# pquantile: Parallel quantile, median, mean In WGCNA: Weighted Correlation Network Analysis

## Description

Calculation of “parallel” quantiles, minima, maxima, medians, and means, across given arguments or across lists

## Usage

 ```1 2 3 4 5 6``` ```pquantile(prob, ...) pquantile.fromList(dataList, prob) pmedian(...) pmean(..., weights = NULL) pmean.fromList(dataList, weights = NULL) pminWhich.fromList(dataList) ```

## Arguments

 `prob` A single probability at which to calculate the quantile. See `quantile`. `dataList` A list of numeric vectors or arrays, all of the same length and dimensions, over which to calculate “parallel” quantiles. `weights` Optional vector of the same length as `dataList`, giving the weights to be used in the weighted mean. If not given, unit weights will be used. `...` Numeric arguments. All arguments must have the same dimensions. See details.

## Details

Given numeric arguments, say x,y,z, of equal dimensions (and length), the `pquantile` calculates and returns the quantile of the first components of x,y,z, then the second components, etc. Similarly, `pmedian` and `pmean` calculate the median and mean, respectively. The funtion `pquantile.fromList` is identical to `pquantile` except that the argument `dataList` replaces the ... in holding the numeric vectors over which to calculate the quantiles.

## Value

 `pquantile, pquantile.fromList` A vector or array containing quantiles. `pmean, pmean.fromList` A vector or array containing means. `pmedian` A vector or array containing medians. `pminWhich.fromList` A list with two components: `min` gives the minima, `which` gives the indices of the elements that are the minima.

Dimensions are copied from dimensions of the input arguments. If any of the input variables have `dimnames`, the first non-NULL dimnames are copied into the output.

## Author(s)

Peter Langfelder and Steve Horvath

`quantile`, `median`, `mean` for the underlying statistics.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```# Generate 2 simple matrices a = matrix(c(1:12), 3, 4); b = a+ 1; c = a + 2; # Set the colnames on matrix a colnames(a) = spaste("col_", c(1:4)); # Example use pquantile(prob = 0.5, a, b, c) pmean(a,b,c) pmedian(a,b,c) ```