assignQuantityToMutation

Matrix in which each row corrsponds to a mutation. Has to contain at least the following column names: 
	chr - the chromosome on which each mutation is located;
	startpos - the genomic position of each mutation.

Matrix in which each row corrsponds to a copy number fragment as computed by a circular binary segmentation algorithm. Has to contain at least the following columnnames:
	chr - chromosome;
	startpos - the first genomic position of a copy number segment; 
	endpos - the last genomic position of a copy number segment; 
	CN_Estimate - the copy number estimated for each segment.

The name of the new column. Valid options are: <code>FPKM, CN_Estimate.</code>

quantityColumnLabel

Assigns a quantity to each mutated locus. Currently, the only assignable quantity is the average ploidy (among all cells) of the locus in which the mutation is embedded. 


Expanding Ploidy and Allele Frequency on Nested Subpopulations (expands) characterizes coexisting subpopulations in a single tumor sample using copy number and allele frequencies derived from exome- or whole genome sequencing input data (http://www.ncbi.nlm.nih.gov/pubmed/24177718). The model detects coexisting genotypes by leveraging run-specific tradeoffs between depth of coverage and breadth of coverage. This package predicts the number of clonal expansions, the size of the resulting subpopulations in the tumor bulk, the mutations specific to each subpopulation, tumor purity and phylogeny. The main function runExPANdS() provides the complete functionality needed to predict coexisting subpopulations from single nucleotide variations (SNVs) and associated copy numbers.  The robustness of subpopulation predictions increases with the number of mutations provided. It is recommended that at least 200 mutations are used as input to obtain stable results. Updates in version 1.7 include: (1) Higher subpopulation detection specificity, in particular for small subpopulations. (2) Higher accuracy for mutation assignment to subpopulations. (3) Whenever possible, SNVs are assigned not only to the subpopulation in which they first occurred, but also to descending subpopulations. (4) Two additional output files are created: subpopulation specific ploidy matrix and a summary file of all detected subpopulations, including information on the inferred ancestor and the closest descendant of each subpopulation. (5) New subpopulation plotting options (function plotSPs). (6) New phylogeny plotting option: user can choose between consensus and germline population to be included as control. (7) 50 simulated samples of various genetic complexities and measurement precision included for user testing. Special thanks to Dr. Ryan Morin for his contributions that have led to higher accuracy measures during simulations for mutation assignment to subpopulations, as well as advanced visualization features of assigned mutations. Further documentation and FAQ available at http://dna-discovery.stanford.edu/software/expands.

assignQuantityToMutation: Quantity assignment (copy number) to mutations

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Examples