SFpval {SigFuge} | R Documentation

## Calculate SigFuge p-value

### Description

Function for computing significance of clustering p-value. p-value is obtained from `sigclust`, a simulation based procedure for testing significance of clustering in high dimension low sample size (HDLSS) data.

The SigClust hypothesis test is given:

- H0: data generated from single Gaussian

- H1: data not generated from single Gaussian

### Usage

      SFpval(data, normalize = 1, flag = 1)

### Arguments

`data` | a d x n matrix of read counts at d positions for n samples.
`normalize` | a n x 1 logical vector of flagged samples.
`flag` | a n x 1 logical vector of samples flagged as low expression. If `flag == 1`, default low expression cutoffs are applied to `data`. If `flag == 0`, no samples are flagged as low expression (equivalent to setting `flag = zeros(n,1)`).

### Value

`SFpval` returns an object of class `sigclust-class`. Avaliable slots are described in detail in the `sigclust` package. Primarily, we make use of `@pvalnorm`.

### Author(s)

Patrick Kimes <pkimes@live.unc.edu>

### Examples

    data(geneDepth)
    SFout <- SFpval(geneDepth, normalize = 1, flag = 1)
    SFout@pvalnorm

[Package SigFuge version 1.18.0 Index]