Robust linear regression based simple interval mapping for QTL analysis with backcross population

Multistage QTL mapping strategy in an advanced backcross cattle population

QTL Analysis using Bayesian Interval Mapping

R/qtlbim (www.qtlbim.org) provides a powerful suite of tools for model selection of the genetic architecture for traits influenced by multiple quantitative trait loci (QTL). The Markov chain Monte Carlo (MCMC) sampling approach draws samples from the more probable genetic architectures. Subsequent visualization and summary provides posterior estimates of the number and location of QTL, their ma...

Interval linear regression

‎In this paper‎, ‎we have studied the analysis an interval linear regression model for fuzzy data‎. ‎In section one‎, ‎we have introduced the concepts required in this thesis and then we illustrated linear regression fuzzy sets and some primary definitions‎. ‎In section two‎, ‎we have introduced various methods of interval linear regression analysis‎. ‎In section three‎, ‎we have implemented nu...

A comment on the simple regression method for interval mapping.

H ALEY and KNOTT (1992) developed a simple regression method for mapping quantitative trait loci (QTLs) using F2 populations. MARTINEZ and CURNOW (1992) considered the same approach using backcross populations. Studies that compare the regression method with that of LANDER and BOSTEIN’S (1989) maximum likelihood find very little difference between the two methods. The simple regression method o...

Robust Estimation in Linear Regression with Molticollinearity and Sparse Models

‎One of the factors affecting the statistical analysis of the data is the presence of outliers‎. ‎The methods which are not affected by the outliers are called robust methods‎. ‎Robust regression methods are robust estimation methods of regression model parameters in the presence of outliers‎. ‎Besides outliers‎, ‎the linear dependency of regressor variables‎, ‎which is called multicollinearity...