{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/115367"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/115367","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Methylation and High Dimensional Data Integration","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms","abstract_has_math":false,"creators":["Tu, Robin"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Statistics","degree_department":null,"school":null,"contributors":["Zhao, Sihai D","Foss, Alexander H","Li, Bo","Simpson, Douglas G"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-05","date_published":"2022-05","updated_at":"2026-07-22T22:24:54Z","subjects":["Dimension Reduction","Contrastive","Methylation","Bioinformatics","Statistics","Methodology"],"languages":["en","eng"],"rights":["Copyright 2022 Robin Tu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/115367","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhao, Sihai D","Foss, Alexander H","Li, Bo","Simpson, Douglas G"]},{"key":"dc:creator","label":"Author","values":["Tu, Robin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-05","2022-04-12"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Statistics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Dimension Reduction","Contrastive","Methylation","Bioinformatics","Statistics","Methodology"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2022 Robin Tu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/115367"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms","The student, Robin Tu, accepted the attached license on 2022-04-05 at 10:39.","The student, Robin Tu, submitted this Dissertation for approval on 2022-04-05 at 10:47.","This Dissertation was approved for publication on 2022-04-12 at 16:22.","DSpace SAF Submission Ingestion Package generated from Vireo submission #17585 on 2022-11-11 at 13:04:47","Data integration challenges in bioinformatics are multifaceted. This paper aims to motivate methods and techniques to handle multiple data types and data sources. We integrate multiple sources of data to explore the usefulness of proxy blood methylation as a substitute for brain tissue. We then propose a likelihood based dimension reduction method to handle non-quantitative data. Lastly, we propose a tuning-free method that identifies low-dimensional representations of a target dataset relative to one or more comparison datasets which also is computationally efficient even with large numbers of features."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Methylation and High Dimensional Data Integration"]}]}],"canonical_facts":{"dc:contributor":["Zhao, Sihai D","Foss, Alexander H","Li, Bo","Simpson, Douglas G"],"dc:creator":["Tu, Robin"],"dc:date":["2022-05","2022-04-12"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms","The student, Robin Tu, accepted the attached license on 2022-04-05 at 10:39.","The student, Robin Tu, submitted this Dissertation for approval on 2022-04-05 at 10:47.","This Dissertation was approved for publication on 2022-04-12 at 16:22.","DSpace SAF Submission Ingestion Package generated from Vireo submission #17585 on 2022-11-11 at 13:04:47","Data integration challenges in bioinformatics are multifaceted. This paper aims to motivate methods and techniques to handle multiple data types and data sources. We integrate multiple sources of data to explore the usefulness of proxy blood methylation as a substitute for brain tissue. We then propose a likelihood based dimension reduction method to handle non-quantitative data. Lastly, we propose a tuning-free method that identifies low-dimensional representations of a target dataset relative to one or more comparison datasets which also is computationally efficient even with large numbers of features."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/115367"],"dc:language":["en","eng"],"dc:rights":["Copyright 2022 Robin Tu"],"dc:subject":["Dimension Reduction","Contrastive","Methylation","Bioinformatics","Statistics","Methodology"],"dc:title":["Methylation and High Dimensional Data Integration"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Statistics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:54Z"}