Somatic mutations and Loss of Heterozygosity (LOH) of a Glioblastoma tumor (TCGA-06-0152-01).

datasets

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 (<https://pubmed.ncbi.nlm.nih.gov/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 2.1 include: (i) new parameter ploidy in runExPANdS.R allows specification of non-diploid background ploidies (e.g. for near-triploid cell lines); (ii) parallel computing option is available.

Noemi Andor

expands

Expanding Ploidy and Allele-Frequency on Nested Subpopulations

snv function

Numeric matrix with 773 rows (one per mutation) and 7 columns:
	 chr - the chromosome 
	 startpos - genomic position 
	 endpos - same as above 
	 REF - ASCII code of the reference nucleotide (in hg18/hg19) 
	 ALT - ASCII code of the B-allele nucleotide 
	 AF_Tumor - allele frequency of B-allele 
	 PN_B - count of B-allele in normal cells. A value of 0 indicates that the mutation has only been detected in the tumor sample (i.e. somatic mutations). A value of 1 indicates that the variant is also present in the normal (control) sample, albeit at reduced allele frequency (i.e. this is a germline variant, which passed the calling filter due to the presence of an LOH event). Other mutations should not be included.

snv: Single Nucleotide Variations

Description

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