Main CBS Algorithm for Change-Point Detection

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Description

This is the main algorithm. It teratively scans for window of arbitrary size where the case and control read depths are different. It continues until a stopping criterion based on mBIC, maximum number of cut, and the statistic at the current segment.

Usage

1
ScanCBS(cases, controls, statistic = "binomial", grid.size = "auto", takeN = 5, maxNCut = 30, minStat = 5, verbose = FALSE, timing = TRUE)

Arguments

cases

A numeric vector of the case/tumor reads

controls

A numeric vector of the control/normal reads

statistic

The statistic to be used. Can be 'binomial','rabinowitz', 'normal', or 'hybrid'

grid.size

The set of grid sizes for the iterative search. An automatic default can be computed.

takeN

The number of candidate change points to be added to a temporary set at each grid size

maxNCut

The maximum number of segmentation steps to perform

minStat

The minimum statistic value required to continue the segmentation. Can be set to 0 to be ignored.

verbose

If TRUE, then will print much information on each segmentation. For diagnostics only.

timing

If TRUE, perform a timing of this algorithm, include in the output data file.

Details

This algorithm is an use of the Circular Binary Segmentation method. It continues to segment the reads and consider the resulting child regions for further segmentation. It keeps track of the most promising cut in each children, and only the child region with the most significant segmentation is further cut, yielding more children. This is repeated until stopping criteria are met. The four types of statistics are by the use of exact binomial likelihood, score statistic, normal approximation, and an hybrid of normal approximation with binomial likelihood for small windows.

Value

tauHat

The change points called

statHat

A matrix containing the statistic and its segmentation for the model called

relCN

The relative CN computed for each segment between change points

timingRes

A list containing the result of the timing of this algorithm

Author(s)

Jeremy J. Shen

References

D. Rabinowitz, IMS Lecture Notes - Monograph Series, Vol. 23, 1994

See Also

ScanIterateGrid, ScanBIC, relCNComp, getAutoGridSize

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