Literature DB >> 22189467

Computer simulation is an undervalued tool for genetic analysis: a historical view and presentation of SHIMSHON--a Web-based genetic simulation package.

David A Greenberg1.   

Abstract

Computer simulation methods are under-used tools in genetic analysis because simulation approaches have been portrayed as inferior to analytic methods. Even when simulation is used, its advantages are not fully exploited. Here, I present SHIMSHON, our package of genetic simulation programs that have been developed, tested, used for research, and used to generated data for Genetic Analysis Workshops (GAW). These simulation programs, now web-accessible, can be used by anyone to answer questions about designing and analyzing genetic disease studies for locus identification. This work has three foci: (1) the historical context of SHIMSHON's development, suggesting why simulation has not been more widely used so far. (2) Advantages of simulation: computer simulation helps us to understand how genetic analysis methods work. It has advantages for understanding disease inheritance and methods for gene searches. Furthermore, simulation methods can be used to answer fundamental questions that either cannot be answered by analytical approaches or cannot even be defined until the problems are identified and studied, using simulation. (3) I argue that, because simulation was not accepted, there was a failure to grasp the meaning of some simulation-based studies of linkage. This may have contributed to perceived weaknesses in linkage analysis; weaknesses that did not, in fact, exist.
Copyright © 2011 S. Karger AG, Basel.

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Mesh:

Year:  2011        PMID: 22189467      PMCID: PMC3726233          DOI: 10.1159/000330633

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  35 in total

1.  Summary of analyses of problem 2 simulated data for GAW11.

Authors:  D A Greenberg
Journal:  Genet Epidemiol       Date:  1999       Impact factor: 2.135

2.  Comparison of 'model-free' and 'model-based' linkage statistics in the presence of locus heterogeneity: single data set and multiple data set applications.

Authors:  J Huang; V J Vieland
Journal:  Hum Hered       Date:  2001       Impact factor: 0.444

3.  Merlin--rapid analysis of dense genetic maps using sparse gene flow trees.

Authors:  Gonçalo R Abecasis; Stacey S Cherny; William O Cookson; Lon R Cardon
Journal:  Nat Genet       Date:  2001-12-03       Impact factor: 38.330

4.  Determining trait locus position from multipoint analysis: accuracy and power of three different statistics.

Authors:  D A Greenberg; P C Abreu
Journal:  Genet Epidemiol       Date:  2001-12       Impact factor: 2.135

5.  Inferring mode of inheritance by comparison of lod scores.

Authors:  D A Greenberg
Journal:  Am J Med Genet       Date:  1989-12

6.  The effect of proband designation on segregation analysis.

Authors:  D A Greenberg
Journal:  Am J Hum Genet       Date:  1986-09       Impact factor: 11.025

7.  Analysis of family resemblance. IV. Operational characteristics of segregation analysis.

Authors:  C J MacLean; N E Morton; R Lew
Journal:  Am J Hum Genet       Date:  1975-05       Impact factor: 11.025

8.  Simulation studies of segregation analysis: application to two-locus models.

Authors:  D A Greenberg
Journal:  Am J Hum Genet       Date:  1984-01       Impact factor: 11.025

9.  The essence of linkage-based imprinting detection: comparing power, type 1 error, and the effects of confounders in two different analysis approaches.

Authors:  David A Greenberg; Maria Cristina Monti; Bjarke Feenstra; Junying Zhang; Susan E Hodge
Journal:  Ann Hum Genet       Date:  2010-03-31       Impact factor: 1.670

10.  Reproducibility and complications in gene searches: linkage on chromosome 6, heterogeneity, association, and maternal inheritance in juvenile myoclonic epilepsy.

Authors:  D A Greenberg; M Durner; M Keddache; S Shinnar; S R Resor; S L Moshe; D Rosenbaum; J Cohen; C Harden; H Kang; S Wallace; D Luciano; K Ballaban-Gil; L Tomasini; G Zhou; I Klotz; E Dicker
Journal:  Am J Hum Genet       Date:  2000-02       Impact factor: 11.025

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  5 in total

1.  Obtaining accurate p values from a dense SNP linkage scan.

Authors:  William C L Stewart; Ryan L Subaran
Journal:  Hum Hered       Date:  2012-10-03       Impact factor: 0.444

Review 2.  How should we be searching for genes for common epilepsy? A critique and a prescription.

Authors:  David A Greenberg; William C L Stewart
Journal:  Epilepsia       Date:  2012-09       Impact factor: 5.864

3.  A powerful test of independent assortment that determines genome-wide significance quickly and accurately.

Authors:  W C L Stewart; V R Hager
Journal:  Heredity (Edinb)       Date:  2016-06-01       Impact factor: 3.821

4.  Using Linkage Analysis to Detect Gene-Gene Interactions. 2. Improved Reliability and Extension to More-Complex Models.

Authors:  Susan E Hodge; Valerie R Hager; David A Greenberg
Journal:  PLoS One       Date:  2016-01-11       Impact factor: 3.240

5.  Using linkage analysis to detect gene-gene interaction by stratifying family data on known disease, or disease-associated, alleles.

Authors:  Barbara Corso; David A Greenberg
Journal:  PLoS One       Date:  2014-04-01       Impact factor: 3.240

  5 in total

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