ordinationPlot {MatrixQCvis} | R Documentation

## Plot the coordinates from 'ordination' values

### Description

The function 'ordinationPlot' creates a dimension reduction plot. The function takes as input the 'tbl' object obtained from the 'ordination' function. The 'tbl' contains transformed values by one of the ordination methods.

### Usage

    ordinationPlot(
      tbl,
      se,
      highlight = c("none", colnames(colData(se))),
      explainedVar = NULL,
      x_coord,
      y_coord,
      height = 600
    )

### Arguments

`tbl` | 'tbl' as obtained by the function 'ordination'
`se` | 'SummarizedExperiment'
`highlight` | 'character', one of '"none"' or 'colnames(colData(se))'
`explainedVar` | NULL or named 'numeric', if 'numeric' 'explainedVar' contains the explained variance per principal component (names of 'explainedVar' corresponds to the principal components)
`x_coord` | 'character', column name of 'tbl' that stores x coordinates
`y_coord` | 'character', column name of 'tbl' that stores y coordinates
`height` | 'numeric', specifying the height of the plot (in pixels)

### Details

The function 'ordinationPlot' is a wrapper for a 'ggplot'/'ggplotly' expression.

### Value

'plotly'

### Author(s)

Thomas Naake

### Examples

    library(SummarizedExperiment)

    ## create se
    a <- matrix(1:100, nrow = 10, ncol = 10, byrow = TRUE,
                dimnames = list(1:10, paste("sample", 1:10)))
    set.seed(1)
    a <- a + rnorm(100)
    cD <- data.frame(name = colnames(a), type = c(rep("1", 5), rep("2", 5)))
    rD <- data.frame(spectra = rownames(a))
    se <- SummarizedExperiment(assay = a, rowData = rD, colData = cD)

    pca <- ordination(x = assay(se), type = "PCA", params = list())

    ordinationPlot(tbl = pca, se = se, highlight = "type",
        x_coord = "PC1", y_coord = "PC2")

[Package MatrixQCvis version 1.0.0 Index]