# corAndPvalue: Calculation of correlations and associated p-values In WGCNA: Weighted Correlation Network Analysis

## Description

A faster, one-step calculation of Student correlation p-values for multiple correlations, properly taking into account the actual number of observations.

## Usage

 ```1 2 3 4``` ```corAndPvalue(x, y = NULL, use = "pairwise.complete.obs", alternative = c("two.sided", "less", "greater"), ...) ```

## Arguments

 `x` a vector or a matrix `y` a vector or a matrix. If `NULL`, the correlation of columns of `x` will be calculated. `use` determines handling of missing data. See `cor` for details. `alternative` specifies the alternative hypothesis and must be (a unique abbreviation of) one of `"two.sided"`, `"greater"` or `"less"`. the initial letter. `"greater"` corresponds to positive association, `"less"` to negative association. `...` other arguments to the function `cor`.

## Details

The function calculates correlations of a matrix or of two matrices and the corresponding Student p-values. The output is not as full-featured as `cor.test`, but can work with matrices as input.

## Value

A list with the following components, each a matrix:

 `cor` the calculated correlations `p` the Student p-values corresponding to the calculated correlations `Z` Fisher transforms of the calculated correlations `t` Student t statistics of the calculated correlations `nObs` Numbers of observations for the correlation, p-values etc.

## Author(s)

Peter Langfelder and Steve Horvath

## References

Peter Langfelder, Steve Horvath (2012) Fast R Functions for Robust Correlations and Hierarchical Clustering. Journal of Statistical Software, 46(11), 1-17. https://www.jstatsoft.org/v46/i11/

`cor` for calculation of correlations only;

`cor.test` for another function for significance test of correlations

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```# generate random data with non-zero correlation set.seed(1); a = rnorm(100); b = rnorm(100) + a; x = cbind(a, b); # Call the function and display all results corAndPvalue(x) # Set some components to NA x[c(1:4), 1] = NA corAndPvalue(x) # Note that changed number of observations. ```

### Example output

```Loading required package: dynamicTreeCut

Attaching package: 'fastcluster'

The following object is masked from 'package:stats':

hclust

==========================================================================
*
*
sh: 1: wc: Permission denied
sh: 1: cannot create /dev/null: Permission denied
sh: 1: wc: Permission denied
sh: 1: cannot create /dev/null: Permission denied
sh: 1: wc: Permission denied
sh: 1: cannot create /dev/null: Permission denied
*    but it is not enabled within WGCNA in R.
*    To allow multi-threading within WGCNA with all available cores, use
*
*
*    Alternatively, set the following environment variable on your system:
*
*
*    for example
*
*
*    To set the environment variable in linux bash shell, type
*
*
*     before running R. Other operating systems or shells will
*     have a similar command to achieve the same aim.
*
==========================================================================

Attaching package: 'WGCNA'

The following object is masked from 'package:stats':

cor

\$cor
a         b
a 1.0000000 0.6836311
b 0.6836311 1.0000000

\$p
a            b
a 0.000000e+00 4.583225e-15
b 4.583225e-15 0.000000e+00

\$Z
a        b
a      Inf 8.274985
b 8.274985      Inf

\$t
a        b
a      Inf 9.272878
b 9.272878      Inf

\$nObs
a   b
a 100 100
b 100 100

\$cor
a         b
a 1.0000000 0.6699188
b 0.6699188 1.0000000

\$p
a           b
a 0.00000e+00 8.40745e-14
b 8.40745e-14 0.00000e+00

\$Z
a        b
a      Inf 7.859018
b 7.859018      Inf

\$t
a        b
a      Inf 8.748388
b 8.748388      Inf

\$nObs
a   b
a 96  96
b 96 100
```

WGCNA documentation built on March 1, 2021, 1:05 a.m.