A Non Parametric Data Transformation Technique for Quantitative Genetic Analyses: The Rank Transformation
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Date
2017
Authors
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Journal ISSN
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Publisher
AMER INST PHYSICS
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
The aim of this study was to determine the effects of rank transformation on estimations of genetic parameters for non-normally distributed four simulated variables. X-1, X-2, X-3, X-4 have means and variances of 10, and the variables originated from Laplace distribution, Poisson distribution, Uniform distribution, Weibull distribution, respectively. After rank transformation, these values are 0 and 1 for each variable, respectively. Except the Poisson distribution all variables has been transformed into Gaussian distribution by rank transformation. It was determined that genetic information loss did not occur in any of the variables with normally distributed by rank transformation. It is possible to say that rank transformation can be used safely in quantitative genetic analyzes with regard to research results.
Description
2nd International Conference on Advances in Natural and Applied Sciences (ICANAS) -- APR 18-21, 2017 -- Antalya, TURKEY
Keywords
Multivariate analysis of variance, growth curve, biological meaningful parameters, mixed modeling
Journal or Series
INTERNATIONAL CONFERENCE ON ADVANCES IN NATURAL AND APPLIED SCIENCES (ICANAS 2017)
WoS Q Value
N/A
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N/A
Volume
1833
