{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/116252"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/116252","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Performing phylogenetic placement at scale","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. 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The submission was exported from vireo on 2022-11-15 without embargo terms","The student, Gillian Chu, accepted the attached license on 2022-07-15 at 12:25.","The student, Gillian Chu, submitted this Thesis for approval on 2022-07-15 at 12:28.","This Thesis was approved for publication on 2022-07-19 at 11:32.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18335 on 2022-11-15 at 18:21:17","Phylogenetic placement is the problem of placing “query” sequences into an existing tree (called a “backbone tree”) whose leaves are aligned sequences, and has applications in updating large trees as well as in microbiome analysis. This is a study of phylogenetic placement pipelines which use extended alignment methods to first align the query sequence to the backbone alignment, before leveraging this information to place the query sequence into the tree using a placement method. We show that using methods specifically targeted for fragmentary sequences lead to higher accuracy, and we present pplacer-SCAMPP-taxtastic, which leverages several scalable techniques to extend the scalability of likelihood-based placement methods to ultra-large backbone trees (e.g., 200,000 sequences) with high accuracy."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Performing phylogenetic placement at scale"]}]}],"canonical_facts":{"dc:contributor":["Warnow, Tandy"],"dc:creator":["Chu, Gillian"],"dc:date":["2022-08","2022-07-19"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. 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We show that using methods specifically targeted for fragmentary sequences lead to higher accuracy, and we present pplacer-SCAMPP-taxtastic, which leverages several scalable techniques to extend the scalability of likelihood-based placement methods to ultra-large backbone trees (e.g., 200,000 sequences) with high accuracy."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/116252"],"dc:language":["en","eng"],"dc:rights":["Copyright 2022 Gillian Chu"],"dc:subject":["phylogeny","scalable","phylogenetic placement"],"dc:title":["Performing phylogenetic placement at scale"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Ecol, Evol, Conservation Biol"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:55Z"}