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Copy Number Aberrations (SENECA)
The copy number aberrations module is also referred to as SENECA (SEnsitive detection of copy NumbErs in CAncer). It identifies copy number aberrations (CNAs) in heterogeneous tumor samples that exhibit contamination with normal tissues, aneuploidy, and loss of heterozygosity (LOH) that can confound correct copy assignment and lead to erroneous CNA calls.
The algorithm workflow comprises of 2 distinct steps:
| ▶ | Segmentation of data into regions with putatively distinct copy numbers. |
| ▶ | Calculation of ploidy and purity with a final copy number assignment. |
As input, SENECA uses aligned sequences from tumor and matched normal samples and annotation information about the location of known variants in dbSNP, regional alignability, and the location of gaps in dbSNP.