Genetic linkage analysisKyazma ® focuses on genetic linkage analysis in diploid experimental populations. JoinMap ® is Kyazma's software product for computing genetic linkage maps and MapQTL ® is its software for linkage analysis of quantitative traits. The two products have their origins in plant genetics. They are utilized broadly in genetic research of many plant species. In early versions of the software, their methods were extended for the analysis of single full-sib families of outbreeding species. This enhanced the genetic linkage analysis in, for example, many fruit tree and forest tree species. Because this family type is not limited to plant species alone, the software has found its way to the genetic research of many other species than plants, for example fish, amphibians and crustaceans. In addition to producing software, Kyazma teaches introductory courses on genetic linkage mapping and QTL analysis.
• Expected in April: stable early release of JoinMap ® version 5[24 January 2017]
Version number 5 of JoinMap is developed to be able to deal with large numbers of loci. The major technical improvements with respect to versions 4 and 4.1 are: (a) the change towards 64-bit software, (b) making the program use an embedded database system for storing all data and (c) parallelization of some algorithms. In addition, several aspects of the various algorithms are improved.
The change to 64-bit allows access to more system memory, which is useful for very large datasets. Using an embedded database system (SQLite) greatly improves the responsiveness of the user interface with large datasets; due to the 'embedded' property, the database system requires no special installation and usage instructions. Finally, parallelization increases the computational speed on systems with multi-core CPUs, of which now all available computional cores will be utilized.
With this version of JoinMap, the speed of the hard disk drive will now become a limiting factor in dealing with large datasets. For instance, a dataset of 50,000 loci in an F2 population will produce a table of ~1.2 billion records of pairwise data that must be stored, resulting in a database file of over 30 GB in size, which will require some time to write.
The final release of JoinMap v5 is still several months in the future. Because of the demand, a stable early edition is expected to be released in April. Following this first release, subsequent update releases in the months afterwards will get to include the remaining to be added functions.
Upgrade discounts will be available for owners of licenses for version 4 and version 4.1 (~30% and ~50%, respectively).
Please, note that the production of a reliable high resolution linkage map does require a population of sufficient size containing the necessary segregation information.
• Maintenance updates of JoinMap ® 4 and 4.1[31 July 2013]
Updates of JoinMap 4 and 4.1 were released with a useful new feature: a new Grouping node menu function 'Assign Identical Loci to Their Groups'. Please read more about the details in the Release notes. The updates are available for free for licensed users.
• Maintenance update of MapQTL ® 6[12 March 2013]
An update of MapQTL 6 was released that corrects an error in IM and MQM analyses on BCBxFy populations.
• Textbook hint:
Genetic Mapping in Experimental PopulationsAuthors: J.W. Van Ooijen & J. Jansen
Publisher: Cambridge University Press
Date: August 2013
This concise introduction to genetic mapping in diploid species teaches the theory behind map construction, explains the computations involved at each stage, and provides exercises and problem solving tips. It will enable graduate students and researchers in the life sciences to employ methods effectively and to achieve more reliable results.
• Practical coverage enables readers to effectively use the currently available software for achieving more reliable results
• Includes a description of eight of the most common map ordering algorithms
• Contains a detailed explanation on map construction in an outbreeding species full-sib family
• Written specifically for life science researchers; does not assume any background in mathematics or statistics