The goal of this thesis research was to develop software to be used with RNA-Seq data for transcriptome quantification that was capable of handling multireads and quantifying isoforms on a more global level. Current software available for these purposes uses various forms of parameter alteration in order to work with multireads. Many still analyze isoforms per gene or per researcher determined clusters as well. By doing so, the effects of multireads are diminished or possibly wrongly represented. To address this issue, two programs, GWIE and ChromIE, were developed based on a simple iterative EM-like algorithm with no parameter manipulation. These programs are used to produce accurate isoform expression levels.
","abstract_html":"<p>The goal of this thesis research was to develop software to be used with RNA-Seq data for transcriptome quantification that was capable of handling multireads and quantifying isoforms on a more global level. Current software available for these purposes uses various forms of parameter alteration in order to work with multireads. Many still analyze isoforms per gene or per researcher determined clusters as well. By doing so, the effects of multireads are diminished or possibly wrongly represented. To address this issue, two programs, GWIE and ChromIE, were developed based on a simple iterative EM-like algorithm with no parameter manipulation. These programs are used to produce accurate isoform expression levels.</p>","abstract_has_math":false,"creators":["Johnson, Kristen"],"institution":null,"degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Dongxiao Zhu","Jaime Nino","Christopher Taylor"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-05-18T07:00:00Z","date_published":"2012-05-18T07:00:00Z","updated_at":"2026-07-24T05:29:36Z","subjects":["RNA-Seq","Transcriptome Quantification","Isoform Expression","Multireads","Expectation-Maximization (EM) Algorithm","Numerical Analysis and Scientific Computing","Other Computer Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarworks.uno.edu/td/1448","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dongxiao Zhu","Jaime Nino","Christopher Taylor"]},{"key":"dc:creator","label":"Author","values":["Johnson, Kristen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["RNA-Seq","Transcriptome Quantification","Isoform Expression","Multireads","Expectation-Maximization (EM) Algorithm","Numerical Analysis and Scientific Computing","Other Computer Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarworks.uno.edu/td/1448"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The goal of this thesis research was to develop software to be used with RNA-Seq data for transcriptome quantification that was capable of handling multireads and quantifying isoforms on a more global level. Current software available for these purposes uses various forms of parameter alteration in order to work with multireads. Many still analyze isoforms per gene or per researcher determined clusters as well. By doing so, the effects of multireads are diminished or possibly wrongly represented. To address this issue, two programs, GWIE and ChromIE, were developed based on a simple iterative EM-like algorithm with no parameter manipulation. These programs are used to produce accurate isoform expression levels.
"]},{"key":"dc:title","label":"Title","values":["Software for Estimation of Human Transcriptome Isoform Expression Using RNA-Seq Data"]}]}],"canonical_facts":{"dc:contributor":["Dongxiao Zhu","Jaime Nino","Christopher Taylor"],"dc:creator":["Johnson, Kristen"],"dc:description.abstract":["The goal of this thesis research was to develop software to be used with RNA-Seq data for transcriptome quantification that was capable of handling multireads and quantifying isoforms on a more global level. Current software available for these purposes uses various forms of parameter alteration in order to work with multireads. Many still analyze isoforms per gene or per researcher determined clusters as well. By doing so, the effects of multireads are diminished or possibly wrongly represented. To address this issue, two programs, GWIE and ChromIE, were developed based on a simple iterative EM-like algorithm with no parameter manipulation. These programs are used to produce accurate isoform expression levels.
"],"dc:identifier":["https://scholarworks.uno.edu/td/1448"],"dc:subject":["RNA-Seq","Transcriptome Quantification","Isoform Expression","Multireads","Expectation-Maximization (EM) Algorithm","Numerical Analysis and Scientific Computing","Other Computer Sciences"],"dc:title":["Software for Estimation of Human Transcriptome Isoform Expression Using RNA-Seq Data"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."]},"updated_at":"2026-07-24T05:29:36Z"}