covar {bqtl}R Documentation

Treat locus as covariate


Sometimes it is helps speed computations to linearize the likelihood or at least a part of it w.r.t. the locus allele values. Both 'Haley-Knott regression' and 'composite interval mapping' use this approach. covar provides a mechanism for creating formula objects that specify such linearizations.





The name of a locus (except for F2 designs, when it is the name of an effect like 'add.m.32') or any argument of the sort that locus allows. If x evaluates to a single value, then additional atomic elements may be included as with locus.


The function covar actually only returns x. The real work is done by a covar function that is hidden inside of bqtl, where the arguments are parsed as for locus. Each of the return values from locus is prefixed by "covar(" and suffixed by ")". If x is a name of a locus or effect, then paste("covar(",deparse(x),")") is returned. Later, when bqtl calls lapadj, terms like covar(PVV4.1) are recognized as requiring a linearization w.r.t. effect 'PVV4.1'.


a character string or vector


Charles C. Berry


HALEY, C. S. and S. A. KNOTT, 1992 A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity 69:315-324.

Knapp SJ, Bridges WC, and Birkes D. Mapping quantitative trait loci using molecular marker linkage maps. Theoretical and Applied Genetics 79: 583-592, 1990.

ZENG, Z.-B., 1994 Precision mapping of quantitative trait loci. Genetics 136:1457-1468

See Also

locus, add, dom, configs

[Package bqtl version 1.0-33 Index]