EVOLUTION-MANAGER
Edit File: findDupMarkers.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: Find markers with identical genotype data</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 findDupMarkers {qtl}"><tr><td>findDupMarkers {qtl}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2>Find markers with identical genotype data</h2> <h3>Description</h3> <p>Identify sets of markers with identical genotype data. </p> <h3>Usage</h3> <pre> findDupMarkers(cross, chr, exact.only=TRUE, adjacent.only=FALSE) </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>chr</code></td> <td> <p>Optional vector specifying which chromosomes to consider. This may be a logical, numeric, or character string vector.</p> </td></tr> <tr valign="top"><td><code>exact.only</code></td> <td> <p>If TRUE, look only for markers that have matching genotypes and the same pattern of missing data; if FALSE, also look for cases where the observed genotypes at one marker match those at another, and where the first marker has missing genotype whenever the genotype for the second marker is missing.</p> </td></tr> <tr valign="top"><td><code>adjacent.only</code></td> <td> <p>If TRUE, look only for sets of markers that are adjacent to each other.</p> </td></tr> </table> <h3>Details</h3> <p>If <code>exact.only=TRUE</code>, we look only for groups of markers whose pattern of missing data and observed genotypes match exactly. One marker (chosen at random) is selected as the name of the group (in the output of the function). </p> <p>If <code>exact.only=FALSE</code>, we look also for markers whose observed genotypes are contained in the observed genotypes of another marker. We use a pair of nested loops, working from the markers with the most observed genotypes to the markers with the fewest observed genotypes. </p> <h3>Value</h3> <p>A list of marker names; each component is a set of markers whose genotypes match one other marker, and the name of the component is the name of the marker that they match.</p> <h3>Author(s)</h3> <p>Karl W Broman, <a href="mailto:broman@wisc.edu">broman@wisc.edu</a> </p> <h3>See Also</h3> <p><code><a href="drop.nullmarkers.html">drop.nullmarkers</a></code>, <code><a href="drop.markers.html">drop.markers</a></code>, <code><a href="pickMarkerSubset.html">pickMarkerSubset</a></code> </p> <h3>Examples</h3> <pre> data(hyper) hyper <- drop.nullmarkers(hyper) dupmar <- findDupMarkers(hyper) # finds 4 pairs dupmar.adjonly <- findDupMarkers(hyper, adjacent.only=TRUE) # finds 4 pairs dupmar.nexact <- findDupMarkers(hyper, exact.only=FALSE, adjacent.only=TRUE) # finds 6 pairs # one might consider dropping the extra markers totmar(hyper) # 173 markers hyper <- drop.markers(hyper, unlist(dupmar.adjonly)) totmar(hyper) # 169 markers </pre> <hr /><div style="text-align: center;">[Package <em>qtl</em> version 1.66 <a href="00Index.html">Index</a>]</div> </body></html>