Metagenomic investigation of co-infections of Ebola virus disease and Lassa fever patients
Name
965796036-MIT.pdf
Description
Full printable version
Size
25.44 MB
Format
Adobe PDF
Checksum (MD5)
6200e28f8391fb7f83ff8d3dfd6c83b0
Author(s)
Krasilnikova, Lydia A
Advisor(s)
Pardis Sabeti and Daniel Park
Date Issued
2016
Publisher
Massachusetts Institute of Technology
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.
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).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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