kersplatSimCellMeans {splatter} | R Documentation

## Simulate Kersplat cell means

### Description

Simulate endogenous counts for each cell in a Kersplat simulation

### Usage

    kersplatSimCellMeans(sim, params, verbose)

### Arguments

`sim` | SingleCellExperiment containing simulation.
`params` | KersplatParams object with simulation parameters.
`verbose` | logical. Whether to print progress messages

### Details

Cells are first assigned to a path and a step along that path. This is controlled by the `cells.design` parameter which is a `data.frame` with the columns "Path", "Probability", "Alpha" and "Beta". The Path field is an ID for each path and the Probability field is the probability that a cell will come from that path (must sum to 1). The Alpha and Beta parameters control the density of cells along the path. After they are assigned to paths the step for each cell is sampled from a Beta distribution with parameters shape1 equals Alpha and shape2 equals beta. This approach is very flexible and allows almost any distribution of cells along a path. The distribution can be viewed using `hist(rbeta(10000, Alpha, Beta), breaks = 100)`. Some useful combinations of parameters are:

`Alpha = 1`, `Beta = 1`

  Uniform distribution along the path

`Alpha = 0`, `Beta = 1`

  All cells at the start of the path.

`Alpha = 1`, `Beta = 0`

  All cells at the end of the path.

`Alpha = 0`, `Beta = 0`

  Cells only at each end of the path.

`Alpha = 1`, `Beta = 2`

  Linear skew towards the start of the path

`Alpha = 0.5`, `Beta = 1`

  Curved skew towards the start of the path

`Alpha = 2`, `Beta = 1`

  Linear skew towards the end of the path

`Alpha = 1`, `Beta = 0.5`

  Curved skew towards the end of the path

`Alpha = 0.5`, `Beta = 0.5`

  Curved skew towards both ends of the path

`Alpha = 0.5`, `Beta = 0.5`

  Curved skew away from both ends of the path

Once cells are assigned to paths and steps the correct means are extracted from the `paths.means` parameter and adjusted based on each cell's library size. An adjustment for BCV is then applied. Doublets are also simulated at this stage by selecting two path/step combinations and averaging the means.

### Value

SingleCellExperiment with cell means

[Package splatter version 1.14.1 Index]