Abstract
Compared with other quantitative traits, count trait express discrete variation generally with countable values. It is necessary to consider an effective model incorporating both multiple genetic factors and environment factor in count trait mapping. In this article, we apply a multivariate Poisson model to fit the count traits of individuals and consider the multiple-interval mapping for QTLs by providing the joint estimating of QTL positions and effects. Simulation studies are conducted to validate the proposed algorithm.
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Sheng, X., Ma, W., Zhou, Y. (2014). Joint Estimation of QTL Positions and Effects in Multiple-Interval Mapping for Count Trait. In: Pan, L., Păun, G., Pérez-Jiménez, M.J., Song, T. (eds) Bio-Inspired Computing - Theories and Applications. Communications in Computer and Information Science, vol 472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45049-9_60
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DOI: https://doi.org/10.1007/978-3-662-45049-9_60
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