Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients

Thesis: M. Eng. in Computer Science and Molecular Biology, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.

Bibliographic Details
Main Author: Krasilnikova, Lydia A
Other Authors: Pardis Sabeti and Daniel Park
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2016
Subjects:
Online Access:http://hdl.handle.net/1721.1/106113
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author Krasilnikova, Lydia A
author2 Pardis Sabeti and Daniel Park
author_facet Pardis Sabeti and Daniel Park
Krasilnikova, Lydia A
author_sort Krasilnikova, Lydia A
collection MIT
description Thesis: M. Eng. in Computer Science and Molecular Biology, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
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spelling mit-1721.1/1061132019-04-11T07:44:57Z Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients Krasilnikova, Lydia A Pardis Sabeti and Daniel Park Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. 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). 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. by Lydia A. Krasilnikova. M. Eng. in Computer Science and Molecular Biology 2016-12-22T16:29:32Z 2016-12-22T16:29:32Z 2016 2016 Thesis http://hdl.handle.net/1721.1/106113 965796036 eng 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. http://dspace.mit.edu/handle/1721.1/7582 384 pages application/pdf Massachusetts Institute of Technology
spellingShingle Electrical Engineering and Computer Science.
Krasilnikova, Lydia A
Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients
title Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients
title_full Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients
title_fullStr Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients
title_full_unstemmed Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients
title_short Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients
title_sort metagenomic investigation of co infections of ebola virus disease and lassa fever patients
topic Electrical Engineering and Computer Science.
url http://hdl.handle.net/1721.1/106113
work_keys_str_mv AT krasilnikovalydiaa metagenomicinvestigationofcoinfectionsofebolavirusdiseaseandlassafeverpatients