getadjustedsegments: Create a data frame with segment information corresponding to...

In tgac-vumc/ACE: Absolute Copy Number Estimation from Low-coverage Whole Genome Sequencing

Create a data frame with segment information corresponding to a model

Description

getadjustedsegments applies model parameters to segment data and returns a data frame with information of the individual segments, scaled according to the model.

Usage

getadjustedsegments(template, QDNAseqobjectsample = FALSE, 
                    cellularity = 1, ploidy = 2, sgc = c(),
                    standard, log = FALSE)

Arguments

template	Object. Either a data frame as created by objectsampletotemplate, or a QDNAseq-object
QDNAseqobjectsample	Integer. Specifies which sample to analyze from the QDNAseq-object. Required when using a QDNAseq-object as template. Default = FALSE
cellularity	Numeric. Used for rescaling bin and segment values. Default = 1
ploidy	Integer. Assume the median of segments has this absolute copy number. Default = 2
sgc	Integer or character vector. Specify which chromosomes occur with only a single copy in the germline
standard	Numeric. Force the given ploidy to represent this raw value. When omitted, the standard will be calculated from the data. When using parameters obtained from squaremodel, specify standard = 1
log	Logical. When TRUE, log2-values are calculated straigth from raw data, unadjusted! Convenience function to resemble DNAcopy output as used for ABSOLUTE and others. Default = FALSE

Details

The output contains two columns for segment mean. The first is the adjusted segment value, the second (Segment_Mean2) is the mean of the adjusted copy number values. I do not know how the QDNAseq or DNAcopy calculates the segment mean, but there is always a very small difference between the two. The P_log10 is the 10-base log of the two-sided probability that the real segment mean is the integer closest to the segment mean. While this gives an indication of the chance that a segment is subclonal, it should be interpreted with care. Because segments usually comprise many bins, these values can easily be very low. A small bias in the normalization can cause "significant", but not necessarily relevant results.

Value

Returns a data frame with segment information

Note

If your data contains sex chromosomes, then make sure to specify sgc = c("X", "Y") when analyzing data from a male individual.

Author(s)

Jos B. Poell

See Also

analyzegenomiclocations, postanalysisloop

Examples

## using segmented data from a QDNAseq-object
data("copyNumbersSegmented")
singlemodel(copyNumbersSegmented, QDNAseqobjectsample = 2)
getadjustedsegments(copyNumbersSegmented, QDNAseqobjectsample = 2, 
  cellularity = 0.39)

tgac-vumc/ACE documentation built on Nov. 29, 2022, 12:15 a.m.