Description Usage Arguments Details Value Author(s) References See Also
View source: R/assignMutations.R
Assigns mutations to previously predicted subpopulations.
1 | assignMutations(dm, finalSPs, max_PM=6, cnvSPs=NULL, ploidy = 2, verbose = T)
|
dm |
Matrix in which each row corresponds to a mutation. Has to contain at least the following column names: |
finalSPs |
Matrix in which each row corresponds to a subpopulation, as calculated by |
max_PM |
Upper threshold for the number of amplicons per mutated cell. See also |
cnvSPs |
Matrix in which each row corresponds to a subpopulation, as calculated by |
ploidy |
The background ploidy of the sequenced sample (default: 2). Changing the value of this parameter is not recommended. Dealing with cell lines or tumor biopsies of very high (>=0.95) tumor purity is a necessary but not sufficient condition to change the value of this parameter. |
verbose |
Give a more verbose output. |
Each mutated locus l is assigned to the subpopulation C, whose size f_C can best explain the allele frequency (AF) and copy number (CN) observed at l. Four alternative cell frequency probabilities, P_x(f_C), are calculated for the SNV at locus l, with x denoting one of the four alternative evolutionary scenarios (see also cellfrequency_pdf
).
The SNV is assigned to subpopulation:
C:=argmax_C (P_s(f_C), P_p(f_C), P_c(f_C), P_i(f_C)) (see cellfrequency_pdf
).
The mutated loci assigned to each subpopulation cluster represent the genetic profile of each predicted subpopulation.
The assignment between subpopulation C and locus l only implies that the SNV at l has been first propagated during the clonal expansion that gave rise to C. So SNVs present in C may not be exclusive to C but may also be present in subpopulations smaller than C. Whether or not this is the case can sometimes be inferred from the phylogenetic structure of the subpopulation composition. See also buildPhylo
.
A list with two fields:
dm |
The input matrix with seven additional columns: |
finalSPs |
The input matrix of subpopulations with column nMutations updated according to the total number of mutations assigned to each subpopulation. |
Noemi Andor
Li, B. & Li, J. Z (2014). A general framework for analyzing tumor subclonality using SNP array and DNA sequencing data. Genome Biol.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.