{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/genomic-data-analysis-in-tree-spaces","title":"Genomic data analysis in tree spaces","arxiv_id":"1607.07503","date":"2016-07-25","proceeding":null,"authors":[],"abstract":"Recently, an elegant approach in phylogenetics was introduced by\nBillera-Holmes-Vogtmann that allows a systematic comparison of different\nevolutionary histories using the metric geometry of tree spaces. In many\nproblem settings one encounters heavily populated phylogenetic trees, where the\nlarge number of leaves encumbers visualization and analysis in the relevant\nevolutionary moduli spaces. To address this issue, we introduce tree\ndimensionality reduction, a structured approach to reducing large phylogenetic\ntrees to a distribution of smaller trees. We prove a stability theorem ensuring\nthat small perturbations of the large trees are taken to small perturbations of\nthe resulting distributions.\n  We then present a series of four biologically motivated applications to the\nanalysis of genomic data, spanning cancer and infectious disease. The first\nquantifies how chemotherapy can disrupt the evolution of common leukemias. The\nsecond examines a link between geometric information and the histologic grade\nin relapsed gliomas, where longer relapse branches were specific to high grade\nglioma. The third concerns genetic stability of xenograft models of cancer,\nwhere heterogeneity at the single cell level increased with later mouse\npassages. The last studies genetic diversity in seasonal influenza A virus. We\napply tree dimensionality reduction to 24 years of longitudinally collected\nH3N2 hemagglutinin sequences, generating distributions of smaller trees\nspanning between three and five seasons. A negative correlation is observed\nbetween the influenza vaccine effectiveness during a season and the variance of\nthe distributions produced using preceding seasons' sequence data. We also show\nhow tree distributions relate to antigenic clusters and choice of influenza\nvaccine. Our formalism exposes links between viral genomic data and clinical\nobservables such as vaccine selection and efficacy.","url_abs":"http://arxiv.org/abs/1607.07503v1","url_pdf":"http://arxiv.org/pdf/1607.07503v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"genomic-data-analysis-in-tree-spaces","repo_url":"https://github.com/antheamonod/FluPCA","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"dimensionality-reduction","task_name":"Dimensionality Reduction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}