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Marker Distribution (marker + distribution)
Selected AbstractsFamily-based association test for time-to-onset data with time-dependent differences between the hazard functionsGENETIC EPIDEMIOLOGY, Issue 2 2006Hongyu Jiang Abstract In genetic association studies, the differences between the hazard functions for the individual genotypes are often time-dependent. We address the non-proportional hazards data by using the weighted logrank approach by Fleming and Harrington [1981]:Commun Stat-Theor M 10:763,794. We introduce a weighted FBAT-Logrank whose weights are based on a non-parametric estimator for the genetic marker distribution function under the alternative hypothesis. We show that the computation of the marker distribution under the alternative does not bias the significance level of any subsequently computed FBAT-statistic. Hence, we use the estimated marker distribution to select the Fleming-Harrington weights so that the power of the weighted FBAT-Logrank test is maximized. In simulation studies and applications to an asthma study, we illustrate the practical relevance of the new methodology. In addition to power increases of 100% over the original FBAT-Logrank test, we also gain insight into the age at which a genotype exerts the greatest influence on disease risk. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. [source] Amplified fragment length polymorphism (AFLP) markers reveal that population structure of triploid dandelions (Taraxacum officinale) exhibits both clonality and recombinationMOLECULAR ECOLOGY, Issue 1 2000R. G. M. Van Der Hulst Abstract Highly variable amplified fragment length polymorphism (AFLP) fingerprints of triploid apomictic dandelions obtained from three localities in an area where diploids are lacking were analysed to infer the predominant modes of reproduction. The distribution of markers was analysed using character compatibility to infer whether many genotypes agree with a tree-like structure in the data set. The presence of incompatible character state combinations (matrix incompatibility; MI) was used as a measure of genetic exchange. The detection of overrepresented genotypes, of which some were widespread, confirmed asexual reproduction. Not all genotypes were overrepresented; approximately half of the genotypes in the three localities were found only once. Because, in terms of genotype frequencies, only a part of the genetic variation is described, more important aspects of the molecular data such as relationships between markers or genotypes have been studied. The analysis of character compatibility indicated a disagreement of the data with a clonal structure. Nearly all genotypes contributed to MI and this contribution varied considerably among genotypes in each sampled locality. A gradual decrease of matrix incompatibility upon successive deletion of genotypes showing the highest contribution to MI indicated that marker distribution of virtually all genotypes disagreed with a tree-like structure in the data. This result suggested that many genotypes were separated by one or more sexual generations. Consistent with this conclusion was the fact that markers that show a low probability of contributing to MI are different in every sampled locality, which is most easily explained as the result of recombination. Apparently, asexual reproduction has resulted in overrepresented, widespread genotypes but sexual recombination has also substantially contributed to genetic variation in the sites studied. [source] First-trimester serum marker distribution in singleton pregnancies conceived with assisted reproductionPRENATAL DIAGNOSIS, Issue 4 2010M. A. J. Engels Abstract Objective To evaluate marker distribution of free ,-human chorionic gonadotrophin (f,-hCG) and pregnancy-associated plasma protein-A (PAPP-A) in singleton pregnancies conceived by assisted reproduction techniques (ART). Methods In vitro fertilization (IVF) (n = 203) and intracytoplasmic sperm injection (ICSI) (n = 192) cases from a database of 14 645 first-trimester combined tests (overall study group) were selected and matched to 1164 controls for gestational age at sample date and maternal age. Results In the IVF group and ICSI group, lnPAPP-A was lower (IVF 6.74 vs 7.08; P = 0.0001; ICSI 6.59 vs 7.07; P = 0.0001) compared with the matched controls. Lnf,-hCG was lower in the IVF group (3.75 vs 3.90; P = 0.005) but not significantly different in the ICSI group (3.87 vs 3.93; P = 0.27). The computed correction factors for PAPP-A and f,-hCG were 1.42 and 1.17 for the IVF group and 1.56 and 1.05 for the ICSI group. The false-positive rate (FPR) in the IVF and ICSI group compared with the matched controls was higher (IVF 10.3% vs 8.6% and ICSI 10.9% vs 7.5%). In the overall age-biased [maternal age significantly lower compared with all ART and control groups] study group the FPR was 6.8%. Conclusion The increase in FPR in the ART groups can be explained by decreased PAPP-A values. Therefore, an adjustment in risk analysis for Down syndrome is suggested. Copyright © 2010 John Wiley & Sons, Ltd. [source] A linkage map of common carp (Cyprinus carpio) based on AFLP and microsatellite markersANIMAL GENETICS, Issue 2 2010L. Cheng Summary Common carp (Cyprinus carpio) is an important fish for aquaculture, but genomics of this species is still in its infancy. In this study, a linkage map of common carp based on Amplified Fragment Length Polymorphism (AFLP) and microsatellite (SSR) markers has been generated using gynogenetic haploids. Of 926 markers genotyped, 151 (149 AFLPs, two SSRs) were distorted and eliminated from the linkage analyses. A total of 699 AFLP and 20 microsatellite (SSR) markers were assigned to the map, which comprised 64 linkage groups and covered 5506.9 cM Kosambi, with an average interval distance of 7.66 cM Kosambi. The normality tests on interval map distances showed a non-normal marker distribution. Visual inspection of the map distance distribution histogram showed a cluster of interval map distances on the left side of the chart, which suggested the occurrence of AFLP marker clusters. On the other hand, the lack of an obvious cluster on the right side showed that there were a few big gaps which need more markers to bridge. The correlation analysis showed a highly significant relatedness between the length of linkage group and the number of markers, indicating that the AFLP markers in this map were randomly distributed among different linkage groups. This study is helpful for research into the common carp genome and for further studies of genetics and marker-assisted breeding in this species. [source] | ||||||||||