SRmapqtl uses stepwise regression to map quantitative trait loci to
a map of molecular markers. 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
This program should be run before
.Zmapqtl if you want to use composite interval mapping. The results will be used
to pick markers background control in composite interval mapping. The main result from using this program
is to rank the markers in terms of their influence on the trait of interest.
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 tells SRmapqtl
what type of analysis to perform. Use a 0 for forward stepwise (FS) regression, a 1 for
backward elimination (BE) and a 2 for forward regression with a backward elimination
step at the end (FB). It is probably best to use Model 2 here.
Requires a real number in the range 0.0 to 1.0.
This is a threshold p value for deleting markers in model 2 during the backward elimination
step. It should probably be the same as the previous option. The default is 0.05.
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
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