Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

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 (Unpublished)

[img]
Preview
PDF
Submitted Version

Download (485kB) | Preview

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.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Jiang, Yanyaj12@pitt.eduyaj12
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorPark, Yongseokyongpark@pitt.eduyongpark
Committee MemberMarques, Ernestomarques@pitt.edumarques
Committee MemberTang, Lulutang@pitt.edulutang
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: Graduate 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

Metrics

Monthly Views for the past 3 years

Plum Analytics


Actions (login required)

View Item View Item