Skip to main content

Advertisement

Log in

MapDisto: fast and efficient computation of genetic linkage maps

  • Short communication
  • Published:
Molecular Breeding Aims and scope Submit manuscript

Abstract

Several options are available to the scientific community for genetic map construction but few are simple to install and use. Available programs either lack intuitive interface or are commercial, expensive for many laboratories. We present MapDisto, a free, user-friendly and powerful program for constructing genetic maps from experimental segregating populations. MapDisto is freely available at http://mapdisto.free.fr/DL/. Current version: 1.7.5.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

References

  • Allard RW (1956) Formulas and tables to facilitate the calculation of recombination values in heredity. Hilgardia 24:235–278

    Google Scholar 

  • Bailey NTJ (1949) The estimation of linkage with differential viability, II and III. Heredity 3:220–228

    Article  Google Scholar 

  • Garavito A, Guyot R, Lozano J, Gavory F, Samain S, Panaud O, Tohme J, Ghesquiere A, Lorieux M (2010) A genetic model for the female sterility barrier between Asian and African cultivated rice species. Genetics 185(4):1425–1440

    Article  PubMed  CAS  Google Scholar 

  • Holloway J, Knapp SJ (1994) Gmendel 3.0 users guide. http://www.css.orst.edu/G-Mendel/Default.htm

  • Joehanes R, Nelson JC (2008) QGene 4.0, an extensible Java QTL-analysis platform. Bioinformatics 24:2788–2789

    Google Scholar 

  • Lander ES, Green P, Abrahamson J, Barlow A, Daly MJ, Lincoln SE, Newburg L (1987) Mapmaker: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1:174–181

    Article  PubMed  CAS  Google Scholar 

  • Lorieux M, Goffinet B, Perrier X, González de León D, Lanaud C (1995a) Maximum-likelihood models for mapping genetic markers showing segregation distortion. 1. Backcross populations. Theor Appl Genet 90:73–80

    Google Scholar 

  • Lorieux M, Perrier X, Goffinet B, Lanaud C, González de León D (1995b) Maximum-likelihood models for mapping genetic markers showing segregation distortion. 2. F2 populations. Theor Appl Genet 90:81–89

    Google Scholar 

  • Manly KF, Cudmore RH, Meer JM (2001) Map manager QTX, cross-platform software for genetic mapping. Mamm Genome 12(12):930–932

    Article  PubMed  CAS  Google Scholar 

  • Mester DI, Ronin YI, Minkov D, Nevo E, Korol AB (2003) Constructing large scale genetic maps using an evolutionary strategy algorithm. Genetics 165:2269–2282

    PubMed  CAS  Google Scholar 

  • Rebai A, Goffinet B, Mangin B (1995) Comparing power of different methods for QTL detection. Biometrics 51(1):87–99

    Article  PubMed  CAS  Google Scholar 

  • Schiex T, Gaspin C (1997) CARTHAGENE: constructing and joining maximum likelihood genetic maps. In: Proceedings of ISMB (1997), pp 258–267

  • Stam P (1993) Construction of integrated genetic-linkage maps by means of a new computer package—Joinmap. Plant J 3(5):739–744

    Article  CAS  Google Scholar 

  • Van Os H, Stam P, Visser RGF, Van Eck HJ (2005) RECORD: a novel method for ordering loci on a genetic linkage map. Theor Appl Genet 112(1):30–40. doi:10.1007/S00122-005-0097-X

    Article  PubMed  CAS  Google Scholar 

  • Wu YH, Bhat P, Close TJ, Lonardi S (2008) Efficient and accurate construction of genetic linkage maps from the minimum spanning tree of a graph. PLoS Genet 4(10):e1000212

    Article  PubMed  Google Scholar 

  • Wu JX, Jenkins JN, McCarty JC, Lou XY (2011) Comparisons of four approximation algorithms for large-scale linkage map construction. Theor Appl Genet 123(4):649–655. doi:10.1007/S00122-011-1614-8

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

My thanks go to Ian Mackay, Jean-François Rami, Stéphane Dussert and Denis Lespinasse for their kind help and advice.

Conflict of interest

None declared.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mathias Lorieux.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lorieux, M. MapDisto: fast and efficient computation of genetic linkage maps. Mol Breeding 30, 1231–1235 (2012). https://doi.org/10.1007/s11032-012-9706-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11032-012-9706-y

Keywords

Navigation