Description Usage Arguments Details Value Author(s) References See Also Examples
Load TITAN model parameters based on maximum copy number and number of clonal clusters.
1 2 3 | loadDefaultParameters(copyNumber = 5, numberClonalClusters = 1, skew = 0,
hetBaselineSkew = NULL, alleleEmissionModel = "binomial",
symmetric = TRUE, data = NULL)
|
copyNumber |
Maximum number of absolute copies to account for in the model. Default (and recommended) is 5. |
numberClonalClusters |
Number of clonal clusters to use in the analysis. Each cluster represents a potential clone. Using ‘1’ treats the sample as being clonal (no subclonality). ‘2’ or higher treats the tumour data as being subclonal. |
skew |
|
hetBaselineSkew |
Allelic reference base skew for heterozygous states (e.g. 1:1, 2:2, 3:3). Value is additive to baseline allelic ratios (which may already be adjusted by |
alleleEmissionModel |
Specify the emission model to use for the allelic input data. |
symmetric |
|
data |
|
Generally, TitanCNA should be run once for each number of clonal clusters in the range of 1 to 5. Then, use model selection to choose the run with the optimal number of clusters.
If the allelic ratio data is skewed towards one allele, then use skew
to help define the baseline. For example, if the data is skewed towards the reference, then use 0.1 so that the heterozygous baseline is at 0.6. The allelic ratio baseline is normally at 0.5.
sParams
, which represents the parameters for estimation of subclonality, always contains values for one cluster that represents the clonally dominant cluster (events present in nearly all tumour cells) with an initial value of sParams$s_0[1] = 0.001
.
Setting symmetric
to TRUE
will treat reference and non-reference alleles the same. For example, genotypes AA
(homozygous for reference allele) and BB
(homozygous for non-reference allele) as being equivalent. This will reduce the state space substantially.
list
containing 4 sets of parameters, each as a component:
genotypeParams |
Parameters for copy number and allelic ratios geneotype states |
normalParams |
Parameters for normal contamination |
ploidyParams |
Parameters for average tumour ploidy |
sParams |
Parameters for modeling subclonality: clonal clusters and cellular prevalence |
Gavin Ha <gavinha@gmail.com>
Ha, G., Roth, A., Khattra, J., Ho, J., Yap, D., Prentice, L. M., Melnyk, N., McPherson, A., Bashashati, A., Laks, E., Biele, J., Ding, J., Le, A., Rosner, J., Shumansky, K., Marra, M. A., Huntsman, D. G., McAlpine, J. N., Aparicio, S. A. J. R., and Shah, S. P. (2014). TITAN: Inference of copy number architectures in clonal cell populations from tumour whole genome sequence data. Genome Research, 24: 1881-1893. (PMID: 25060187)
1 2 3 4 | #### LOAD PARAMETERS ####
numClusters <- 2
params <- loadDefaultParameters(copyNumber = 5,
numberClonalClusters = numClusters)
|
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