# cosinePerm: Cosine Permutations In CoreGx: Classes and Functions to Serve as the Basis for Other 'Gx' Packages

## Description

Computes the cosine similarity and significance using permutation test. This function uses random numbers, to ensure reproducibility please call `set.seed()` before running the function.

## Usage

 ```1 2 3 4 5 6 7 8 9``` ```cosinePerm( x, y, nperm = 1000, alternative = c("two.sided", "less", "greater"), include.perm = FALSE, nthread = 1, ... ) ```

## Arguments

 `x` `factor` is the factors for the first variable `y` `factor` is the factors for the second variable `nperm` `integer` is the number of permutations to compute the null distribution of MCC estimates `alternative` `string` indicates the alternative hypothesis and must be one of <80><98>'two.sided'<80><99>, <80><98>'greater'<80><99> or <80><98>'less'<80><99>. You can specify just the initial letter. <80><98>'greater'<80><99> corresponds to positive association, <80><98>'less'<80><99> to negative association. Options are 'two.sided', 'less', or 'greater' `include.perm` `boolean` indicates whether the estimates for the null distribution should be returned. Default set to 'FALSE' `nthread` `integer` is the number of threads to be used to perform the permutations in parallel `...` A `list` of fallthrough parameters

## Value

A `list` estimate of the cosine similarity, p-value and estimates after random permutations (null distribution) in include.perm is set to 'TRUE'

## Examples

 ```1 2 3``` ```x <- factor(c(1,2,1,2,1)) y <- factor(c(2,2,1,1,1)) cosinePerm(x, y) ```

CoreGx documentation built on Nov. 8, 2020, 4:50 p.m.