Literature DB >> 19172084

Haplotyping methods for pedigrees.

Guimin Gao1, David B Allison, Ina Hoeschele.   

Abstract

Haplotypes provide valuable information in the study of diseases, complex traits, population histories, and evolutionary genetics. With the dramatic increase in the number of available single nucleotide polymorphism (SNP) markers, haplotype inference (haplotyping) using observed genotype data has become an important component of genetic studies in general and of statistical gene mapping in particular. Existing haplotyping methods include (1) population-based methods, (2) methods for pooled DNA samples, and (3) methods for family and pedigree data. The methods and computer programs for population data and pooled DNA samples were reviewed recently in the literature. As several authors noted, family and pedigree datasets are abundant and have unique advantages. In the past twenty years, many haplotyping methods for family and pedigree data have been developed. Therefore, in this contribution we review haplotyping methods and the corresponding computer programs suitable for family and pedigree data and discuss their applications and limitations. We explore the connections among these methods, and describe the challenges that remain to be addressed.

Entities:  

Mesh:

Year:  2009        PMID: 19172084      PMCID: PMC2692835          DOI: 10.1159/000194978

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


  61 in total

1.  Haplotyping in pedigrees via a genetic algorithm.

Authors:  P Tapadar; S Ghosh; P P Majumder
Journal:  Hum Hered       Date:  2000 Jan-Feb       Impact factor: 0.444

2.  Detection and integration of genotyping errors in statistical genetics.

Authors:  Eric Sobel; Jeanette C Papp; Kenneth Lange
Journal:  Am J Hum Genet       Date:  2002-01-08       Impact factor: 11.025

3.  Haplotypes vs single marker linkage disequilibrium tests: what do we gain?

Authors:  J Akey; L Jin; M Xiong
Journal:  Eur J Hum Genet       Date:  2001-04       Impact factor: 4.246

4.  Chromlook: an interactive program for error detection and mapping in reference linkage data.

Authors:  J L Haines
Journal:  Genomics       Date:  1992-10       Impact factor: 5.736

5.  Markov chain Monte Carlo segregation and linkage analysis for oligogenic models.

Authors:  S C Heath
Journal:  Am J Hum Genet       Date:  1997-09       Impact factor: 11.025

6.  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

7.  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

8.  A general model for the genetic analysis of pedigree data.

Authors:  R C Elston; J Stewart
Journal:  Hum Hered       Date:  1971       Impact factor: 0.444

9.  Sequential imputation for multilocus linkage analysis.

Authors:  M Irwin; N Cox; A Kong
Journal:  Proc Natl Acad Sci U S A       Date:  1994-11-22       Impact factor: 11.205

10.  The VITESSE algorithm for rapid exact multilocus linkage analysis via genotype set-recoding and fuzzy inheritance.

Authors:  J R O'Connell; D E Weeks
Journal:  Nat Genet       Date:  1995-12       Impact factor: 38.330

View more
  13 in total

1.  Estimation and visualization of identity-by-descent within pedigrees simplifies interpretation of complex trait analysis.

Authors:  Elizabeth E Marchani; Ellen M Wijsman
Journal:  Hum Hered       Date:  2011-12-23       Impact factor: 0.444

2.  GenomeLaser: fast and accurate haplotyping from pedigree genotypes.

Authors:  Wenzhi Li; Guoxing Fu; Weinian Rao; Wei Xu; Li Ma; Shiwen Guo; Qing Song
Journal:  Bioinformatics       Date:  2015-08-18       Impact factor: 6.937

Review 3.  Family-based designs for genome-wide association studies.

Authors:  Jurg Ott; Yoichiro Kamatani; Mark Lathrop
Journal:  Nat Rev Genet       Date:  2011-06-01       Impact factor: 53.242

4.  Curiosities of X chromosomal markers and haplotypes.

Authors:  Daniel Kling
Journal:  Int J Legal Med       Date:  2017-05-26       Impact factor: 2.686

Review 5.  The importance of phase information for human genomics.

Authors:  Ryan Tewhey; Vikas Bansal; Ali Torkamani; Eric J Topol; Nicholas J Schork
Journal:  Nat Rev Genet       Date:  2011-02-08       Impact factor: 53.242

Review 6.  Rediscovering the value of families for psychiatric genetics research.

Authors:  David C Glahn; Vishwajit L Nimgaonkar; Henriette Raventós; Javier Contreras; Andrew M McIntosh; Pippa A Thomson; Assen Jablensky; Nina S McCarthy; Jac C Charlesworth; Nicholas B Blackburn; Juan Manuel Peralta; Emma E M Knowles; Samuel R Mathias; Seth A Ament; Francis J McMahon; Ruben C Gur; Maja Bucan; Joanne E Curran; Laura Almasy; Raquel E Gur; John Blangero
Journal:  Mol Psychiatry       Date:  2018-06-28       Impact factor: 15.992

7.  Haplotype association analyses in resources of mixed structure using Monte Carlo testing.

Authors:  Ryan Abo; Jathine Wong; Alun Thomas; Nicola J Camp
Journal:  BMC Bioinformatics       Date:  2010-12-09       Impact factor: 3.169

8.  A haplotype inference algorithm for trios based on deterministic sampling.

Authors:  Alexandros Iliadis; John Watkinson; Dimitris Anastassiou; Xiaodong Wang
Journal:  BMC Genet       Date:  2010-08-23       Impact factor: 2.797

9.  Molecular characterization of a long range haplotype affecting protein yield and mastitis susceptibility in Norwegian Red cattle.

Authors:  Marte Sodeland; Harald Grove; Matthew Kent; Simon Taylor; Morten Svendsen; Ben J Hayes; Sigbjørn Lien
Journal:  BMC Genet       Date:  2011-08-11       Impact factor: 2.797

10.  Rapid haplotype inference for nuclear families.

Authors:  Amy L Williams; David E Housman; Martin C Rinard; David K Gifford
Journal:  Genome Biol       Date:  2010-10-29       Impact factor: 13.583

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.