TY - JOUR
T1 - Local Phylogeny Mapping of Quantitative Traits: Higher Accuracy and Better Ranking Than Single Marker Association in Genomewide Scans
AU - Besenbacher, Søren
AU - Mailund, Thomas
AU - Schierup, Mikkel H
PY - 2008
Y1 - 2008
N2 - We present a new method, termed QBlossoc, for linkage disequilibrium (LD) mapping of genetic variants underlying a quantitative trait. The method use principles similar to a previously published method, Blossoc, for LD mapping of case-control studies. The method builds local genealogies along the genome and looks for a significant clustering of quantitative trait values in these trees. We analyze its efficiency in terms of localization and ranking of true positives among a large number of negatives and compare the results with single marker approaches. Simulation results of markers at densities comparable to contemporary genotype chips show that QBlossoc is more accurate in localization of true positives as expected since it uses the additional information of LD between markers simultaneously. More importantly, however, for genome wide surveys, QBlossoc places regions with true positives higher on a ranked list than single marker approaches, again suggesting that a true signal displays itself more strongly in a set of adjacent markers than a spurious (false) signal. The method is both memory and CPU efficient. It has been tested on a real data set of height data for 5000 individuals measured at 317K markers and completed analysis within 5 CPU days.
AB - We present a new method, termed QBlossoc, for linkage disequilibrium (LD) mapping of genetic variants underlying a quantitative trait. The method use principles similar to a previously published method, Blossoc, for LD mapping of case-control studies. The method builds local genealogies along the genome and looks for a significant clustering of quantitative trait values in these trees. We analyze its efficiency in terms of localization and ranking of true positives among a large number of negatives and compare the results with single marker approaches. Simulation results of markers at densities comparable to contemporary genotype chips show that QBlossoc is more accurate in localization of true positives as expected since it uses the additional information of LD between markers simultaneously. More importantly, however, for genome wide surveys, QBlossoc places regions with true positives higher on a ranked list than single marker approaches, again suggesting that a true signal displays itself more strongly in a set of adjacent markers than a spurious (false) signal. The method is both memory and CPU efficient. It has been tested on a real data set of height data for 5000 individuals measured at 317K markers and completed analysis within 5 CPU days.
U2 - 10.1534/genetics.108.092643
DO - 10.1534/genetics.108.092643
M3 - Journal article
C2 - 19064712
SN - 0016-6731
JO - Genetics
JF - Genetics
ER -