TY - JOUR
T1 - A general mixture model for mapping quantitative trait loci by using molecular markers
AU - Jansen, R.C.
N1 - Relation: http://www.rug.nl/gbb/
date_submitted:2007
Rights: University of Groningen, Groningen Biomolecular Sciences and Biotechnology Institute
PY - 1992
Y1 - 1992
N2 - In a segregating population a quantitative trait may be considered to follow a mixture of (normal) distributions, the mixing proportions being based on Mendelian segregation rules. A general and flexible mixture model is proposed for mapping quantitative trait loci (QTLs) by using molecular markers. A method is discribed to fit the model to data. The model makes it possible to (1) analyse non-normally distributed traits such as lifetimes, counts or percentages in addition to normally distributed traits, (2) reduce environmental variation by taking into account the effects of experimental design factors and interaction between genotype and environment, (3) reduce genotypic variation by taking into account the effects of two or more QTLs simultaneously, (4) carry out a (combined) analysis of different population types, (5) estimate recombination frequencies between markers or use known marker distances, (6) cope with missing marker observations, (7) use markers as covariables in detection and mapping of QTLs, and finally to (8) implement the mapping in standard statistical packages.
AB - In a segregating population a quantitative trait may be considered to follow a mixture of (normal) distributions, the mixing proportions being based on Mendelian segregation rules. A general and flexible mixture model is proposed for mapping quantitative trait loci (QTLs) by using molecular markers. A method is discribed to fit the model to data. The model makes it possible to (1) analyse non-normally distributed traits such as lifetimes, counts or percentages in addition to normally distributed traits, (2) reduce environmental variation by taking into account the effects of experimental design factors and interaction between genotype and environment, (3) reduce genotypic variation by taking into account the effects of two or more QTLs simultaneously, (4) carry out a (combined) analysis of different population types, (5) estimate recombination frequencies between markers or use known marker distances, (6) cope with missing marker observations, (7) use markers as covariables in detection and mapping of QTLs, and finally to (8) implement the mapping in standard statistical packages.
KW - Quantitative trait locus
KW - Molecular marker
KW - Mixture of distributions
KW - Genetic linkage map
KW - Generalised linear model
KW - EM-algorithm
U2 - 10.1007/BF00222867
DO - 10.1007/BF00222867
M3 - Article
VL - 85
JO - Theoretical and Applied Genetics
JF - Theoretical and Applied Genetics
IS - 2
ER -