{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/106113"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/106113","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients","abstract":"Sequencing followed by metagenomic analysis is an extremely promising method for broad, unbiased disease profiling of patients for disease surveillance and diagnosis. Here, we use two popular metagenomics tools in union, k-mer-based Kraken with reads and BLAST- and LCAbased MEGAN with assembled contiguous sequence. We analyze sequence from 463 febrile and afebrile patients from Sierra Leone before and during the 2014 Ebola virus outbreak. We find that co-infection with malaria is correlated with increased survival of Ebola virus patients, from 18% survival rate to 53%. We also explore the utility of and emphasize the need for both positive and negative controls to distinguish and remove noise and contaminants from real signal, especially to keep up with increasing sensitivity in sequencing.","abstract_html":"Sequencing followed by metagenomic analysis is an extremely promising method for broad, unbiased disease profiling of patients for disease surveillance and diagnosis. Here, we use two popular metagenomics tools in union, k-mer-based Kraken with reads and BLAST- and LCAbased MEGAN with assembled contiguous sequence. We analyze sequence from 463 febrile and afebrile patients from Sierra Leone before and during the 2014 Ebola virus outbreak. We find that co-infection with malaria is correlated with increased survival of Ebola virus patients, from 18% survival rate to 53%. We also explore the utility of and emphasize the need for both positive and negative controls to distinguish and remove noise and contaminants from real signal, especially to keep up with increasing sensitivity in sequencing.","abstract_has_math":false,"creators":["Krasilnikova, Lydia A"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Pardis Sabeti and Daniel Park"],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016","date_published":"2016","updated_at":"2026-07-22T22:21:20Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/106113","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Pardis Sabeti and Daniel Park"]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."]},{"key":"dc:creator","label":"Author","values":["Krasilnikova, Lydia A"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2016-12-22T16:29:32Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2016-12-22T16:29:32Z"]},{"key":"dc:date.issued","label":"Date","values":["2016"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrical Engineering and Computer Science."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/106113"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis: M. Eng. in Computer Science and Molecular Biology, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.","Cataloged from PDF version of thesis.","Includes bibliographical references (page 37)."]},{"key":"dc:description.abstract","label":"Abstract","values":["Sequencing followed by metagenomic analysis is an extremely promising method for broad, unbiased disease profiling of patients for disease surveillance and diagnosis. Here, we use two popular metagenomics tools in union, k-mer-based Kraken with reads and BLAST- and LCAbased MEGAN with assembled contiguous sequence. We analyze sequence from 463 febrile and afebrile patients from Sierra Leone before and during the 2014 Ebola virus outbreak. We find that co-infection with malaria is correlated with increased survival of Ebola virus patients, from 18% survival rate to 53%. We also explore the utility of and emphasize the need for both positive and negative controls to distinguish and remove noise and contaminants from real signal, especially to keep up with increasing sensitivity in sequencing."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M. Eng. in Computer Science and Molecular Biology"]},{"key":"dc:title","label":"Title","values":["Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients"]}]}],"canonical_facts":{"dc:contributor.advisor":["Pardis Sabeti and Daniel Park"],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:contributor.other":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:creator":["Krasilnikova, Lydia A"],"dc:date.accessioned":["2016-12-22T16:29:32Z"],"dc:date.available":["2016-12-22T16:29:32Z"],"dc:date.issued":["2016"],"dc:description":["Thesis: M. Eng. in Computer Science and Molecular Biology, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.","Cataloged from PDF version of thesis.","Includes bibliographical references (page 37)."],"dc:description.abstract":["Sequencing followed by metagenomic analysis is an extremely promising method for broad, unbiased disease profiling of patients for disease surveillance and diagnosis. Here, we use two popular metagenomics tools in union, k-mer-based Kraken with reads and BLAST- and LCAbased MEGAN with assembled contiguous sequence. We analyze sequence from 463 febrile and afebrile patients from Sierra Leone before and during the 2014 Ebola virus outbreak. We find that co-infection with malaria is correlated with increased survival of Ebola virus patients, from 18% survival rate to 53%. We also explore the utility of and emphasize the need for both positive and negative controls to distinguish and remove noise and contaminants from real signal, especially to keep up with increasing sensitivity in sequencing."],"dc:description.degree":["M. Eng. in Computer Science and Molecular Biology"],"dc:identifier.uri":["http://hdl.handle.net/1721.1/106113"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Electrical Engineering and Computer Science."],"dc:title":["Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:20Z"}