model_points: Generate B-allele frequency, mutation frequency and depth...
In sequenza: Copy Number Estimation from Tumor Genome Sequencing Data

Description Usage Arguments Details Value See Also Examples

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.

1 2	baf.model.points(cellularity, ploidy, baf_types, avg.depth.ratio) mufreq.model.points(cellularity, ploidy, mufreq_types, avg.depth.ratio)

`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.

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.

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.

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

    # 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))

  CNn CNt B       BAF depth.ratio
1   2   0 0 0.5000000        0.50
2   2   1 0 0.3333333        0.75
3   2   2 0 0.2500000        1.00
4   2   2 1 0.5000000        1.00
5   2   3 0 0.2000000        1.25
6   2   3 1 0.4000000        1.25
7   2   4 0 0.1666667        1.50
8   2   4 1 0.3333333        1.50
9   2   4 2 0.5000000        1.50
   CNn CNt Mt   mufreqs depth.ratio
1    1   0  0 0.0000000         0.5
2    1   1  0 0.0000000         1.0
3    1   1  1 0.5000000         1.0
4    1   2  0 0.0000000         1.5
5    1   2  1 0.3333333         1.5
6    1   2  2 0.6666667         1.5
7    1   3  0 0.0000000         2.0
8    1   3  1 0.2500000         2.0
9    1   3  2 0.5000000         2.0
10   1   3  3 0.7500000         2.0
11   1   4  0 0.0000000         2.5
12   1   4  1 0.2000000         2.5
13   1   4  2 0.4000000         2.5
14   1   4  3 0.6000000         2.5
15   1   4  4 0.8000000         2.5