ingest
cdrApp
2018-06-13T14:45:33.888Z
51cd2fe2-3fd7-401f-a923-a97bc3db68a2
modifyDatastreamByValue
RELS-EXT
fedoraAdmin
2018-06-13T14:54:36.647Z
Setting exclusive relation
addDatastream
MD_TECHNICAL
fedoraAdmin
2018-06-13T14:54:51.110Z
Adding technical metadata derived by FITS
addDatastream
MD_FULL_TEXT
fedoraAdmin
2018-06-13T14:55:23.667Z
Adding full text metadata extracted by Apache Tika
modifyDatastreamByValue
RELS-EXT
fedoraAdmin
2018-06-13T14:55:35.679Z
Setting exclusive relation
modifyDatastreamByValue
MD_DESCRIPTIVE
cdrApp
2018-07-16T21:54:59.060Z
modifyDatastreamByValue
MD_DESCRIPTIVE
cdrApp
2018-07-18T17:26:49.971Z
modifyDatastreamByValue
MD_DESCRIPTIVE
cdrApp
2018-08-22T16:12:50.430Z
modifyDatastreamByValue
MD_DESCRIPTIVE
cdrApp
2018-09-28T19:04:34.861Z
modifyDatastreamByValue
MD_DESCRIPTIVE
cdrApp
2018-10-12T17:50:49.147Z
modifyDatastreamByValue
MD_DESCRIPTIVE
cdrApp
2019-03-22T21:13:35.166Z
Daniel
Oreper
Author
Curriculum in Bioinformatics and Computational Biology
School of Medicine
Computational methods for studying parent-of-origin effects via reciprocal mouse crosses
Imprinted genes have been linked with diseases ranging from cancer, to metabolic syndromes, to psychiatric illness. With regard to psychiatric illness in particular, numerous lines of evidence, both from human and mouse studies, suggest imprinted genes affect behavior along with brain development and function. Nonetheless, the effect of imprinted genes on most complex traits is not well characterized. Moreover, the architecture of environment-by-imprinting effects is even less well-understood.
The lack of characterization is likely due to the general difficulty of observing ``parent-of-origin effects'' (POEs), which typically arise in mammals from maternal effects--or from imprinting. To study POE/environment-by-POE, we can employ a relatively neglected but maximally powerful POE-detection system: the reciprocal cross (RX). Towards this end, we develop and apply computational methods for designing and analyzing RX experiments. Here, these techniques are applied in the context of RXs of inbred lines of mice, with a focus on behavior--but these techniques could be similarly employed in any model organism subject to POE, and on any complex trait.
The first set of methods focuses on the analysis of expression and behavioral data from RXs of a single pair of classical inbred mouse strains, with offspring exposed in utero to various diets. In this analysis, we detected dozens of POE/diet-by-POE on gene expression, a handful of similar effects on behavior, and a possible connection between POE on expression and behavior. Motivated by these results, we engaged in a similar but larger study, the CC-POE, in which we RXd multiple pairs of inbred lines drawn from the Collaborative Cross (CC)--a panel of multiparental recombinant inbred mouse strains. To aid in the CC-POE design, we developed a novel method for selecting an optimal set of reciprocal crosses: the Reciprocal Cross Explorer. Finally, with the goal of analyzing CC-POE data, we develop a resource for variant imputation in the CC: the Inbred Strain Variant Database (available online at https://isvdb.unc.edu ). Taken together, methods developed in this dissertation represent progress towards a new way of studying POEs via RXs.
Spring 2018
2018
Bioinformatics
Genetics
Neurosciences
behavior, Collaborative Cross, parent-of-origin effect, perinatal diet, reciprocal cross, Rexplorer
eng
Doctor of Philosophy
Dissertation
University of North Carolina at Chapel Hill Graduate School
Degree granting institution
Bioinformatics and Computational Biology
William
Valdar
Thesis advisor
Daniel
Pomp
Thesis advisor
Leonard
McMillan
Thesis advisor
Fernando
Pardo-Manuel De Villena
Thesis advisor
Michael
Love
Thesis advisor
text
Daniel
Oreper
Author
Curriculum in Bioinformatics and Computational Biology
School of Medicine
Computational methods for studying parent-of-origin effects via reciprocal mouse crosses
Imprinted genes have been linked with diseases ranging from cancer, to metabolic syndromes, to psychiatric illness. With regard to psychiatric illness in particular, numerous lines of evidence, both from human and mouse studies, suggest imprinted genes affect behavior along with brain development and function. Nonetheless, the effect of imprinted genes on most complex traits is not well characterized. Moreover, the architecture of environment-by-imprinting effects is even less well-understood.
The lack of characterization is likely due to the general difficulty of observing ``parent-of-origin effects'' (POEs), which typically arise in mammals from maternal effects--or from imprinting. To study POE/environment-by-POE, we can employ a relatively neglected but maximally powerful POE-detection system: the reciprocal cross (RX). Towards this end, we develop and apply computational methods for designing and analyzing RX experiments. Here, these techniques are applied in the context of RXs of inbred lines of mice, with a focus on behavior--but these techniques could be similarly employed in any model organism subject to POE, and on any complex trait.
The first set of methods focuses on the analysis of expression and behavioral data from RXs of a single pair of classical inbred mouse strains, with offspring exposed in utero to various diets. In this analysis, we detected dozens of POE/diet-by-POE on gene expression, a handful of similar effects on behavior, and a possible connection between POE on expression and behavior. Motivated by these results, we engaged in a similar but larger study, the CC-POE, in which we RXd multiple pairs of inbred lines drawn from the Collaborative Cross (CC)--a panel of multiparental recombinant inbred mouse strains. To aid in the CC-POE design, we developed a novel method for selecting an optimal set of reciprocal crosses: the Reciprocal Cross Explorer. Finally, with the goal of analyzing CC-POE data, we develop a resource for variant imputation in the CC: the Inbred Strain Variant Database (available online at https://isvdb.unc.edu ). Taken together, methods developed in this dissertation represent progress towards a new way of studying POEs via RXs.
Spring 2018
2018
Bioinformatics
Genetics
Neurosciences
behavior, Collaborative Cross, parent-of-origin effect, perinatal diet, reciprocal cross, Rexplorer
eng
Doctor of Philosophy
Dissertation
University of North Carolina at Chapel Hill Graduate School
Degree granting institution
Bioinformatics and Computational Biology
William
Valdar
Thesis advisor
Daniel
Pomp
Thesis advisor
Leonard
McMillan
Thesis advisor
Fernando
Pardo-Manuel De Villena
Thesis advisor
Michael
Love
Thesis advisor
text
Daniel
Oreper
Author
Curriculum in Bioinformatics and Computational Biology
School of Medicine
Computational methods for studying parent-of-origin effects via reciprocal mouse crosses
Imprinted genes have been linked with diseases ranging from cancer, to metabolic syndromes, to psychiatric illness. With regard to psychiatric illness in particular, numerous lines of evidence, both from human and mouse studies, suggest imprinted genes affect behavior along with brain development and function. Nonetheless, the effect of imprinted genes on most complex traits is not well characterized. Moreover, the architecture of environment-by-imprinting effects is even less well-understood.
The lack of characterization is likely due to the general difficulty of observing ``parent-of-origin effects'' (POEs), which typically arise in mammals from maternal effects--or from imprinting. To study POE/environment-by-POE, we can employ a relatively neglected but maximally powerful POE-detection system: the reciprocal cross (RX). Towards this end, we develop and apply computational methods for designing and analyzing RX experiments. Here, these techniques are applied in the context of RXs of inbred lines of mice, with a focus on behavior--but these techniques could be similarly employed in any model organism subject to POE, and on any complex trait.
The first set of methods focuses on the analysis of expression and behavioral data from RXs of a single pair of classical inbred mouse strains, with offspring exposed in utero to various diets. In this analysis, we detected dozens of POE/diet-by-POE on gene expression, a handful of similar effects on behavior, and a possible connection between POE on expression and behavior. Motivated by these results, we engaged in a similar but larger study, the CC-POE, in which we RXd multiple pairs of inbred lines drawn from the Collaborative Cross (CC)--a panel of multiparental recombinant inbred mouse strains. To aid in the CC-POE design, we developed a novel method for selecting an optimal set of reciprocal crosses: the Reciprocal Cross Explorer. Finally, with the goal of analyzing CC-POE data, we develop a resource for variant imputation in the CC: the Inbred Strain Variant Database (available online at https://isvdb.unc.edu ). Taken together, methods developed in this dissertation represent progress towards a new way of studying POEs via RXs.
Spring 2018
2018
Bioinformatics
Genetics
Neurosciences
behavior, Collaborative Cross, parent-of-origin effect, perinatal diet, reciprocal cross, Rexplorer
eng
Doctor of Philosophy
Dissertation
University of North Carolina at Chapel Hill Graduate School
Degree granting institution
Bioinformatics and Computational Biology
William
Valdar
Thesis advisor
Daniel
Pomp
Thesis advisor
Leonard
McMillan
Thesis advisor
Fernando
Pardo-Manuel De Villena
Thesis advisor
Michael
Love
Thesis advisor
text
Daniel
Oreper
Author
Curriculum in Bioinformatics and Computational Biology
School of Medicine
Computational methods for studying parent-of-origin effects via reciprocal mouse crosses
Imprinted genes have been linked with diseases ranging from cancer, to metabolic syndromes, to psychiatric illness. With regard to psychiatric illness in particular, numerous lines of evidence, both from human and mouse studies, suggest imprinted genes affect behavior along with brain development and function. Nonetheless, the effect of imprinted genes on most complex traits is not well characterized. Moreover, the architecture of environment-by-imprinting effects is even less well-understood.
The lack of characterization is likely due to the general difficulty of observing ``parent-of-origin effects'' (POEs), which typically arise in mammals from maternal effects--or from imprinting. To study POE/environment-by-POE, we can employ a relatively neglected but maximally powerful POE-detection system: the reciprocal cross (RX). Towards this end, we develop and apply computational methods for designing and analyzing RX experiments. Here, these techniques are applied in the context of RXs of inbred lines of mice, with a focus on behavior--but these techniques could be similarly employed in any model organism subject to POE, and on any complex trait.
The first set of methods focuses on the analysis of expression and behavioral data from RXs of a single pair of classical inbred mouse strains, with offspring exposed in utero to various diets. In this analysis, we detected dozens of POE/diet-by-POE on gene expression, a handful of similar effects on behavior, and a possible connection between POE on expression and behavior. Motivated by these results, we engaged in a similar but larger study, the CC-POE, in which we RXd multiple pairs of inbred lines drawn from the Collaborative Cross (CC)--a panel of multiparental recombinant inbred mouse strains. To aid in the CC-POE design, we developed a novel method for selecting an optimal set of reciprocal crosses: the Reciprocal Cross Explorer. Finally, with the goal of analyzing CC-POE data, we develop a resource for variant imputation in the CC: the Inbred Strain Variant Database (available online at https://isvdb.unc.edu ). Taken together, methods developed in this dissertation represent progress towards a new way of studying POEs via RXs.
Spring 2018
2018
Bioinformatics
Genetics
Neurosciences
behavior, Collaborative Cross, parent-of-origin effect, perinatal diet, reciprocal cross, Rexplorer
eng
Doctor of Philosophy
Dissertation
Bioinformatics and Computational Biology
William
Valdar
Thesis advisor
Daniel
Pomp
Thesis advisor
Leonard
McMillan
Thesis advisor
Fernando
Pardo-Manuel De Villena
Thesis advisor
Michael
Love
Thesis advisor
text
University of North Carolina at Chapel Hill
Degree granting institution
Daniel
Oreper
Creator
Curriculum in Bioinformatics and Computational Biology
School of Medicine
Computational methods for studying parent-of-origin effects via reciprocal mouse crosses
Imprinted genes have been linked with diseases ranging from cancer, to metabolic syndromes, to psychiatric illness. With regard to psychiatric illness in particular, numerous lines of evidence, both from human and mouse studies, suggest imprinted genes affect behavior along with brain development and function. Nonetheless, the effect of imprinted genes on most complex traits is not well characterized. Moreover, the architecture of environment-by-imprinting effects is even less well-understood.
The lack of characterization is likely due to the general difficulty of observing ``parent-of-origin effects'' (POEs), which typically arise in mammals from maternal effects--or from imprinting. To study POE/environment-by-POE, we can employ a relatively neglected but maximally powerful POE-detection system: the reciprocal cross (RX). Towards this end, we develop and apply computational methods for designing and analyzing RX experiments. Here, these techniques are applied in the context of RXs of inbred lines of mice, with a focus on behavior--but these techniques could be similarly employed in any model organism subject to POE, and on any complex trait.
The first set of methods focuses on the analysis of expression and behavioral data from RXs of a single pair of classical inbred mouse strains, with offspring exposed in utero to various diets. In this analysis, we detected dozens of POE/diet-by-POE on gene expression, a handful of similar effects on behavior, and a possible connection between POE on expression and behavior. Motivated by these results, we engaged in a similar but larger study, the CC-POE, in which we RXd multiple pairs of inbred lines drawn from the Collaborative Cross (CC)--a panel of multiparental recombinant inbred mouse strains. To aid in the CC-POE design, we developed a novel method for selecting an optimal set of reciprocal crosses: the Reciprocal Cross Explorer. Finally, with the goal of analyzing CC-POE data, we develop a resource for variant imputation in the CC: the Inbred Strain Variant Database (available online at https://isvdb.unc.edu ). Taken together, methods developed in this dissertation represent progress towards a new way of studying POEs via RXs.
Bioinformatics
Genetics
Neurosciences
behavior; Collaborative Cross; parent-of-origin effect; perinatal diet; reciprocal cross; Rexplorer
eng
Doctor of Philosophy
Dissertation
Bioinformatics and Computational Biology
William
Valdar
Thesis advisor
Daniel
Pomp
Thesis advisor
Leonard
McMillan
Thesis advisor
Fernando
Pardo-Manuel De Villena
Thesis advisor
Michael
Love
Thesis advisor
text
University of North Carolina at Chapel Hill
Degree granting institution
2018
2018-05
Daniel
Oreper
Author
Curriculum in Bioinformatics and Computational Biology
School of Medicine
Computational methods for studying parent-of-origin effects via reciprocal mouse crosses
Imprinted genes have been linked with diseases ranging from cancer, to metabolic syndromes, to psychiatric illness. With regard to psychiatric illness in particular, numerous lines of evidence, both from human and mouse studies, suggest imprinted genes affect behavior along with brain development and function. Nonetheless, the effect of imprinted genes on most complex traits is not well characterized. Moreover, the architecture of environment-by-imprinting effects is even less well-understood.
The lack of characterization is likely due to the general difficulty of observing ``parent-of-origin effects'' (POEs), which typically arise in mammals from maternal effects--or from imprinting. To study POE/environment-by-POE, we can employ a relatively neglected but maximally powerful POE-detection system: the reciprocal cross (RX). Towards this end, we develop and apply computational methods for designing and analyzing RX experiments. Here, these techniques are applied in the context of RXs of inbred lines of mice, with a focus on behavior--but these techniques could be similarly employed in any model organism subject to POE, and on any complex trait.
The first set of methods focuses on the analysis of expression and behavioral data from RXs of a single pair of classical inbred mouse strains, with offspring exposed in utero to various diets. In this analysis, we detected dozens of POE/diet-by-POE on gene expression, a handful of similar effects on behavior, and a possible connection between POE on expression and behavior. Motivated by these results, we engaged in a similar but larger study, the CC-POE, in which we RXd multiple pairs of inbred lines drawn from the Collaborative Cross (CC)--a panel of multiparental recombinant inbred mouse strains. To aid in the CC-POE design, we developed a novel method for selecting an optimal set of reciprocal crosses: the Reciprocal Cross Explorer. Finally, with the goal of analyzing CC-POE data, we develop a resource for variant imputation in the CC: the Inbred Strain Variant Database (available online at https://isvdb.unc.edu ). Taken together, methods developed in this dissertation represent progress towards a new way of studying POEs via RXs.
Spring 2018
2018
Bioinformatics
Genetics
Neurosciences
behavior, Collaborative Cross, parent-of-origin effect, perinatal diet, reciprocal cross, Rexplorer
eng
Doctor of Philosophy
Dissertation
University of North Carolina at Chapel Hill Graduate School
Degree granting institution
Bioinformatics and Computational Biology
William
Valdar
Thesis advisor
Daniel
Pomp
Thesis advisor
Leonard
McMillan
Thesis advisor
Fernando
Pardo-Manuel De Villena
Thesis advisor
Michael
Love
Thesis advisor
text
Daniel
Oreper
Creator
Curriculum in Bioinformatics and Computational Biology
School of Medicine
Computational methods for studying parent-of-origin effects via reciprocal mouse crosses
Imprinted genes have been linked with diseases ranging from cancer, to metabolic syndromes, to psychiatric illness. With regard to psychiatric illness in particular, numerous lines of evidence, both from human and mouse studies, suggest imprinted genes affect behavior along with brain development and function. Nonetheless, the effect of imprinted genes on most complex traits is not well characterized. Moreover, the architecture of environment-by-imprinting effects is even less well-understood.
The lack of characterization is likely due to the general difficulty of observing ``parent-of-origin effects'' (POEs), which typically arise in mammals from maternal effects--or from imprinting. To study POE/environment-by-POE, we can employ a relatively neglected but maximally powerful POE-detection system: the reciprocal cross (RX). Towards this end, we develop and apply computational methods for designing and analyzing RX experiments. Here, these techniques are applied in the context of RXs of inbred lines of mice, with a focus on behavior--but these techniques could be similarly employed in any model organism subject to POE, and on any complex trait.
The first set of methods focuses on the analysis of expression and behavioral data from RXs of a single pair of classical inbred mouse strains, with offspring exposed in utero to various diets. In this analysis, we detected dozens of POE/diet-by-POE on gene expression, a handful of similar effects on behavior, and a possible connection between POE on expression and behavior. Motivated by these results, we engaged in a similar but larger study, the CC-POE, in which we RXd multiple pairs of inbred lines drawn from the Collaborative Cross (CC)--a panel of multiparental recombinant inbred mouse strains. To aid in the CC-POE design, we developed a novel method for selecting an optimal set of reciprocal crosses: the Reciprocal Cross Explorer. Finally, with the goal of analyzing CC-POE data, we develop a resource for variant imputation in the CC: the Inbred Strain Variant Database (available online at https://isvdb.unc.edu ). Taken together, methods developed in this dissertation represent progress towards a new way of studying POEs via RXs.
2018-05
2018
Bioinformatics
Genetics
Neurosciences
behavior; Collaborative Cross; parent-of-origin effect; perinatal diet; reciprocal cross; Rexplorer
eng
Doctor of Philosophy
Dissertation
University of North Carolina at Chapel Hill Graduate School
Degree granting institution
William
Valdar
Thesis advisor
Daniel
Pomp
Thesis advisor
Leonard
McMillan
Thesis advisor
Fernando
Pardo-Manuel De Villena
Thesis advisor
Michael
Love
Thesis advisor
text
Oreper_unc_0153D_17602.pdf
uuid:4cc65024-e5bf-4dd3-8696-ac95b15c3351
2020-06-13T00:00:00
2018-04-06T19:06:46Z
proquest
application/pdf
6768085