plotSMApp {bigPint} | R Documentation

## 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)

[Package bigPint version 1.6.0 Index]