Identifying chromatin interactions at high spatial resolution
Name
890132290-MIT.pdf
Description
Full printable version
Size
8.64 MB
Format
Adobe PDF
Checksum (MD5)
6adcd1f825d8cf51342750e8386017ec
Author(s)
Reeder, Christopher Campbell
Advisor(s)
David K. Gifford.
Date Issued
2014
Publisher
Massachusetts Institute of Technology
Abstract
This thesis presents two computational approaches for identifying chromatin interactions at high spatial resolution from ChIA-PET data. We introduce SPROUT which is a hierarchical probabilistic model that discovers high confidence interactions between binding events that it accurately locates. We apply SPROUT to CTCF ChIA-PET data from mouse embryonic stem cells and demonstrate that SPROUT discovers interactions that are more consistently supported by biological replicates than an alternative method called The ChIA-PET Tool. We also introduce GERM which models genome-wide distributions of protein occupancy without assuming that proteins can be accurately modeled as binding to point locations. We demonstrate that the locations that GERM identifies as interacting with transcription start sites of genes accurately align with ChIP-Seq data that are associated with active enhancers. Finally, we apply GERM to RNA Polymerase II ChIA-PET data from embryonic stem cells and motor neuron progenitors and make several observations about the usage of enhancers during motor neuron development.
Description
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 91-98).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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