Open AccessJournal Article
Faster sequential genetic linkage computations.
TLDR
A variety of algorithmic improvements are described, which synthesize biological principles with computer science techniques, to effectively restructure the time-consuming computations in genetic linkage analysis.Abstract:
Linkage analysis using maximum-likelihood estimation is a powerful tool for locating genes. As available data sets have grown, the computation required for analysis has grown exponentially and become a significant impediment. Others have previously shown that parallel computation is applicable to linkage analysis and can yield order-of-magnitude improvements in speed. In this paper, we demonstrate that algorithmic modifications can also yield order-of-magnitude improvements, and sometimes much more. Using the software package LINKAGE, we describe a variety of algorithmic improvements that we have implemented, demonstrating both how these techniques are applied and their power. Experiments show that these improvements speed up the programs by an order of magnitude, on problems of moderate and large size. All improvements were made only in the combinatorial part of the code, without restoring to parallel computers. These improvements synthesize biological principles with computer science techniques, to effectively restructure the time-consuming computations in genetic linkage analysis.read more
Citations
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Merlin--rapid analysis of dense genetic maps using sparse gene flow trees.
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Parametric and nonparametric linkage analysis: a unified multipoint approach.
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Genetic Heterogeneity and Penetrance Analysis of the BRCA1 and BRCA2 Genes in Breast Cancer Families
D Ford,Douglas F. Easton,Michael R. Stratton,Steven A. Narod,David E. Goldgar,Peter Devilee,D. T. Bishop,Barbara L. Weber,Gilbert M. Lenoir,Jenny Chang-Claude,Hagay Sobol,M D Teare,Jeffery P. Struewing,Adalgeir Arason,Siegfried Scherneck,Julian Peto,Timothy R. Rebbeck,Patricia N. Tonin,Susan L. Neuhausen,Rosa B. Barkardottir,Jorunn E. Eyfjord,Henry T. Lynch,Bruce A.J. Ponder,Simon A. Gayther,J.M. Birch,Annika Lindblom,Dominique Stoppa-Lyonnet,Y. J. Bignon,Åke Borg,U Hamann,Neva E. Haites,Rodney J. Scott,Christine Maugard,Hans F. A. Vasen,Susanne Seitz,Lisa A. Cannon-Albright,Andrew Craig Schofield,Moraima Zelada-Hedman +37 more
TL;DR: The lifetime risk of breast cancer appears similar to the risk in BRCA1 carriers, but there was some suggestion of a lower risk in bRCA2 carriers <50 years of age.
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Hypogonadotropic hypogonadism due to loss of function of the KiSS1-derived peptide receptor GPR54
Nicolas de Roux,Emmanuelle Génin,Jean Claude Carel,Fumihiko Matsuda,Chaussain Jl,Edwin Milgrom +5 more
TL;DR: The present study shows that loss of function of GPR54 is a cause of IHH, and it identifies GPR 54 and possibly KiSS1 protein-derived peptide as playing a major and previously unsuspected role in the physiology of the gonadotropic axis.
References
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Journal ArticleDOI
Strategies for multilocus linkage analysis in humans.
TL;DR: The results show that considerable economy and efficiency can be brought to the mapping endeavor by resorting to appropriate strategies of detecting linkage and by constructing the human genetic map on a common reference panel of families.
Journal Article
Easy calculations of lod scores and genetic risks on small computers.
G M Lathrop,J M Lalouel +1 more
TL;DR: A computer program that calculates lod scores and genetic risks for a wide variety of both qualitative and quantitative genetic traits is discussed and an illustration is given of the joint use of a genetic marker, affection status, and quantitative information in counseling situations regarding Duchenne muscular dystrophy.
Journal Article
Estimation of the recombination fraction in human pedigrees: efficient computation of the likelihood for human linkage studies.
Journal ArticleDOI
Centre d'etude du polymorphisme humain (CEPH): collaborative genetic mapping of the human genome.
Jean Dausset,Howard M. Cann,Daniel Cohen,Mark Lathrop,Jean-Marc Lalouel,Jean-Marc Lalouel,Ray White,Ray White +7 more
Journal ArticleDOI
Extensions to Pedigree Analysis
TL;DR: In this paper, a computer method for calculating recurrence under the polygenic threshold model is explained, which permits accurate risk evaluation for pedigrees of arbitrary structure and large enough size.
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