{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/110417"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/110417","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Small-sample estimation of the mutational support and the distribution of mutations in the SARS-CoV-2 genome","abstract":"DSpace SAF Submission Ingestion Package generated from Vireo submission #16175 on 2021-09-16 at 16:40:03","abstract_html":"DSpace SAF Submission Ingestion Package generated from Vireo submission #16175 on 2021-09-16 at 16:40:03","abstract_has_math":false,"creators":["Rana, Vishal"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Milenkovic, Olgica"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-09-17T01:10:35Z","date_published":"2021-09-17T01:10:35Z","updated_at":"2026-07-22T22:24:50Z","subjects":["Comparative ORF study","Good-Turing estimation","Mutation rates","SARS-Cov-2 Data analysis","Small-sample support estimation"],"languages":["en"],"rights":["Copyright 2021 Vishal Rana"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/110417","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Milenkovic, Olgica"]},{"key":"dc:creator","label":"Author","values":["Rana, Vishal"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2021-09-17T01:10:35Z","2021-02-23","2021-05"]},{"key":"dc:type","label":"Dc Type","values":["Thesis","text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"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":["Comparative ORF study","Good-Turing estimation","Mutation rates","SARS-Cov-2 Data analysis","Small-sample support estimation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2021 Vishal Rana"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/110417"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["DSpace SAF Submission Ingestion Package generated from Vireo submission #16175 on 2021-09-16 at 16:40:03","Made available in DSpace on 2021-09-17T01:10:35Z (GMT). No. of bitstreams: 4 RANA-THESIS-2021.pdf: 2056607 bytes, checksum: 3ab4339ddbd42eb62574f6b98cade434 (MD5) Supplementary_tables.xlsx: 33949 bytes, checksum: 5cf8eda9cf8909f4409183d2122637b5 (MD5) MS Thesis.zip: 6002493 bytes, checksum: 4e40b4fc03c803a23752422b7f73659e (MD5) LICENSE.txt: 4208 bytes, checksum: 7ab10df0f102fdcd50fb33f4cbae102a (MD5) Previous issue date: 2021-02-23","The problem of accurately estimating and characterizing different mutations in the viral genomes present within a population is of great importance in tracking and mitigating the spread of the virus and is made difficult by the lack of a sufficient number of sequenced genomes especially during the early stages of an outbreak. We consider the problem of determining the mutational support and distribution of mutations in the SARS-Cov-2 genome and its open reading frames (ORFs). The mutational support refers to the unknown number of sites that are mutated among all the viral strains present in a population. The support and distribution of mutations can be used to guide primer selection for RT PCR test kits, study the virulence of the virus, discover adaptation mechanisms deployed by the virus to evade the host immune system, as well as to identify new strains that might be circulating in the population early on. We propose new state-of-the-art polynomial estimation techniques using weighted and regularized Chebyshev approximations for small-sample mutational support estimation and we use a modified Good-Turing estimator for distribution estimation. Our differential analysis of mutations in various population subgroups (based on data retrieved from GISAID repository) revealed several important differences including those in the ORF6 and ORF7a regions for older versus younger patients, ORF1b and ORF10 regions for females versus males, and in several ORFs for Asia versus Europe and North America. We also found no significant mutations in the primer regions from ORF N chosen by CDC for RT-PCR test kits in any of the subpopulations, which is important for the reliability of the test results.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2021-09-16 without embargo terms","The student, Vishal Rana, accepted the attached license on 2021-02-23 at 11:50.","The student, Vishal Rana, submitted this Thesis for approval on 2021-02-23 at 12:13.","This Thesis was approved for publication on 2021-02-23 at 14:46."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Small-sample estimation of the mutational support and the distribution of mutations in the SARS-CoV-2 genome"]}]}],"canonical_facts":{"dc:contributor":["Milenkovic, Olgica"],"dc:creator":["Rana, Vishal"],"dc:date":["2021-09-17T01:10:35Z","2021-02-23","2021-05"],"dc:description":["DSpace SAF Submission Ingestion Package generated from Vireo submission #16175 on 2021-09-16 at 16:40:03","Made available in DSpace on 2021-09-17T01:10:35Z (GMT). No. of bitstreams: 4 RANA-THESIS-2021.pdf: 2056607 bytes, checksum: 3ab4339ddbd42eb62574f6b98cade434 (MD5) Supplementary_tables.xlsx: 33949 bytes, checksum: 5cf8eda9cf8909f4409183d2122637b5 (MD5) MS Thesis.zip: 6002493 bytes, checksum: 4e40b4fc03c803a23752422b7f73659e (MD5) LICENSE.txt: 4208 bytes, checksum: 7ab10df0f102fdcd50fb33f4cbae102a (MD5) Previous issue date: 2021-02-23","The problem of accurately estimating and characterizing different mutations in the viral genomes present within a population is of great importance in tracking and mitigating the spread of the virus and is made difficult by the lack of a sufficient number of sequenced genomes especially during the early stages of an outbreak. We consider the problem of determining the mutational support and distribution of mutations in the SARS-Cov-2 genome and its open reading frames (ORFs). The mutational support refers to the unknown number of sites that are mutated among all the viral strains present in a population. The support and distribution of mutations can be used to guide primer selection for RT PCR test kits, study the virulence of the virus, discover adaptation mechanisms deployed by the virus to evade the host immune system, as well as to identify new strains that might be circulating in the population early on. We propose new state-of-the-art polynomial estimation techniques using weighted and regularized Chebyshev approximations for small-sample mutational support estimation and we use a modified Good-Turing estimator for distribution estimation. Our differential analysis of mutations in various population subgroups (based on data retrieved from GISAID repository) revealed several important differences including those in the ORF6 and ORF7a regions for older versus younger patients, ORF1b and ORF10 regions for females versus males, and in several ORFs for Asia versus Europe and North America. We also found no significant mutations in the primer regions from ORF N chosen by CDC for RT-PCR test kits in any of the subpopulations, which is important for the reliability of the test results.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2021-09-16 without embargo terms","The student, Vishal Rana, accepted the attached license on 2021-02-23 at 11:50.","The student, Vishal Rana, submitted this Thesis for approval on 2021-02-23 at 12:13.","This Thesis was approved for publication on 2021-02-23 at 14:46."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/110417"],"dc:language":["en"],"dc:rights":["Copyright 2021 Vishal Rana"],"dc:subject":["Comparative ORF study","Good-Turing estimation","Mutation rates","SARS-Cov-2 Data analysis","Small-sample support estimation"],"dc:title":["Small-sample estimation of the mutational support and the distribution of mutations in the SARS-CoV-2 genome"],"dc:type":["Thesis","text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:50Z"}