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Improving genome assembly by identifying reliable sequencing data

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TitleInfo
Title
Improving genome assembly by identifying reliable sequencing data
Name (type = personal)
NamePart (type = family)
Roy
NamePart (type = given)
Rajat Shuvro
NamePart (type = date)
1983-
DisplayForm
Rajat Shuvro Roy
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Schliep
NamePart (type = given)
Alexander
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Alexander Schliep
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Bhattacharya
NamePart (type = given)
Debashish
DisplayForm
Debashish Bhattacharya
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
co-chair
Name (type = personal)
NamePart (type = family)
Chen
NamePart (type = given)
Kevin
DisplayForm
Kevin Chen
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Farach-Colton
NamePart (type = given)
Martin
DisplayForm
Martin Farach-Colton
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Grigoriev
NamePart (type = given)
Andrey
DisplayForm
Andrey Grigoriev
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2014
DateOther (qualifier = exact); (type = degree)
2014-10
CopyrightDate (encoding = w3cdtf)
2014
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
De novo Genome assembly and k-mer frequency counting are two of the classical prob- lems of Bioinformatics. k-mer counting helps to identify genomic k-mers from sequenced reads which may then inform read correction or genome assembly. Genome assembly has two major subproblems: contig construction and scaffolding. A contig is a continu- ous sub-sequence of the genome assembled from sequencing reads. Scaffolding attempts to construct a linear sequence of contigs (with possible gaps in between) using paired reads (two reads whose distance on the genome is approximately known). In this the- sis I will present a new computationally efficient tool for identifying frequent k-mers which are more likely to be genomic, and a set of linear inequalities which can improve scaffolding (which is known to be NP-hard) by identifying reliable paired reads. Identifying reliable k-mers from Whole Genome Amplification (WGA) data is more challenging compared to multi-cell data due to the coverage variation introduced by the amplification step (MDA, MALBEC, etc.), which implies that applying a simple k- mer frequency cutoff is unreasonable. We observed that with sufficient coverage, using partial reads (read prefix of a certain length) of length approximately twice or less than that of the k-mer length recovers a large proportion of genomic k-mers while keeping the proportion of erroneous k-mers low. We show that using partial reads for assembly ii and gene prediction recovers a significant proportion of genes and propose to use this approach for rapid pathogen detection in combination with Single Cell Genomics (SCG). Thanks to SCG, it is now possible to isolate one single cell from environmental sam- ple, extract its DNA and perform genetic sequencing without any need for culturing the cell in the lab. We show that current bioinformatic tools are capable of charac- terizing a novel organism by producing a draft genome assembly and gene annotation from single cell data of a MAST-4 stramenopile. This demonstrates the potential of SCG for genetic study of the vast majority of environmental organisms that has so far eluded scientists as they cannot be brought into culture, typically a necessity for future studies.
Subject (authority = RUETD)
Topic
Computer Science
Subject (authority = ETD-LCSH)
Topic
Genomes--Analysis
Subject (authority = ETD-LCSH)
Topic
Gene amplification
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_5745
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xi, 120 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Rajat Shuvro Roy
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T37P911F
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Roy
GivenName
Rajat
MiddleName
Shuvro
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2014-07-29 12:20:14
AssociatedEntity
Name
Rajat Roy
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
RightsEvent
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2014-10-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2015-05-02
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after May 2nd, 2015.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
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