EVOLUTION-MANAGER
Edit File: scanonevar.html
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><title>R: Genome scan for QTL affecting mean and/or variance</title> <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> <link rel="stylesheet" type="text/css" href="R.css" /> </head><body> <table width="100%" summary="page for scanonevar {qtl}"><tr><td>scanonevar {qtl}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2>Genome scan for QTL affecting mean and/or variance</h2> <h3>Description</h3> <p>Genome scan with a single QTL model for loci that can affect the variance as well as the mean.</p> <h3>Usage</h3> <pre> scanonevar(cross, pheno.col=1, mean_covar=NULL, var_covar=NULL, maxit=25, tol=1e-6, quiet=TRUE) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>cross</code></td> <td> <p>An object of class <code>cross</code>. See <code><a href="read.cross.html">read.cross</a></code> for details.</p> </td></tr> <tr valign="top"><td><code>pheno.col</code></td> <td> <p>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 < 1 or > no. phenotypes; this last case may be useful for studying transformations.</p> </td></tr> <tr valign="top"><td><code>mean_covar</code></td> <td> <p>Numeric matrix with covariates affecting the mean.</p> </td></tr> <tr valign="top"><td><code>var_covar</code></td> <td> <p>Numeric matrix with covariates affecting the variances.</p> </td></tr> <tr valign="top"><td><code>maxit</code></td> <td> <p>Maximum number of iterations in the algorithm to fit the model at a given position.</p> </td></tr> <tr valign="top"><td><code>tol</code></td> <td> <p>Tolerance for convergence.</p> </td></tr> <tr valign="top"><td><code>quiet</code></td> <td> <p>If <code>FALSE</code>, print some information about the course of the calculations.</p> </td></tr> </table> <h3>Value</h3> <p>A data frame (with class <code>"scanone"</code>, in the form output by <code><a href="scanone.html">scanone</a></code>), with four columns: chromosome, position, the -log P-value for the mean effect, and the -log P-value for the effect on the variance. The result is given class <code>"scanone"</code> </p> <h3>Author(s)</h3> <p>Lars Ronnegard and Karl Broman</p> <h3>References</h3> <p>Ronnegard, L. and Valdar W. (2011) Detecting major genetic loci controlling phenotypic variability in experimental crosses. Genetics 188:435-447 </p> <p>Ronnegard, L. and Valdar W. (2012) Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability. BMC Genetics 13:63 </p> <h3>See Also</h3> <p><code><a href="scanone.html">scanone</a></code>, <code><a href="summary.scanone.html">summary.scanone</a></code>, <code><a href="calc.genoprob.html">calc.genoprob</a></code>, <code><a href="summary.scanoneperm.html">summary.scanoneperm</a></code> </p> <h3>Examples</h3> <pre> data(fake.bc) fake.bc <- calc.genoprob(fake.bc, step=2.5) out <- scanonevar(fake.bc) color <- c("slateblue", "violetred") plot(out, lod=1:2, col=color, bandcol="gray80") legend("topright", lwd=2, c("mean", "variance"), col=color) # use format="allpeaks" to get summary for each of mean and variance # also consider format="tabByCol" or format="tabByChr" summary(out, format="allpeaks") # with sex and age as covariates covar <- fake.bc$pheno[,c("sex", "age")] out.cov <- scanonevar(fake.bc, mean_covar=covar, var_covar=covar) </pre> <hr /><div style="text-align: center;">[Package <em>qtl</em> version 1.66 <a href="00Index.html">Index</a>]</div> </body></html>