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Developing a forensically relevant single-cell interpretation strategy for human identification

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TitleInfo
Title
Developing a forensically relevant single-cell interpretation strategy for human identification
Name (type = personal)
NamePart (type = family)
Gonzalez
NamePart (type = given)
Amanda J.
NamePart (type = date)
1985-
DisplayForm
Amanda Gonzalez
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Grgicak
NamePart (type = given)
Catherine M.
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Catherine M. Grgicak
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Shain
NamePart (type = given)
Daniel
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Daniel Shain
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Yakoby
NamePart (type = given)
Nir
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Nir Yakoby
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Camden Graduate School
Role
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school
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Text
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theses
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2019
DateOther (encoding = w3cdtf); (qualifier = exact); (type = degree)
2019-05
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2019
Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
Abstract
Biological evidence submitted to the forensic DNA laboratory contains cells from an unknown number of contributors in unknown proportions, resulting in profiles that are difficult to interpret.

Thus, recent efforts have focused on developing single-cell forensic DNA pipelines to deconvolve mixture signal by separating cells at the front end of processing. Single-cell signal, however, are often obfuscated by the presence of confounding signal such as false negative detection of alleles (i.e., drop-out); stutter, a polymerase chain reaction (PCR) artifact; and false positive detection of alleles (i.e., drop-in). Given the need to provide the weight-of-evidence against the accused, probabilistic characterization of the confounding single-cell artifacts is a necessity.

As such, 556 single-source, single-cell samples of known genotype were analyzed. The data were evaluated to determine if distributions associated with allele detection, stutter, and allelic drop-in were significantly different from those of bulk-processed samples. The results demonstrate that, in contrast to bulk-processed samples, allele detection is cell dependent. Like bulk-processed samples, stutter in the single-cell regime was found to be locus dependent; however, single-cell samples resulted in higher stutter ratios. As predicted, the frequency of allelic drop-in appeared consistent with that of bulk-processed samples. These findings suggest current state-of-the-art probabilistic systems are ill-equipped to evaluate single-cell evidence and new probabilistic constructs are required. The results of this study form the foundation from which these new inference systems may be developed.

Not only is probabilistic characterization of single-cell signal a necessity; practical implementation of a single-cell pipeline (i.e., that the cells can be effectively desorbed from common collection material such as cotton swabs) must be verified. Therefore, the second phase of this work focused on developing and accessing a protocol to desorb buccal cells from cotton-tipped applicators. To measure its efficacy, hemocytometry was used to determine the percent of cells recovered. The percent recovery of buccal cells appeared consistent with that of bulk-mixture extraction, demonstrating that a single-cell strategy is a viable alternative to the traditional forensic DNA pipeline.
Subject (authority = RUETD)
Topic
Biology
Subject (authority = ETD-LCSH)
Topic
Forensic genetics -- Mathematical models
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_9915
PhysicalDescription
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application/pdf
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text/xml
Extent
1 online resource (xiv, 56 pages) : illustrations
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
RelatedItem (type = host)
TitleInfo
Title
Camden Graduate School Electronic Theses and Dissertations
Identifier (type = local)
rucore10005600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/t3-tq0z-7w76
Genre (authority = ExL-Esploro)
ETD graduate
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Gonzalez
GivenName
Amanda
MiddleName
J.
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2019-04-26 18:35:14
AssociatedEntity
Name
Amanda J. Gonzalez
Role
Copyright holder
Affiliation
Rutgers University. Camden Graduate School
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.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

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2019-05-07T13:03:35
DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2019-05-07T13:03:35
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