RT Journal Article
SR Electronic
T1 Advances in Statistical Methods to Map Quantitative Trait Loci in Outbred Populations
JF Genetics
JO Genetics
FD Genetics Society of America
SP 1445
OP 1457
VO 147
IS 3
A1 Hoeschele, I.
A1 Uimari, P.
A1 Grignola, F. E.
A1 Zhang, Q.
A1 Gage, K. M.
YR 1997
UL http://www.genetics.org/content/147/3/1445.abstract
AB Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLS on a chromosome as an unknown.