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Applications of the mixed linear model in genome-wide association studies and small RNA motif discovery
Descriptive
TitleInfo
Title
Applications of the mixed linear model in genome-wide association studies and small RNA motif discovery
Name
(type = personal)
NamePart
(type = family)
Diao
NamePart
(type = given)
Liyang
NamePart
(type = date)
1986-
DisplayForm
Liyang Diao
Role
RoleTerm
(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Chen
NamePart
(type = given)
Kevin C.
DisplayForm
Kevin C. Chen
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
chair
Name
(type = personal)
NamePart
(type = family)
Mischaikow
NamePart
(type = given)
Konstantin
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Konstantin Mischaikow
Affiliation
Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Olson
NamePart
(type = given)
Wilma
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Wilma Olson
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Xing
NamePart
(type = given)
Jinchuan
DisplayForm
Jinchuan Xing
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
outside member
Name
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NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
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NamePart
Graduate School - New Brunswick
Role
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(authority = RULIB)
school
TypeOfResource
Text
Genre
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theses
OriginInfo
DateCreated
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2014
DateOther
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2014-10
CopyrightDate
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2014
Place
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(type = code)
xx
Language
LanguageTerm
(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
If sheer number of papers published is indicative of anything, it suggests that the age of genome-wide association studies, or GWAS, is here to stay. However, in spite of the influx of data, several issues remain, one of which is the presence of confounding factors caused by relatedness within the study sample. This can cause many false positive results. In recent years, the use of mixed linear models to correct for unknown types of relatedness, i.e. "cryptic relatedness", has been very popular. While this model has been shown to be successful in some cases, here we address the feasibility of performing GWAS in a highly structured population such as Saccharomyces cerevisiae, and find that the inclusion of fixed local ancestry covariates can sometimes lend a study more power. Furthermore, we explore the application of mixed linear models in a different type of biological problem of discovering motifs associated with active microRNAs. While there exist several algorithms for miRNA motif discovery, only a few consider background sequence composition of the 3' UTR binding site in addition to seed sequence motif enrichment, which is known to factor into miNRA binding efficacy. The methods that do account for 3' UTR sequence composition do so by rescoring motif counts based on the background UTR sequence in which it appears. Though computationally efficient, these methods are unable to simultaneously compare both gene expression values and UTR sequence, which our method, named MixMir, is able to do, with favorable results. When compared to the simple linear model, as well as existing motif discovery algorithms, MixMir is able to rank true motifs more highly in multiple data sets. Such computational methods are biologically significant because although it is possible to sequence small RNAs in a sample, their expression may not be perfectly correlated with the size of their effect, which is what we observed.
Subject
(authority = RUETD)
Topic
Computational Biology and Molecular Biophysics
Subject
(authority = ETD-LCSH)
Topic
Linear models (Statistics)
Subject
(authority = ETD-LCSH)
Topic
Genomes--Analysis
RelatedItem
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
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ETD
Identifier
ETD_5857
PhysicalDescription
Form
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electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (x, 126 p. : ill.)
Note
(type = degree)
Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Liyang Diao
RelatedItem
(type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
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rucore19991600001
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T33X8547
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
Diao
GivenName
Liyang
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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(qualifier = exact);
(point = start)
2014-09-18 19:11:08
AssociatedEntity
Name
Liyang Diao
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
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(qualifier = exact);
(point = start)
2014-10-31
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = end)
2016-10-30
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after October 30th, 2016.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
RULTechMD
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ContentModel
ETD
OperatingSystem
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windows xp
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Statistical Profile