### R/qtlcharts: Interactive graphics for QTL experiments

Karl W Broman

R/qtlcharts is an R package to create interactive charts for QTL data, for use with R/qtl. [website]

It is built with D3, using a set of reusable panels (also available separately, as d3panels).

For example charts, see the R/qtlcharts website.

#### Installation

Install R/qtlcharts from CRAN using

`install.packages("qtlcharts")`

Alternatively, install it from its GitHub repository. You first need to install the R/qtl, htmlwidgets, and devtools packages.

`install.packages(c("qtl", "htmlwidgets", "devtools"))`

Then install R/qtlcharts using the `install_github`

function in the devtools package.

```
library(devtools)
install_github("kbroman/qtlcharts")
```

#### Example use

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)
```

Also try `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)
```

Finally, try `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)
```

#### Licenses

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.