Association Strength (association + strength)

Distribution by Scientific Domains


Selected Abstracts


Asymptotic tests of association with multiple SNPs in linkage disequilibrium

GENETIC EPIDEMIOLOGY, Issue 6 2009
Wei Pan
Abstract We consider detecting associations between a trait and multiple single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD). To maximize the use of information contained in multiple SNPs while minimizing the cost of large degrees of freedom (DF) in testing multiple parameters, we first theoretically explore the sum test derived under a working assumption of a common association strength between the trait and each SNP, testing on the corresponding parameter with only one DF. Under the scenarios that the association strengths between the trait and the SNPs are close to each other (and in the same direction), as considered by Wang and Elston [Am. J. Hum. Genet. [2007] 80:353,360], we show with simulated data that the sum test was powerful as compared to several existing tests; otherwise, the sum test might have much reduced power. To overcome the limitation of the sum test, based on our theoretical analysis of the sum test, we propose five new tests that are closely related to each other and are shown to consistently perform similarly well across a wide range of scenarios. We point out the close connection of the proposed tests to the Goeman test. Furthermore, we derive the asymptotic distributions of the proposed tests so that P -values can be easily calculated, in contrast to the use of computationally demanding permutations or simulations for the Goeman test. A distinguishing feature of the five new tests is their use of a diagonal working covariance matrix, rather than a full covariance matrix as used in the usual Wald or score test. We recommend the routine use of two of the new tests, along with several other tests, to detect disease associations with multiple linked SNPs. Genet. Epidemiol. 33:497,507, 2009. 2009 Wiley-Liss, Inc. [source]


Evolutionary history shapes the association between developmental instability and population-level genetic variation in three-spined sticklebacks

JOURNAL OF EVOLUTIONARY BIOLOGY, Issue 8 2009
S. VAN DONGEN
Abstract Developmental instability (DI) is the sensitivity of a developing trait to random noise and can be measured by degrees of directionally random asymmetry [fluctuating asymmetry (FA)]. FA has been shown to increase with loss of genetic variation and inbreeding as measures of genetic stress, but associations vary among studies. Directional selection and evolutionary change of traits have been hypothesized to increase the average levels of FA of these traits and to increase the association strength between FA and population-level genetic variation. We test these two hypotheses in three-spined stickleback (Gasterosteus aculeatus L.) populations that recently colonized the freshwater habitat. Some traits, like lateral bone plates, length of the pelvic spine, frontal gill rakers and eye size, evolved in response to selection regimes during colonization. Other traits, like distal gill rakers and number of pelvic fin rays, did not show such phenotypic shifts. Contrary to a priori predictions, average FA did not systematically increase in traits that were under presumed directional selection, and the increases observed in a few traits were likely to be attributable to other factors. However, traits under directional selection did show a weak but significantly stronger negative association between FA and selectively neutral genetic variation at the population level compared with the traits that did not show an evolutionary change during colonization. These results support our second prediction, providing evidence that selection history can shape associations between DI and population-level genetic variation at neutral markers, which potentially reflect genetic stress. We argue that this might explain at least some of the observed heterogeneities in the patterns of asymmetry. [source]


On the relation between the association strength and other similarity measures

JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 7 2010
Leo Egghe
A graph in van Eck and Waltman [JASIST, 60(8), 2009, p. 1644], representing the relation between the association strength and the cosine, is partially explained as a sheaf of parabolas, each parabola being the functional relation between these similarity measures on the trajectories , a constant. Based on earlier obtained relations between cosine and other similarity measures (e.g., Jaccard index), we can prove new relations between the association strength and these other measures. [source]


Missed prime words within the attentional blink evoke an N400 semantic priming effect

PSYCHOPHYSIOLOGY, Issue 2 2001
Bettina Rolke
When subjects identified a target among distractors in a rapid serial visual presentation task, the detection of a subsequent target is impaired (attentional blink). By measuring event-related potentials (ERPs) we investigated if the processing of an unidentified prime word elicits the N400 semantic priming effect. Subjects (N= 12) had to identify three target words among distractors in a rapid serial visual presentation task. We varied the association strength between a prime (second target) and a probe (third target). The detection of the prime was impaired. Missed primes did not elicit a P300, indicating that they were not explicitly recognized. Despite this difference between recognized and missed primes, the N400 effect was present in both cases. This result suggests that automatic spread of activation (ASA) can be evoked by missed primes within the attentional blink. It furthermore demonstrates that ASA is sufficient to evoke the N400 effect. [source]


Asymptotic tests of association with multiple SNPs in linkage disequilibrium

GENETIC EPIDEMIOLOGY, Issue 6 2009
Wei Pan
Abstract We consider detecting associations between a trait and multiple single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD). To maximize the use of information contained in multiple SNPs while minimizing the cost of large degrees of freedom (DF) in testing multiple parameters, we first theoretically explore the sum test derived under a working assumption of a common association strength between the trait and each SNP, testing on the corresponding parameter with only one DF. Under the scenarios that the association strengths between the trait and the SNPs are close to each other (and in the same direction), as considered by Wang and Elston [Am. J. Hum. Genet. [2007] 80:353,360], we show with simulated data that the sum test was powerful as compared to several existing tests; otherwise, the sum test might have much reduced power. To overcome the limitation of the sum test, based on our theoretical analysis of the sum test, we propose five new tests that are closely related to each other and are shown to consistently perform similarly well across a wide range of scenarios. We point out the close connection of the proposed tests to the Goeman test. Furthermore, we derive the asymptotic distributions of the proposed tests so that P -values can be easily calculated, in contrast to the use of computationally demanding permutations or simulations for the Goeman test. A distinguishing feature of the five new tests is their use of a diagonal working covariance matrix, rather than a full covariance matrix as used in the usual Wald or score test. We recommend the routine use of two of the new tests, along with several other tests, to detect disease associations with multiple linked SNPs. Genet. Epidemiol. 33:497,507, 2009. 2009 Wiley-Liss, Inc. [source]