For example charts, see the R/qtlcharts website.
Install R/qtlcharts from CRAN using
Then install R/qtlcharts using the
install_github function in
Try the following example, which creates an interactive chart with LOD curves linked to estimated QTL effects.
library(qtl) library(qtlcharts) data(hyper) hyper <- calc.genoprob(hyper, step=1) out <- scanone(hyper) iplotScanone(out, hyper)
iplotCorr, an image of a correlation matrix (for the
gene expression of a set of 100 genes) linked to the underlying
scatterplots, with the points in the scatterplot colored by their
genotype at a QTL:
library(qtlcharts) data(geneExpr) iplotCorr(geneExpr$expr, geneExpr$genotype)
iboxplot, a plot of the quantiles of many
distributions, linked to the underlying histograms.
library(qtlcharts) # simulate some data n.ind <- 500 n.gene <- 10000 expr <- matrix(rnorm(n.ind * n.gene, (1:n.ind)/n.ind*3), ncol=n.gene) dimnames(expr) <- list(paste0("ind", 1:n.ind), paste0("gene", 1:n.gene)) # generate the plot iboxplot(expr)
The R/qtlcharts package as a whole is distributed under GPL-3 (GNU General Public License version 3).
R/qtlcharts incorporates the following other open source software components, which have their own license agreements.
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