Following is a fuller description of the Quercus program set:

Shaw (1987; Evolution 41: 812-826 and 1991; Evolution 45: 143-151)
and others have presented a maximum-likelihood approach to quantitative
genetic analysis.  This approach provides estimates of fixed effects 
and components of variance for a polygenic model fitted to data on 
phenotypic values for individuals whose genetic relationships are 
known.  The current programs have the capability of handling multivariate 
data of diverse genetic designs, spanning the range of standard mating 
schemes (offspring-parent, nested, factorial, diallel, regardless of 
balance).  The programs permit tests of the hypothesis that any 
particular component (or set of components) of variance or covariance 
equals zero.  In addition, there is a program that tests the hypothesis 
that two G matrices are the same.  Efficiency of the current programs 
(i.e. requirements of computer memory and time) has been greatly improved 
over that of the previous versions.  Data input has been made more 
flexible and diagnostics have been implemented in order to avoid 
and/or clarify runtime errors.  The programs are written in standard 
Pascal and are distributed as source code.  They have been run successfully 
on Sun and DEC workstations, VAX and IBM mainframes, and a Cray Y-1 
supercomputer.  This work has been supported by grants from NIH (GM09664-02) and NSF (BSR 8817756, BSR 8905808, and DIR 9112842).

If you obtain files from the quercus set, please send your name and
address, including e-mail address, to notify us.

Ruth G. Shaw
Department of Ecology, Evolution, and Behavior
University of Minnesota
St. Paul, MN 55108
shaw@superb.ecology.umn.edu, rshaw@ecology.umn.edu, rshaw@vx.cis.umn.edu

Frank H. Shaw
Institute for Mathematics and Its Applications
University of Minnesota
Minneapolis, MN 55455
fshaw@ima.umn.edu, fshaw@superb.ecology.umn.edu