The bourque distances for mutation trees of cancers
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Author / Producer
Date
2020
Publication Type
Conference Paper
ETH Bibliography
yes
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OPEN ACCESS
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Abstract
Mutation trees are rooted trees of arbitrary node degree in which each node is labeled with a mutation set. These trees, also referred to as clonal trees, are used in computational oncology to represent the mutational history of tumours. Classical tree metrics such as the popular Robinson - Foulds distance are of limited use for the comparison of mutation trees. One reason is that mutation trees inferred with different methods or for different patients often contain different sets of mutation labels. Here, we generalize the Robinson - Foulds distance into a set of distance metrics called Bourque distances for comparing mutation trees. A connection between the Robinson - Foulds distance and the nearest neighbor interchange distance is also presented.
Permanent link
Publication status
published
External links
Book title
20th International Workshop on Algorithms in Bioinformatics (WABI 2020)
Volume
172
Pages / Article No.
14
Publisher
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Event
20th International Workshop on Algorithms in Bioinformatics (WABI 2020) (virtual)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
mutation trees; clonal trees; tree distance; phylogenetic trees; tree metric; Robinson–Foulds distance; Bourque distance
Organisational unit
03790 - Beerenwinkel, Niko / Beerenwinkel, Niko
Notes
Due to the Coronavirus (COVID-19) the conference was conducted virtually.
Funding
Related publications and datasets
Is previous version of: https://doi.org/10.3929/ethz-b-000490252