kqtl: Suite of QTL Mapping Functions

Description Usage Arguments Examples

This function produces a probability heatmap plot, ordered by the phenotype. This gives an idea of what the regression procedure is actually being handed as inputs.

prob.heatmap(marker, p.value = NULL, genomecache, model = "additive",
  phenotype, phenotype.data, merge.by = "SUBJECT.NAME",
  founder.labels = NULL, founder.cex = 1, include.ramp = TRUE,
  include.marker = TRUE, alternative.phenotype.label = NULL)

`marker`	A marker that is contained in the genome cache. In general this should be a marker of interest, such as one beneath a putative QTL peak.
`p.value`	DEFAULT: NULL. Includes the observed p-value in the plot title.
`genomecache`	The path to the genome cache that contains founder haplotype information.
`model`	DEFAULT: "additive". If "additive", dosages are plotted. If "full", probabilities are plotted.
`phenotype`	The name of the phenotype column in the data set.
`phenotype.data`	A data.frame object that contains the phenotype information. Should also have a column that matches genomes in the genome cache.
`merge.by`	DEFAULT: "SUBJECT.NAME". Specifies the columns to merge phenotype and haplotype data.
`founder.labels`	DEFAULT: "NULL". If NULL, will default to the labels in the genome cache.
`founder.cex`	DEFAULT: 1. Defines the text size of the founder labels.
`include.ramp`	DEFAULT: TRUE. If TRUE, spectrum ramp for dosages or probabilities is included.
`include.marker`	DEFAULT: TRUE. If TRUE, the marker name is included in the title.
`alternative.phenotype.label`	DEFAULT: NULL. Allows for an alternative label for the phenotype.