scanonevar.meanperm

Executes permutations of the genotypes in the mean-effect part of scanonevar

Analysis of experimental crosses to identify genes
(called quantitative trait loci, QTLs) contributing to variation in
quantitative traits.
Broman et al. (2003) <doi:10.1093/bioinformatics/btg112>.

Karl Broman

Tools for Analyzing QTL Experiments

Hao Wu

Gary Churchill

Saunak Sen

Danny Arends

Robert Corty

Timothee Flutre

Ritsert Jansen

Pjotr Prins

Lars Ronnegard

Rohan Shah

Laura Shannon

Quoc Tran

Aaron Wolen

Brian Yandell

R Core Team 

scanonevar.meanperm function

<dl> <dt>cross</dt>
<dd>An object of class <code>cross</code>. See
 <code>read.cross</code> for details.</dd> <dt>pheno.col</dt>
<dd>Column number in the phenotype matrix which should be
 used as the phenotype. This must be a single value (integer index or
 phenotype name) or a numeric vector of
 phenotype values, in which case it must have the length equal to the number
 of individuals in the cross, and there must be either non-integers or
 values &lt; 1 or &gt; no. phenotypes; this last case may be useful for studying
 transformations.</dd> <dt>mean_covar</dt>
<dd>Numeric matrix with covariates affecting the mean.</dd> <dt>var_covar</dt>
<dd>Numeric matrix with covariates affecting the variances.</dd> <dt>maxit</dt>
<dd>Maximum number of iterations in the algorithm to fit the
 model at a given position.</dd> <dt>tol</dt>
<dd>Tolerance for convergence.</dd> <dt>n.mean.perm</dt>
<dd>Numeric vector of length one indicates the number of permutations to execute.</dd> <dt>seed</dt>
<dd>Numeric vector of length one indicates the random seed to start the permutations.</dd> <dt>quiet</dt>
<dd>If <code>FALSE</code>, print some information about the course
 of the calculations.</dd></dl>

Arguments

Permutation test for mean effect in scanonevar — scanonevar.meanperm

<dl>

 <dt>cross</dt>
<dd>An object of class <code>cross</code>. See
 <code>read.cross</code> for details.</dd>

 <dt>pheno.col</dt>
<dd>Column number in the phenotype matrix which should be
 used as the phenotype. This must be a single value (integer index or
 phenotype name) or a numeric vector of
 phenotype values, in which case it must have the length equal to the number
 of individuals in the cross, and there must be either non-integers or
 values &lt; 1 or &gt; no. phenotypes; this last case may be useful for studying
 transformations.</dd>

 <dt>mean_covar</dt>
<dd>Numeric matrix with covariates affecting the mean.</dd>

 <dt>var_covar</dt>
<dd>Numeric matrix with covariates affecting the variances.</dd>

 <dt>maxit</dt>
<dd>Maximum number of iterations in the algorithm to fit the
 model at a given position.</dd>

 <dt>tol</dt>
<dd>Tolerance for convergence.</dd>

 <dt>n.mean.perm</dt>
<dd>Numeric vector of length one indicates the number of permutations to execute.</dd>

 <dt>seed</dt>
<dd>Numeric vector of length one indicates the random seed to start the permutations.</dd>

 <dt>quiet</dt>
<dd>If <code>FALSE</code>, print some information about the course
 of the calculations.</dd>

</dl>

Permutation test for mean effect in scanonevar

scanonevar.meanperm: Permutation test for mean effect in scanonevar

Description

Usage

Value

Arguments