clusterCellFrequencies: Clustering of cellular frequency probability distributions
Description
Calculates overrepresented cell frequencies using a two-step clustering procedure. Based on the assumption that passenger mutations occur within a cell prior to the driver event that initiates the expansion, each clonal expansion should be marked by multiple mutations. Thus mutations and copy number variations that took place in a cell prior to a clonal expansion should be present in a similar fraction of cells and leave a similar trace in the subsequent clonal expansion.
Matrix as obtained by computeCellFrequencyDistributions.Each row corresponds to a mutation and each column corresponds to a cellular frequency. Each value $densities[i,j]$ represen
precision
Precision with which subpopulation size is predicted, a small value reflects a high resolution and can trigger a higher number of predicted subpopulations (recommended: 0.1/log(n/7), where n = # mutations).
plotF
Value of 0 indicates no plot. If plotF > 0, a 3D plot will be generated to display the clustered probability distributions.
label
The sample name, used as title of the 3D plot. Only used if plotF > 0.
nrep
Positive integer giving the number of times to repeat the algorithm (default: 30).
Value
SPsMatrix of predicted subpopulations. Each row corresponds to a subpopulation and each column contains information about that subpopulation, such as the size in the sequenced tumor bulk (column Mean Weighted) and the confidence with which the subpopulation has been detected (column score).
Details
In the first step, mutations with similar cellular frequencies are grouped together by hierarchical cluster analysis of the probability distributions using the Kullback-Leibler divergence as a distance measure. The cell frequency at each cluster-maxima denotes the size of the subpopulation that harbors the clustered mutations. In the second step, each cluster is extended by members with similar distributions in an interval around the cluster-maxima.
References
Noemi Andor, Julie Harness, Hans Werner Mewes and Claudia Petritsch. (2013) ExPANdS: Expanding Ploidy and Allele Frequency on Nested Subpopulations. Bioinformatics. In Review.