CytoKProc {cytoKernel} | R Documentation

## CytoKProc

### Description

This function is a helper function that computes the shrunk effective size mean, shrunk effective size standard deviation (sd), p value and adjusted p value of each feature for the function `CytoK`.

### Usage

    CytoKProc(object, group_factor, lowerRho = 2, upperRho = 12, gridRho = 4)

### Arguments

`object` | an object which is a `matrix` or `data.frame` with features (e.g. cluster-marker combinations or genes) on the rows and samples (group factors) as the columns. Alternatively, a user can provide a `SummarizedExperiment` object and the `assay(object)` will be used as input for the CytoK procedure.
`group_factor` | a group level binary categorical response associated with each sample or column in the `object`. The order of the `group_factor` must match the order of the columns in `object`.
`lowerRho` | (Optional) lower bound of the kernel parameter.
`upperRho` | (Optional) upper bound of the kernel parameter.
`gridRho` | (Optional) number of grid points in the interval [lowerRho, upperRho].

### Value

A list of CytoK statistics including

`shrunkEffectSizeMean` | the shrunk effective size posterior mean per feature
`shrunkEffectSizeSD` | the shrunk effective size posterior sd per feature
`vec_pValue` | the unadjusted p value per feature
`AdjPvalue_features` | the adjusted p value per feature using the Benjamini-Hochberg procedure.

### Examples

    data <- cbind(matrix(rnorm(1200,mean=2, sd=1.5),
    nrow=200, ncol=6), matrix(rnorm(1200,mean=5, sd=1.9),
    nrow=200, ncol=6))
    data_CytoKProc <- CytoKProc(object=data,
    group_factor = rep(c(0,1), each=6), lowerRho=2,
    upperRho=12,gridRho=4)

[Package cytoKernel version 1.0.0 Index]