS, CORRELATION, AND PREDICTING GENETIC EFFECTS

Author
item WU, JIXIANG - MISSISSIPPI STATE UNIV
item ZHU, JUN - ZHEJIANG UNIVERSITY
item Jenkins, Johnie

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 1/15/2003
Publication Date: 8/1/2003
Citation: Wu, J., Zhu, J., Jenkins, J.N. 2003. Mixed linear model approaches for quantitative genetic models. In: Kang, M.S., editor. Handbook of Formulas and Software for Plant Geneticists and Breeders. Binghamton, NY: The Haworth Press, Inc. p. 171-180.

Interpretive Summary: Rapid analyses for genetic and plant breeding data and their interactions with the environment are not easily accomplished. Additionally, software and genetic models for analysis of maternally inherited traits, seed traits, or developmental traits are not readily available. This manuscript contains software and instructions for analyzing complicated or simple genetic models with balanced or unbalanced data. It should be useful to geneticists and breeders because of its flexibility and ease of use. The software is included with the book and was written by Jun Zhu in programming language C++.

Technical Abstract: Rapid analyses for genetic and plant breeding data and their interactions with the environment are not easily accomplished. This manuscript is a software package with illustrations on how to use the software and is published as a chapter in a book of software models for analyzing genetic and plant breeding data. This package has several features: (1) it can handle complicated genetic models for agronomic, seed, and developmental traits, (2) it can handle unbalanced data, (3) it uses jackknifing techniques to estimate standard errors, and (4) it has fast computations. Software for these models was written by Jun Zhu in programming language C++ and is included with the book.