mergeLevels: mergeLevels

In aCGH: Classes and functions for Array Comparative Genomic Hybridization data

Description

Merging of predicted levels for array CGH data and similar.

Usage

mergeLevels(vecObs,vecPred,pv.thres=0.0001,ansari.sign=0.05,thresMin=0.05,thresMax=0.5,verbose=1,scale=TRUE)

Arguments

vecObs	Vector of observed values, i.e. observed log2-ratios
vecPred	Vector of predicted values, i.e. mean or median of levels predicted by segmentation algorithm
pv.thres	Significance threshold for Wilcoxon test for level merging
ansari.sign	Significance threshold for Ansari-Bradley test
thresMin	merge if segment medians are closer than thresMin , defaiult is 0.05
thresMax	don't merge if segment medians are further than thresMax (unless needs to be merged for a different reason: wilcoxon test), default is .5
verbose	if 1, progress is printed
scale	whether thresholds are on the log2ratio scale and thus need to be converted to the copy number. default is TRUE

Details

mergeLevels takes a vector of observed log2-ratios and predicted log2ratios and merges levels that are not significantly distinct.

Value

vecMerged	Vector with merged values. One merged value returned for each predicted/observed value
mnNow	Merged level medians
sq	Vector of thresholds, the function has searched through to find optimum. Note, these thresholds are based on copy number transformed values
ansari	The p-values for the ansari-bradley tests for each threshold in sq

Note

vecObs and vecPred must have same length and observed and predicted value for a given probe should have same position in vecObs and vedPred. The function assumes that log2-ratios are supplied

Author(s)

Hanni Willenbrock ([e-mail]) and Jane Fridlyand ([e-mail])

References

Willenbrock H, Fridlyand J. (2005). A comparison study: applying segmentation to array CGH data for downstream analyses. Bioinformatics. 2005 Sep 14; [Epub ahead of print]

Examples

# Example data of observed and predicted log2-ratios
vecObs <- c(rep(0,40),rep(0.6,15),rep(0,10),rep(-0.4,20),rep(0,15))+rnorm(100,sd=0.2)
vecPred <- c(rep(median(vecObs[1:40]),40),rep(median(vecObs[41:55]),15),
  rep(median(vecObs[56:65]),10),rep(median(vecObs[66:85]),20),rep(median(vecObs[86:100]),15))

# Plot observed values (black) and predicted values (red)
plot(vecObs,pch=20)
points(vecPred,col="red",pch=20)

# Run merge function
merge.obj <- mergeLevels(vecObs,vecPred)

# Add merged values to plot
points(merge.obj$vecMerged,col="blue",pch=20)

# Examine optimum threshold
merge.obj$sq

Example output

Loading required package: cluster
Loading required package: survival
Loading required package: multtest
Loading required package: BiocGenerics
Loading required package: parallel

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, basename, cbind, colMeans, colSums, colnames,
    dirname, 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

Loading required package: Biobase
Welcome to Bioconductor

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


Attaching package: 'aCGH'

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

    heatmap


Current thresAbs:  0.05 

Current thresAbs:  0.09 

Current thresAbs:  0.13 

Current thresAbs:  0.17 

Current thresAbs:  0.21 

Current thresAbs:  0.25 

Current thresAbs:  0.29 

Current thresAbs:  0.33 

Current thresAbs:  0.37 

Current thresAbs:  0.41 

Current thresAbs:  0.45 

Current thresAbs:  0.49 

Current thresAbs:  0.5 
 [1] 0.05 0.09 0.13 0.17 0.21 0.25 0.29 0.33 0.37 0.41 0.45 0.49 0.50

aCGH documentation built on Nov. 8, 2020, 6:58 p.m.