Two algorithmic problems in analyzing genetic and epigenetic variations

Single nucleotide polymorphism (SNP) is the most common type of genetic variations.Accurate detection of SNPs is crucial to many downstream studies. To detect SNPs, MALDI-TOF mass spectrometry combined with base-specific cleavage reactions has been employed in many experiments. A new SNP detecting al...

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Main Author: Sun, Ruimin
Other Authors: Chen Xin
Format: Theses and Dissertations
Language:English
Published: 2015
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Online Access:https://hdl.handle.net/10356/65312
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-653122023-02-28T23:45:04Z Two algorithmic problems in analyzing genetic and epigenetic variations Sun, Ruimin Chen Xin School of Physical and Mathematical Sciences DRNTU::Science::Mathematics::Discrete mathematics::Algorithms DRNTU::Science::Biological sciences::Genetics Single nucleotide polymorphism (SNP) is the most common type of genetic variations.Accurate detection of SNPs is crucial to many downstream studies. To detect SNPs, MALDI-TOF mass spectrometry combined with base-specific cleavage reactions has been employed in many experiments. A new SNP detecting algorithm is presented in the thesis, together with the performance evaluation of its implemented program called SnpMs.Results demonstrate that SnpMs has a high ability to detect SNP mutations accurately. Cytosine methylation plays an important role in many biological regulation processes. The current golden standard method for analyzing cytosine methylation is BS-Seq. In this thesis, a new tool called TAMeBS is introduced to align BS-Seq reads and estimate the methylation status of each cytosine. Experimental results on both simulated and real data showed that TAMeBS could detect many more uniquely best mapped reads while achieving a good balance between sensitivity and precision. DOCTOR OF PHILOSOPHY (SPMS) 2015-07-16T04:18:14Z 2015-07-16T04:18:14Z 2015 2015 Thesis Sun, R. (2015). Two algorithmic problems in analyzing genetic and epigenetic variations. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/65312 10.32657/10356/65312 en 134 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Science::Mathematics::Discrete mathematics::Algorithms
DRNTU::Science::Biological sciences::Genetics
spellingShingle DRNTU::Science::Mathematics::Discrete mathematics::Algorithms
DRNTU::Science::Biological sciences::Genetics
Sun, Ruimin
Two algorithmic problems in analyzing genetic and epigenetic variations
description Single nucleotide polymorphism (SNP) is the most common type of genetic variations.Accurate detection of SNPs is crucial to many downstream studies. To detect SNPs, MALDI-TOF mass spectrometry combined with base-specific cleavage reactions has been employed in many experiments. A new SNP detecting algorithm is presented in the thesis, together with the performance evaluation of its implemented program called SnpMs.Results demonstrate that SnpMs has a high ability to detect SNP mutations accurately. Cytosine methylation plays an important role in many biological regulation processes. The current golden standard method for analyzing cytosine methylation is BS-Seq. In this thesis, a new tool called TAMeBS is introduced to align BS-Seq reads and estimate the methylation status of each cytosine. Experimental results on both simulated and real data showed that TAMeBS could detect many more uniquely best mapped reads while achieving a good balance between sensitivity and precision.
author2 Chen Xin
author_facet Chen Xin
Sun, Ruimin
format Theses and Dissertations
author Sun, Ruimin
author_sort Sun, Ruimin
title Two algorithmic problems in analyzing genetic and epigenetic variations
title_short Two algorithmic problems in analyzing genetic and epigenetic variations
title_full Two algorithmic problems in analyzing genetic and epigenetic variations
title_fullStr Two algorithmic problems in analyzing genetic and epigenetic variations
title_full_unstemmed Two algorithmic problems in analyzing genetic and epigenetic variations
title_sort two algorithmic problems in analyzing genetic and epigenetic variations
publishDate 2015
url https://hdl.handle.net/10356/65312
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