@inproceedings{e35cd030982749e5bb7ef9152a5edca1,
title = "Sapling: Inferring and Summarizing Tumor Phylogenies from Bulk Data Using Backbone Trees",
abstract = "Cancer phylogenies are key to understanding tumor evolution. There exist many important downstream analyses that take as input a single or a small number of trees. However, due to uncertainty, one typically infers many, equally-plausible phylogenies from bulk DNA sequencing data of tumors. We introduce Sapling, a heuristic method to solve the Backbone Tree Inference from Reads problem, which seeks a small set of backbone trees on a smaller subset of mutations that collectively summarize the entire solution space. Sapling also includes a greedy algorithm to solve the Backbone Tree Expansion from Reads problem, which aims to expand an inferred backbone tree into a full tree. We prove that both problems are NP-hard. On simulated and real data, we demonstrate that Sapling is capable of inferring high-quality backbone trees that adequately summarize the solution space and that can be expanded into full trees.",
keywords = "Cancer, consensus, intra-tumor heterogeneity, maximum agreement",
author = "Yuanyuan Qi and Mohammed El-Kebir",
note = "Publisher Copyright: {\textcopyright} Yuanyuan Qi and Mohammed El-Kebir;; 24th International Workshop on Algorithms in Bioinformatics, WABI 2024 ; Conference date: 02-09-2024 Through 04-09-2024",
year = "2024",
month = aug,
doi = "10.4230/LIPIcs.WABI.2024.7",
language = "English (US)",
series = "Leibniz International Proceedings in Informatics, LIPIcs",
publisher = "Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing",
editor = "Pissis, {Solon P.} and Wing-Kin Sung",
booktitle = "24th International Workshop on Algorithms in Bioinformatics, WABI 2024",
address = "Germany",
}