# bootstrapCor: Calculate bootstrap p-values for correlation measures In maigesPack: Functions to handle cDNA microarray data, including several methods of data analysis

## Description

This function takes a numerical matrix (or two vectors) and calculates bootstrapped (by permutation) p-values to test if the correlation value is equal to zero. If the first argument is a matrix, the p-values are calculated between all pairs of rows of the matrix.

## Usage

 ```1 2``` ```bootstrapCor(x, y=NULL, bRep, type="Rpearson", ret="p-value", alternative="two.sided") ```

## Arguments

 `x` numerical matrix or vector to be analysed. If a vector, the argument `y` must be informed. `y` numerical vector. Must be informed if `x` is a vector. If `x` is a matrix, this argument is ignored. Defaults to NULL. `bRep` number of permutation to be done in the test. `type` character string specifying the type of correlation statistic to be used. Possible values are 'Rpearson', 'pearson', 'spearman' or 'kendall'. `ret` character string with the value to return. Must be 'p-value' (default) for the usual p-value or 'max', to return the maximum absolute correlation value obtained by the permutation. `alternative` character specifying the type of test to do, must be 'two.sided' (default), 'less' or 'greater'.

## Details

Pearson, spearman and kendall types of correlation values are calculated by `cor` function from package stats. The method Rpearson was developed in this package and is a generalisation of the jackniffe correlation proposed by Heyer et al. (1999), it is calculated using the function `robustCorr`.

## Value

The result of this function is a square matrix (length equal to the number of rows of `x`) if `x` is a matrix or a numerical value if `x` and `y` are vectors. The result is the p-values or maximum correlation values calculated by permutation tests.

## Author(s)

Gustavo H. Esteves <gesteves@vision.ime.usp.br>

## References

Heyer, L.J.; Kruglyak, S. and Yooseph, S. Exploring expression data: identification and analysis of coexpressed genes, Genome Research, 9, 1106-1115, 1999 (http://www.genome.org/cgi/content/full/9/11/1106)

`cor`, `robustCorr`

## Examples

 ```1 2 3 4 5 6``` ```x <- runif(50, 0, 1) y <- rbeta(50, 1, 2) bootstrapCor(x, y, bRep=100) z <- matrix(rnorm(100, 0, 1), 4, 25) bootstrapCor(z, bRep=100) ```

### Example output

```Loading required package: convert

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colMeans, colSums, colnames, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
setdiff, sort, table, tapply, union, unique, unsplit, which,
which.max, which.min

Welcome to Bioconductor

Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.

Attaching package: 'limma'

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

plotMA