Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/39496
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.date.accessioned | 2019-02-05T10:02:43Z | - |
dc.date.available | 2019-02-05T10:02:43Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Pullicino, K. (2018). A MapReduce approach to genome alignment (Master's dissertation). | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/39496 | - |
dc.description | M.SC.ARTIFICIAL INTELLIGENCE | en_GB |
dc.description.abstract | Recent years brought an enormous growth in DNA sequencing capacity and speed, thanks to the application of Next-Generation Sequencing (NGS) technologies. The alignment of read sequences to a given reference genome is crucial for further diagnostic downstream analysis. Finding the optimal alignment of short DNA reads from a biological sample to a reference human genome, requires big data techniques, since reads' size are in the region of 200GB. In this dissertation we present two approaches to perform distributed sequence alignment of genomic data based on the MapReduce programming paradigm. MR-BWA presents a novel approach in distributing BWA in a different manner than existing work. BWA is an industry standard software used for genomic reads alignment. MR-BWT-FM presents low level optimizations on suffix array and BWT creation which are used to create a custom FM-Index which in turn is used for distributed genome sequence alignment. Output generated by the application generates insights and charts about the results. We evaluate the performance and correctness of both approaches by comparing our output with that of similar tools, using standard datasets from the 1000 Genomes Project. Performance and correctness results for both distributed approaches are comparable with similar tools, whilst the final custom FM-Index size is smaller than the standard BWA index size. The source code of the software described in this dissertation is publicly available at https://github.com/kpullu/msc. | en_GB |
dc.language.iso | en | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | DNA | en_GB |
dc.subject | Gene mapping | en_GB |
dc.subject | Genomics -- Methods | en_GB |
dc.title | A MapReduce approach to genome alignment | en_GB |
dc.type | bachelorThesis | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.publisher.institution | University of Malta | en_GB |
dc.publisher.department | Faculty of Information and Communication Technology. Department of Artificial Intelligence | en_GB |
dc.description.reviewed | N/A | en_GB |
dc.contributor.creator | Pullicino, Karl | - |
Appears in Collections: | Dissertations - FacICT - 2018 Dissertations - FacICTAI - 2018 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
18MAIPT07.pdf Restricted Access | 2.15 MB | Adobe PDF | View/Open Request a copy |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.