sequenza (version 3.0.0)

model.points: Generate B-allele frequency, mutation frequency and depth ratios at given model points, cellularity and ploidy values

Description

The baf.model.points and mufreq.model.points functions combine theoretical_baf, theoretical_mufreq and theoretical_depth_ratio to model the theoretical respective values at known values of cellularity and ploidy.

Usage

baf.model.points(cellularity, ploidy, baf_types, avg.depth.ratio)
    mufreq.model.points(cellularity, ploidy, mufreq_types, avg.depth.ratio)

Arguments

cellularity

fraction of tumor cells in the sample.

ploidy

2 * ratio between total DNA content in a tumor cell and a normal cell.

baf_types

matrix with the sets of copy numbers and number of mutated alleles over which to model mutation frequency and depth ratio. The matrix can be generated with baf.types.matrix.

mufreq_types

matrix with the sets of copy numbers and number of mutated alleles over which to model mutation frequency and depth ratio. The matrix can be generated with mufreq.types.matrix.

avg.depth.ratio

average normalized depth ratio.

Value

For baf.model.points a data.frame with two columns:

BAF

modelled values of B-allele frequency.

depth_ratio

modelled values of depth ratio.

For mufreq.model.points a data.frame with two columns:

mufreqs

modelled values of mutation frequency.

depth_ratio

modelled values of depth ratio.

Details

The baf.model.points and mufreq.model.points functions generate the theoretical values of B-allele frequency, mutation frequency and depth ratio for the given type tags. To learn more about type tags see types.matrix.

See Also

types.matrix, theoretical.depth.ratio, theoretical.baf theoretical.mufreq.

Examples

# NOT RUN {
    # Simulate a cellularity of 0.5, ploidy of 2 and types from min CNt 0
    # and max = 4 on an originally diploid genome:
    types <- baf.types.matrix(CNt.min = 0, CNt.max = 4, CNn = 2)
    cbind(types, baf.model.points(cellularity = 0.5, ploidy = 2,
        baf_types = types, avg.depth.ratio = 1))
    # Simulate a cellularity of 0.5, ploidy of 2 and types from min CNt 0
    # and max = 4 on an originally monoallelic genome:
    types <- mufreq.types.matrix(CNt.min = 0, CNt.max = 4, CNn = 1)
    cbind(types, mufreq.model.points(cellularity = 0.5, ploidy = 2,
        mufreq_types = types, avg.depth.ratio = 1))
# }