regionStats {Repitools} | R Documentation

## Find Regions of significance in microarray data

### Description

The function finds the highest smoothed score cutoff for a pre-specified FDR. Smoothing is performed over a specified number of basepairs, and regions must have a minimum number of qualifying probes to be considered significant. The FDR is calculated as the ratio of the number of significant regions found in a permutation-based test, to the number found in the actual experimental microarray data.

### Usage

      ## S4 method for signature 'matrix'
    regionStats(x, design = NULL, maxFDR=0.05, n.perm=5, window=600, mean.trim=.1, min.probes=10, max.gap=500, two.sides=TRUE, ndf, return.tm = FALSE, verbose=TRUE)
      ## S4 method for signature 'AffymetrixCelSet'
    regionStats(x, design = NULL, maxFDR=0.05, n.perm=5, window=600, mean.trim=.1, min.probes=10, max.gap=500, two.sides=TRUE, ind=NULL, return.tm = FALSE, verbose=TRUE)

### Arguments

`x` | An `AffymetrixCelSet` or `matrix` of array data to use.
`design` | A design matrix of how to manipulate
`maxFDR` | Cutoff of the maximum acceptable FDR
`n.perm` | Number of permutations to use
`window` | Size of window, in base pairs, to check for
`mean.trim` | A number representing the top and bottom fraction of ordered values in a window to be removed, before the window mean is calculated.
`min.probes` | Minimum number of probes in a window, for the region to qualify as a region of significance.
`max.gap` | Maximum gap between significant probes allowable.
`two.sides` | Look for both significant positive and negative regions.
`ind` | A vector of the positions of the probes on the array
`ndf` | The Nimblegen Definition File for Nimblegen array data.
`return.tm` | If TRUE, the values of the trimmed means of the intensities and permuted intensities are also retuned from the function.
`verbose` | Whether to print the progress of processing.

### Value

A `RegionStats` object (list) with elements

`regions` | A list of `data.frame`. Each `data.frame` has columns `chr`, `start`, `end`, `score`.
`tMeanReal` | Matrix of smoothed scores of intensity data. Each column is an experimental design.
`tMeanPerms` | Matrix of smoothed scores of permuted intensity data. Each column is an experimental design.
`fdrTables` | List of table of FDR at different score cutoffs. Each list element is for a different experimental design.

### Author(s)

Mark Robinson

### Examples

    ## Not run:
    library(Repitools)
    library(aroma.affymetrix)

    # assumes appropriate files are at annotationData/chipTypes/Hs_PromPR_v02/
    cdf <- AffymetrixCdfFile$byChipType("Hs_PromPR_v02",verbose=-20)
    cdfU <- getUniqueCdf(cdf,verbose=-20)

    # assumes appropriate files are at rawData/experiment/Hs_PromPR_v02/
    cs <- AffymetrixCelSet$byName("experiment",cdf=cdf,verbose=-20)
    mn <- MatNormalization(cs)
    csMN <- process(mn,verbose=-50)
    csMNU <- convertToUnique(csMN,verbose=-20)

    #> getNames(cs)
    # [1] "samp1"  "samp2"  "samp3"  "samp4"

    design <- matrix( c(1,-1,rep(0,length(cs)-2)), ncol=1, dimnames=list(getNames(cs),"elut5_L-P") )

    # just get indices of chr7 here
    ind <- getCellIndices(cdfU, unit = indexOf(cdfU, "chr7F"), unlist = TRUE, useNames = FALSE)

    regs <- regionStats(csMNU, design, ind = ind, window = 500, verbose = TRUE)

    ## End(Not run)

[Package Repitools version 1.33.3 Index]