estimateKappaByC1Density.PairedPSCBS: Estimate global background in segmented copy numbers
Description
Estimate global background in segmented copy numbers based on the location of peaks in a weighted
density estimator of the minor copy number mean levels.
The global background, here called $\kappa$,
may have multiple origins where normal contamination is one,
but not necessarily the only one.Usage
## S3 method for class 'PairedPSCBS':
estimateKappaByC1Density(this, adjust=1, minDensity=0.2, ..., verbose=FALSE)
Arguments
adjust
A numeric
scale factor specifying the size of
the bandwidth parameter used by the density estimator. minDensity
A non-negative numeric
threshold specifying
the minimum density a peak should have in order to consider
it a peak. Value
- Returns the background estimate as a
numeric
scalar.
Algorithm
- Retrieve segment-level minor copy numbers and corresponding weights:
- Grabs the segment-level C1 estimates.
- Calculate segment weights proportional to the number of heterozygous SNPs.
- Identify subset of regions with C1=0:
- Estimates the weighted empirical density function
(truncated at zero below). Tuning parameter 'adjust'.
- Find the first two peaks
(with a density greater than tuning parameter 'minDensity').
- Assumes that the two peaks corresponds to C1=0 and C1=1.
- Defines threshold Delta0.5 as the center location between
these two peaks.
- Estimate the normal contamination:
- For all segments with C1 < Delta0.5, calculate the weighted
median of their C1:s.
- Let kappa be the above weighted median.
This is the estimated background.
See Also
Instead of calling this method explicitly, it is recommended
to use the *estimateKappa()
method.