Literature DB >> 16224189

SimPed: a simulation program to generate haplotype and genotype data for pedigree structures.

Suzanne M Leal1, Kai Yan, Bertram Müller-Myhsok.   

Abstract

With the widespread availability of SNP genotype data, there is great interest in analyzing pedigree haplotype data. Intermarker linkage disequilibrium for microsatellite markers is usually low due to their physical distance; however, for dense maps of SNP markers, there can be strong linkage disequilibrium between marker loci. Linkage analysis (parametric and nonparametric) and family-based association studies are currently being carried out using dense maps of SNP marker loci. Monte Carlo methods are often used for both linkage and association studies; however, to date there are no programs available which can generate haplotype and/or genotype data consisting of a large number of loci for pedigree structures. SimPed is a program that quickly generates haplotype and/or genotype data for pedigrees of virtually any size and complexity. Marker data either in linkage disequilibrium or equilibrium can be generated for greater than 20,000 diallelic or multiallelic marker loci. Haplotypes and/or genotypes are generated for pedigree structures using specified genetic map distances and haplotype and/or allele frequencies. The simulated data generated by SimPed is useful for a variety of purposes, including evaluating methods that estimate haplotype frequencies for pedigree data, evaluating type I error due to intermarker linkage disequilibrium and estimating empirical p values for linkage and family-based association studies. Copyright (c) 2005 S. Karger AG, Basel.

Mesh:

Year:  2005        PMID: 16224189      PMCID: PMC2909095          DOI: 10.1159/000088914

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


  17 in total

1.  Ignoring linkage disequilibrium among tightly linked markers induces false-positive evidence of linkage for affected sib pair analysis.

Authors:  Qiqing Huang; Sanjay Shete; Christopher I Amos
Journal:  Am J Hum Genet       Date:  2004-10-18       Impact factor: 11.025

2.  A combined linkage-physical map of the human genome.

Authors:  X Kong; K Murphy; T Raj; C He; P S White; T C Matise
Journal:  Am J Hum Genet       Date:  2004-10-14       Impact factor: 11.025

3.  Descent graphs in pedigree analysis: applications to haplotyping, location scores, and marker-sharing statistics.

Authors:  E Sobel; K Lange
Journal:  Am J Hum Genet       Date:  1996-06       Impact factor: 11.025

4.  Parametric and nonparametric linkage analysis: a unified multipoint approach.

Authors:  L Kruglyak; M J Daly; M P Reeve-Daly; E S Lander
Journal:  Am J Hum Genet       Date:  1996-06       Impact factor: 11.025

5.  Computer programs for multilocus haplotyping of general pedigrees.

Authors:  D E Weeks; E Sobel; J R O'Connell; K Lange
Journal:  Am J Hum Genet       Date:  1995-06       Impact factor: 11.025

6.  Chromosome-based method for rapid computer simulation in human genetic linkage analysis.

Authors:  J D Terwilliger; M Speer; J Ott
Journal:  Genet Epidemiol       Date:  1993       Impact factor: 2.135

7.  Faster sequential genetic linkage computations.

Authors:  R W Cottingham; R M Idury; A A Schäffer
Journal:  Am J Hum Genet       Date:  1993-07       Impact factor: 11.025

8.  Comprehensive human genetic maps: individual and sex-specific variation in recombination.

Authors:  K W Broman; J C Murray; V C Sheffield; R L White; J L Weber
Journal:  Am J Hum Genet       Date:  1998-09       Impact factor: 11.025

9.  Large-scale integration of human genetic and physical maps.

Authors:  Caroline M Nievergelt; Douglas W Smith; J Bradley Kohlenberg; Nicholas J Schork
Journal:  Genome Res       Date:  2004-05-12       Impact factor: 9.043

10.  Estimating the power of a proposed linkage study: a practical computer simulation approach.

Authors:  M Boehnke
Journal:  Am J Hum Genet       Date:  1986-10       Impact factor: 11.025

View more
  25 in total

1.  Robustness of linkage maps in natural populations: a simulation study.

Authors:  Jon Slate
Journal:  Proc Biol Sci       Date:  2008-03-22       Impact factor: 5.349

2.  Ignoring intermarker linkage disequilibrium induces false-positive evidence of linkage for consanguineous pedigrees when genotype data is missing for any pedigree member.

Authors:  Bingshan Li; Suzanne M Leal
Journal:  Hum Hered       Date:  2007-12-11       Impact factor: 0.444

3.  Deciphering the fine-structure of tribal admixture in the Bedouin population using genomic data.

Authors:  B Markus; I Alshafee; O S Birk
Journal:  Heredity (Edinb)       Date:  2013-10-02       Impact factor: 3.821

4.  Efficient haplotype inference from pedigrees with missing data using linear systems with disjoint-set data structures.

Authors:  Xin Li; Jing Li
Journal:  Comput Syst Bioinformatics Conf       Date:  2008

5.  Gene mapping in the wild with SNPs: guidelines and future directions.

Authors:  Jon Slate; Jake Gratten; Dario Beraldi; Jessica Stapley; Matt Hale; Josephine M Pemberton
Journal:  Genetica       Date:  2008-09-09       Impact factor: 1.082

6.  Potentials and limits of pairwise kinship analysis using autosomal short tandem repeat loci.

Authors:  Michael Nothnagel; Jörg Schmidtke; Michael Krawczak
Journal:  Int J Legal Med       Date:  2010-02-10       Impact factor: 2.686

7.  Coordinated conditional simulation with SLINK and SUP of many markers linked or associated to a trait in large pedigrees.

Authors:  Alejandro A Schäffer; Mathieu Lemire; Jürg Ott; G Mark Lathrop; Daniel E Weeks
Journal:  Hum Hered       Date:  2011-07-06       Impact factor: 0.444

8.  Integration of SNP genotyping confidence scores in IBD inference.

Authors:  Barak Markus; Ohad S Birk; Dan Geiger
Journal:  Bioinformatics       Date:  2011-08-23       Impact factor: 6.937

9.  GABRG1 and GABRA2 as independent predictors for alcoholism in two populations.

Authors:  Mary-Anne Enoch; Colin A Hodgkinson; Qiaoping Yuan; Bernard Albaugh; Matti Virkkunen; David Goldman
Journal:  Neuropsychopharmacology       Date:  2008-09-24       Impact factor: 7.853

10.  Detecting genome-wide haplotype polymorphism by combined use of Mendelian constraints and local population structure.

Authors:  Xin Li; Yixuan Chen; Jing Li
Journal:  Pac Symp Biocomput       Date:  2010
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.