cross.denovo: Create a de novo genetic map from a population object.

In pheno2geno: High-Throughput Generation of Genetic Markers and Maps from Molecular Phenotypes for Crosses Between Inbred Strains

Description

Create a de novo genetic map from offspring phenotype data stored in a population object

Usage

cross.denovo(population, n.chr, map=c("none", "genetic", "physical"), 
  comparisonMethod = c(sumMajorityCorrelation, majorityCorrelation, meanCorrelation,
  majorityOfMarkers), assignFunction=c(assignMaximumNoConflicts, assignMaximum),
  reOrder=TRUE, use.orderMarkers=FALSE, verbose=FALSE, debugMode=0, ...)

Arguments

population	An object of class population. See create.population for details.
n.chr	Number of chromosomes expected on the map.
map	Which map ( from ones stored in population$maps) should be used for assigning chromosomes on the created map. If none is selected - assigning is not performed.
comparisonMethod	Method used to compare chromosomes from the new map to the original ones while assigning: sumMajorityCorrelation - For each chromosome in cross for every marker checks the marker it is having highest correlation with. Checks on which chromosome this marker is placed in old map. For each of new chromosomes one or more of chromosomes from old map will be represented. Function sums correlations for each pair of those and for every new chromosomes assigns old chromosome with highest cumulative cor. majorityCorrelation - For each chromosome in cross for every marker checks the marker it is having highest correlation with. Checks on which chromosome this marker is placed in old map. For each of new chromosomee, old chromosome with most markers with high correlation is assigned. meanCorrelation - Assigning chromosome from new map to old ones using sum of the mean correlation between their markers. majorityOfMarkers - For each chromosome in the cross object (either created inside the function or provided by user) chromosome from original map, where most markers from new chromosome are is assigned.
assignFunction	function used to assign chromosomes on the created map, in both cases for every chromosome from the new map, original chromosome with maximal score is assigned, but if one of the original chromosomes is assigned to more then one of new ones: assignMaximumNoConflictsadditional step is performed to make sure each of the original chromosomes is used only once assignMaximumthose two are being merged
reOrder	if TRUE, cross object is returned, FALSE - vector showing how chromosomes should be assigned
use.orderMarkers	should markers on the newly created map be ordered using R/qtl orderMarkers funtion
verbose	be verbose
debugMode	1: Print our checks, 2: print additional time information
...	parameters passed directly to the formLinkageGroups function

Details

cross.denovo function creates new genetic map using genotypes simulated by generate.biomarkers function. Then it uses information provided by user to assign number to newly created chromosomes.

Value

When reordering this will produce an object of class cross, otherwise (reOrder=FALSE) a chromosomes assignment vector (See assignChrToMarkers ) is produced which can be used to manual reorder the markers.

Author(s)

Konrad Zych [e-mail], Danny Arends [e-mail] Maintainer: Konrad Zych [e-mail]

See Also

• reorganizeMarkersWithin - Apply new ordering on the cross object usign ordering vector.

• assignChrToMarkers - Create ordering vector from chromosome assignment vector.

• cross.saturate - Saturate existing map.

• reduceChromosomesNumber - Number of routines to reduce number of chromosomes of cross object.

• generate.biomarkers - Creating genotype markers out of gene expression data.

Examples

	data(testPopulation)
	cross <- cross.denovo(testPopulation,n.chr=5,verbose=TRUE,map="genetic",
  comparisonMethod=sumMajorityCorrelation, use.orderMarkers=FALSE)

pheno2geno documentation built on May 2, 2019, 6:35 a.m.