ArticleAmerican journal of human genetics1999
On a randomization procedure in linkage analysis.
Article in American journal of human genetics, 1999. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Weighting affected sib pairs by marker informativity.American journal of human genetics · 2005Article
- On a randomization procedure.American journal of human genetics · 2000Article
- Multilocus linkage tests based on affected relative pairs.American journal of human genetics · 2000Article
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3 authors.
Funding
Abstract
Although much theoretical work has been undertaken to derive thresholds for statistical significance in genetic linkage studies, real data are often complicated by many factors, such as missing individuals or uninformative markers, which make the validity of these theoretical results questionable. Many simulation-based methods have been proposed in the literature to determine empirically the statistical significance of the observed test statistics. However, these methods either are not generally applicable to complex pedigree structures or are too time-consuming. In this article, we propose a computationally efficient simulation procedure that is applicable to arbitrary pedigree structures. This procedure can be combined with statistical tests, to assess the statistical significance for genetic linkage between a locus and a qualitative or quantitative trait. Furthermore, the genomewide significance level can be appropriately controlled when many linked markers are studied in a genomewide scan. Simulated data and a diabetes data set are analyzed to demonstrate the usefulness of this novel simulation method.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.