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. 2013 Jul 27;41(17):e165. doi: 10.1093/nar/gkt641

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© The Author(s) 2013. Published by Oxford University Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 3. — Illustration of the usage of first-generation trees and partial trees for deriving the TrAp solution of a mixture of four subclones. In this example, five aberrations were measured from an aggregate sample and their frequencies were , , , and , respectively. The dummy measurement was also added to generate the aggregate signal frequency vector . In the first step, TrAp identifies all first-generation trees, namely and . In the second step, TrAp generates the possible partial trees, namely , , and , and consequently selects only , as it is the only partial tree that contains a maximum number of first-generation trees. In the third step, TrAp generates evolutionary trees starting from the partial tree . To complete the evolutionary tree starting from PT₄, the subclone C₁ is positioned as the root of the tree. Because C₁ is part of the first-generation tree T₁, the subclones C₂ and C₆ are automatically added as direct descendants of C₁. Next, C₃ is added as a direct descendant of C₂. Because C₃ is part of the first-generation tree T₂, C₄ is automatically added as direct descendant of C₃. Finally, C₅ is added as a direct descendant of C₄, generating the optimal TrAp solution to the subclonal deconvolution problem. We remark that the optimal solution generated by the TrAp algorithm is equal to the left solution of Supplementary Figure S1 and to solution in Supplementary Figure S2.

Inline graphic — Illustration of the usage of first-generation trees and partial trees for deriving the TrAp solution of a mixture of four subclones. In this example, five aberrations were measured from an aggregate sample and their frequencies were , , , and , respectively. The dummy measurement was also added to generate the aggregate signal frequency vector . In the first step, TrAp identifies all first-generation trees, namely and . In the second step, TrAp generates the possible partial trees, namely , , and , and consequently selects only , as it is the only partial tree that contains a maximum number of first-generation trees. In the third step, TrAp generates evolutionary trees starting from the partial tree . To complete the evolutionary tree starting from PT₄, the subclone C₁ is positioned as the root of the tree. Because C₁ is part of the first-generation tree T₁, the subclones C₂ and C₆ are automatically added as direct descendants of C₁. Next, C₃ is added as a direct descendant of C₂. Because C₃ is part of the first-generation tree T₂, C₄ is automatically added as direct descendant of C₃. Finally, C₅ is added as a direct descendant of C₄, generating the optimal TrAp solution to the subclonal deconvolution problem. We remark that the optimal solution generated by the TrAp algorithm is equal to the left solution of Supplementary Figure S1 and to solution in Supplementary Figure S2.