plotSMApp: Plot interactive scatterplot matrices

In lindsayrutter/bigPint: BIG multivariate data Plotted INTeractively

Plot interactive scatterplot matrices

Description

Plot interactive scatterplot matrices.

Usage

plotSMApp(data = data, dataSE = NULL, xbins = 10)

Arguments

data	DATA FRAME | Read counts
dataSE	SUMMARIZEDEXPERIMENT | Summarized experiment format that can be used in lieu of data; default NULL
xbins	INTEGER | Number of bins partitioning the range of the plot; default 10

Value

A Shiny application that shows a scatterplot matrix with hexagon bins and allows users to click on hexagon bins to determine how many genes they each contain. The user can download a file that contains the gene IDs that are located in the clicked hexagon bin.

Examples

# The first example uses data and dataMetrics objects as
# input. The last example creates the same plots now using the
# SummarizedExperiment (i.e. dataSE) object input.

# Example: Create interactive scatterplot matrix for first two treatment
# groups of data.

data(soybean_cn_sub)
soybean_cn_sub <- soybean_cn_sub[,1:7]
app <- plotSMApp(data=soybean_cn_sub)
if (interactive()) {
    shiny::runApp(app)
}

# Below are the same example, only now using the
# SummarizedExperiment (i.e. dataSE) object as input.

# Example: Create interactive scatterplot matrix for first two treatment
# groups of data. When working with the SummarizedExperiment data,
# we can summon the method convertSEPair() to subset our input data
# to only a pair of treatment groups.

## Not run: 
data(se_soybean_cn_sub)
se_soybean_cn_sub <- convertSEPair(se_soybean_cn_sub, "S1", "S2")
app <- plotSMApp(dataSE=se_soybean_cn_sub)
if (interactive()) {
    shiny::runApp(app)
}

## End(Not run)

lindsayrutter/bigPint documentation built on Nov. 13, 2023, 10:36 a.m.