Estimating DNA methylation levels for single-cell bisulfite sequencing (BS-SEQ) data

Jiang, Yan (2019) Estimating DNA methylation levels for single-cell bisulfite sequencing (BS-SEQ) data. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

DNA methylation is among the most studied epigenetic marks, with essential influence on biological growths, disease developments and potential public health benefits. Modified from the well-established measuring method bisulfite sequencing (BS-seq), single-cell bisulfite sequencing (scBS-seq) emerged recently to identify DNA methylation status within a single cell to profile and study heterogeneities better. With the unique features of the single-cell DNA methylation data, there is in need of developing a new method to assign the methylation status for each CpG site more accurately and precisely to represent the underlying truth. In this study, we propose a method using Bayes rule and compare its performance with a simple one-third rule method. A simulation study with various settings is conducted to compare the accuracy, precision and bias. The Bayes’ method shows an improvement in dimensions of accuracy and bias.

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Details

Item Type:	University of Pittsburgh ETD
Status:	Unpublished
Creators/Authors:	Creators Email Pitt Username ORCID Jiang, Yan yaj12@pitt.edu yaj12
ETD Committee:	Title Member Email Address Pitt Username ORCID Thesis Advisor Park, Yongseok yongpark@pitt.edu yongpark Committee Member Marques, Ernesto marques@pitt.edu marques Committee Member Tang, Lu lutang@pitt.edu lutang
Date:	25 June 2019
Date Type:	Publication
Defense Date:	12 April 2019
Approval Date:	25 June 2019
Submission Date:	4 April 2019
Access Restriction:	No restriction; Release the ETD for access worldwide immediately.
Number of Pages:	26
Institution:	University of Pittsburgh
Schools and Programs:	School of Public Health > Biostatistics
Degree:	MS - Master of Science
Thesis Type:	Master's Thesis
Refereed:	Yes
Uncontrolled Keywords:	DNA methylation; single-cell bisulfite sequencing (scBS-seq); Bayes’ rule
Date Deposited:	25 Jun 2019 14:40
Last Modified:	25 Jun 2019 14:40
URI:	http://d-scholarship.pitt.edu/id/eprint/36276

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