JZmapqtl - Multitrait mapping module


JZmapqtl [ -o output ] [ -i input ] [ -m mapfile ] [ -E eqtfile ] [ -S srfile ] [ -t trait ] [ -M Model ] [ -c chrom ] [ -d walk ] [ -n nbp ] [ -w window ] [ -I hypo ]


JZmapqtl uses (composite) interval mapping to map quantitative trait loci to a map of molecular markers and can analyze multiple traits simultaneously. It requires a molecular map that could be a random one produced by Rmap, or a real one in the same format as the output of Rmap. The sample could be a randomly generated one from Rcross or a real one in the same format as the output of Rcross. In addition, the program requires the results of the stepwise linear regression analysis of SRmapqtl for composite interval mapping.


See QTLcart(1) for more information on the global options -h for help, -A for automatic, -V for non-Verbose -W path for a working directory, -R file to specify a resource file, -e to specify the log file, -s to specify a seed for the random number generator and -X stem to specify a filename stem. The options below are specific to this program.

If you use this program without specifying any options, then you will get into a menu that allows you to set them interactively.

This requires a filename for output. JZmapqtl will append the file if it exists, and create a new file if it does not. If not used, then JZmapqtl will use qtlcart.zj, where the j indicates the trait analyzed and the zero'th file contains joint mapping.

This requires an input filename. This file must exist. It should be in the same format as the output of Rcross. The default file is qtlcart.cro.

JZmapqtl requires a genetic linkage map. This option requires the name of a file containing the map. It should be in the same format that Rmap outputs. The default file is qtlcart.map.

Use this to specify which trait JZmapqtl will analyze. If this number is greater than the number of traits, then all traits will be analyzed unless the trait name begins with a minus sign. If a negative number is given, then only traits beginning with a plus sign will be analyzed. The default is to analyze trait 1 only.

Allows the user to specify the name of the file containing results from Eqtl. JZmapqtl reads those results and uses the information to choose cofactors for some of the analysis methods.

Allows the user to specify the name of the file containing results from SRmapqtl. JZmapqtl reads the results and uses the information to choose cofactors for composite interval mapping model 6.

JZmapqtl assumes the specified model (see below) in the analysis. Model 3 is default.

The user can specify a specific chromosome for Zmapqtl to analyze. If zero, then all will be analyzed.

Zmapqtl walks along the chromosome at this rate. The default is to do an analysis every 2 centiMorgans along the chromosome.

Use this to limit the number of background parameters that JZmapqtl uses in composite interval mapping. This is used only with model 6. It tells JZmapqtl to use markers with rank no higher than specified with this option. Markers are ranked by SRmapqtl.out and only those markers for traits in the analysis with sufficient rank are used.

JZmapqtl blocks out a region of this many centiMorgans on either side of the markers flanking the test position when picking background markers. It is 10 by default and is only used in models 5 and 6. We refer to it as the window size.

JZmapqtl requires the user to specify which hypotheses to test. For backcrosses, there are two hypotheses numbered 1 and 0. Use 10 for backcrosses or a 14 to do GxE tests as well. For crosses in which there are three genotypic classes, there are hypotheses 0, 1, 2, and 3. Use 30, 31, 32 in that case or 34 to do GxE. These are explained in greater detail in the manual.


The input format of the molecular map should be the same as that of the output format from the program Rmap. The input format of the individual data should be the same as the output format of the program Rcross.


        % JZmapqtl

Calculates the likelihood ratio test statistics of the dataset in qtlcart.cro using the map in qtlcart.map.

        % nice JZmapqtl -A -V -i corn.cro -m corn.map -M 6 -t 3 -I 34 &

Calculates the likelihood ratio test statistics of the dataset in corn.cro using the map in corn.map. Model 6 is used for analysis. This file has two traits, so specifying trait 3 means that both traits are analyzed. Hypothesis 34 means that GxE interactions are also analyzed. The program is nice'd as a courtesy to other users, and run in the background so that the user can logout and relax.


Different parameters for the -M option allow for the analysis of the data assuming different models. See the Zmapqtl man page for explanations of models 3 and 6. These are the main analysis models available in JZmapqtl. You can also use model 9, which prepares an input file for use in MultiRegress. Mainly, it calculates the expected genotypes at the sites where it would have done analyses. The expected genotypes are calculated according to table 3.7 from the QTL Cartographer manual.


  1. Lander, E. S. and D. Botstein (1989) Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121, 185-199.

  2. Zeng, Zhao-Bang (1993) Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. Proc. Natl. Acad. Sci., USA 90, 10972-10976.

  3. Zeng, Zhao-Bang (1994) Precision mapping of quantitative trait loci. Genetics 136, 1457-1468.

  4. Jiang, Changjian and Zhao-Bang Zeng (1995) Multiple trait analysis of genetic mapping for quantitative trait loci. Genetics 140, 1111-1127.


Preplot ignores the output at present. So far, the program only does joint mapping and one form of GxE. Tests for close linkage, pleiotopic effects and other environmental effects will be added in the future.


You can select traits to include in the analysis in three ways:

Set the trait to analyze at 0, so that no traits except those beginning with a [+] (plus sign) are analyzed. You would need to edit the .cro file first to prepend a + to all traits you wanted in the analysis.

Set the trait to a value in the range [1-t] inclusive, where t is the number of traits in the .cro file. You will then get single trait results.

Set the trait to a value greater than t. Then all traits will be put in the analysis, unless they begin with a minus sign [-]. As in a. above, you would need to edit the .cro file to minus out some traits.

You need to set the hypothesis test for SFx and RFx crosses. The default of 10 is ok for crosses in which there are only two marker genotypic classes (BCx, RIx). To test GxE, use 14. For SFx and RFx, values of 30, 31 or 32 are valid, and a 34 invokes the GxE test. Recall that we have the following hypotheses:

  1. H0: a = d = 0

  2. H1: a !=0 , d = 0

  3. H2: a = 0 , d != 0

  4. H3: a != 0, d != 0

For 30, we test H3:H0. For 31, we test H3:H0, H3:H1 and H1:H0. For 32, we test H3:H0, H3:H2 and H2:H0. 30 is probably fine for initial scans. Hypothesis 34 does a test for H3:H0 as well as the GxE.

For Model 6, be sure to run SRmapqtl first. Once done, JZmapqtl will use all markers that are significant for any of the traits in the analysis. We need to work out a better way to select the cofactors. Presently we use any markers that are significant for any trait. Also, be sure to use FB regression (Model 2 in SRmapqtl), or else you will end up using all markers as cofactors.


Emap(1), Rmap(1), Rqtl(1), Rcross(1), Qstats(1), LRmapqtl(1), BTmapqtl(1), SRmapqtl(1), JZmapqtl(1), Eqtl(1), Prune(1), Preplot(1), MImapqtl(1), MultiRegress(1), Examples(1) SSupdate.pl(1), Prepraw.pl(1), EWThreshold.pl(1), GetMaxLR.pl(1), Permute.pl(1), Vert.pl(1), CWTupdate.pl(1), Ztrim.pl(1), SRcompare.pl(1), Ttransform.pl(1), TestExamples.pl(1), Model8.pl(1), Dobasics.pl(1), Bootstrap.pl(1)


In general, it is best to contact us via email (zeng@statgen.ncsu.edu)

        Christopher J. Basten, B. S. Weir and Z.-B. Zeng
        Bioinformatics Research Center, North Carolina State University
        1523 Partners II Building/840 Main Campus Drive
        Raleigh, NC 27695-7566     USA
        Phone: (919)515-1934

Please report all bugs via email to qtlcart-bug@statgen.ncsu.edu.

The QTL Cartographer web site ( http://statgen.ncsu.edu/qtlcart ) has links to the manual, man pages, ftp server and supplemental materials.

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