findAmplif.func: Function to determine high level amplifications

Description Usage Arguments Details Value Author(s) References See Also

View source: R/hmm.R

Description

This function identifies high level amplifications by considering the height, the width of an amplicon relative to the urrounding clones. Only narrow peaks much higher than its neigbors are considered as high level amplifications.

Usage

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findAmplif.func(absValSingle = 1, absValRegion = 1.5, diffVal1 = 1,
diffVal2 = 0.5, maxSize = 10000, translen.matr, trans.matr, aber,
outliers, pred, pred.obs, statesres)

Arguments

absValSingle

A clone is declared to be an amplification if it is a focal aberration or an outlier and its value exceeds absValSingle

absValRegion

A clone is an amplification if if a clone belong to a region with width less than maxSize and observed value for a clones is greater than absValRegion

diffVal1

Clone is an amplification if it is an aberration and greater by diffVal1 than max of the two surrounding stretches

diffVal2

Clone is an amplification if it is an outlier, its observed values is greater by diffVal2 than max of the two surrounding stretches

maxSize

The clones may not be declared as amplifications if they belong to the states with spanning more than maxSize

translen.matr

State length matrix. The output of the findTrans.func

trans.matr

Transition matrix. The output of the findTrans.func

aber

Aberration matrix. The output of the findAber.func

outliers

Outliers matrix. The output of the findOutliers.func

pred

Predicted values matrix. The output of the findOutliers.func

pred.obs

Predicted values matrix with observed values assigned to the outliers. The output of the findOutliers.func

statesres

The states output of the hmm.run.func

Details

Note that all the distances are in Megabases and all the heights are on log2ratio scale.

Value

amplif.matrix

Binary matrix with a row for each clone and column for each sample. "1" indicates amplification

...

Author(s)

Jane Fridlyand

References

Application of Hidden Markov Models to the analysis of the array CGH data, Fridlyand et.al., JMVA, 2004

See Also

aCGH


Bioconductor-mirror/aCGH documentation built on June 1, 2017, 4:13 a.m.