topRank {celda} | R Documentation

## Identify features with the highest influence on clustering.

### Description

topRank() can quickly identify the top 'n' rows for each column of a matrix. For example, this can be useful for identifying the top 'n' features per cell.

### Usage

    topRank(matrix, n = 25, margin = 2, threshold = 0, decreasing = TRUE)

### Arguments

`matrix` | Numeric matrix.
`n` | Integer. Maximum number of items above 'threshold' returned for each ranked row or column.
`margin` | Integer. Dimension of 'matrix' to rank, with 1 for rows, 2 for columns. Default 2.
`threshold` | Numeric. Only return ranked rows or columns in the matrix that are above this threshold. If NULL, then no threshold will be applied. Default 0.
`decreasing` | Logical. Specifies if the rank should be decreasing. Default TRUE.

### Value

List. The 'index' variable provides the top 'n' row (feature) indices contributing the most to each column (cell). The 'names' variable provides the rownames corresponding to these indexes.

### Examples

    data(sampleCells)
    topRanksPerCell <- topRank(sampleCells, n = 5)
    topFeatureNamesForCell <- topRanksPerCell$names[1]

[Package celda version 1.6.1 Index]