scholarly journals Detection of significantly differentially methylated regions in targeted bisulfite sequencing data

2013 ◽  
Vol 29 (13) ◽  
pp. 1647-1653 ◽  
Author(s):  
Katja Hebestreit ◽  
Martin Dugas ◽  
Hans-Ulrich Klein
Keyword(s):  
Bisulfite Sequencing ◽  
Sequencing Data ◽  
Differentially Methylated Regions ◽  
Targeted Bisulfite Sequencing ◽  
Bisulfite Sequencing Data

scholarly journals metilene: fast and sensitive calling of differentially methylated regions from bisulfite sequencing data

2015 ◽  
Vol 26 (2) ◽  
pp. 256-262 ◽  
Author(s):  
Frank Jühling ◽  
Helene Kretzmer ◽  
Stephan H. Bernhart ◽  
Christian Otto ◽  
Peter F. Stadler ◽  
...  
Keyword(s):  
Bisulfite Sequencing ◽  
Sequencing Data ◽  
Differentially Methylated Regions ◽  
Bisulfite Sequencing Data

scholarly journals Evaluating the Consistency of Gene Methylation in Liver Cancer Using Bisulfite Sequencing Data

2021 ◽  
Vol 9 ◽  
Author(s):  
Xubin Zheng ◽  
Qiong Wu ◽  
Haonan Wu ◽  
Kwong-Sak Leung ◽  
Man-Hon Wong ◽  
...  
Keyword(s):  
Liver Cancer ◽  
Dna Sequences ◽  
Bisulfite Sequencing ◽  
Differentially Methylated Region ◽  
Sequencing Data ◽  
Reduced Representation ◽  
Targeted Bisulfite Sequencing ◽  
Differentially Methylated Genes ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data

Bisulfite sequencing is considered as the gold standard approach for measuring DNA methylation, which acts as a pivotal part in regulating a variety of biological processes without changes in DNA sequences. In this study, we introduced the most prevalent methods for processing bisulfite sequencing data and evaluated the consistency of the data acquired from different measurements in liver cancer. Firstly, we introduced three commonly used bisulfite sequencing assays, i.e., reduced-representation bisulfite sequencing (RRBS), whole-genome bisulfite sequencing (WGBS), and targeted bisulfite sequencing (targeted BS). Next, we discussed the principles and compared different methods for alignment, quality assessment, methylation level scoring, and differentially methylated region identification. After that, we screened differential methylated genes in liver cancer through the three bisulfite sequencing assays and evaluated the consistency of their results. Ultimately, we compared bisulfite sequencing to 450 k beadchip and assessed the statistical similarity and functional association of differentially methylated genes (DMGs) among the four assays. Our results demonstrated that the DMGs measured by WGBS, RRBS, targeted BS and 450 k beadchip are consistently hypo-methylated in liver cancer with high functional similarity.

scholarly journals BiSulfite Bolt: A bisulfite sequencing analysis platform

GigaScience ◽  
2021 ◽  
Vol 10 (5) ◽  
Author(s):  
Colin Farrell ◽  
Michael Thompson ◽  
Anela Tosevska ◽  
Adewale Oyetunde ◽  
Matteo Pellegrini
Keyword(s):  
Data Aggregation ◽  
Bisulfite Sequencing ◽  
Low Complexity ◽  
Sequencing Analysis ◽  
Command Line ◽  
Sequencing Data ◽  
Bisulfite Sequencing Data ◽  
Analysis Platform ◽  
Python Package ◽  
Bisulfite Sequencing Analysis

Abstract Background Bisulfite sequencing is commonly used to measure DNA methylation. Processing bisulfite sequencing data is often challenging owing to the computational demands of mapping a low-complexity, asymmetrical library and the lack of a unified processing toolset to produce an analysis-ready methylation matrix from read alignments. To address these shortcomings, we have developed BiSulfite Bolt (BSBolt), a fast and scalable bisulfite sequencing analysis platform. BSBolt performs a pre-alignment sequencing read assessment step to improve efficiency when handling asymmetrical bisulfite sequencing libraries. Findings We evaluated BSBolt against simulated and real bisulfite sequencing libraries. We found that BSBolt provides accurate and fast bisulfite sequencing alignments and methylation calls. We also compared BSBolt to several existing bisulfite alignment tools and found BSBolt outperforms Bismark, BSSeeker2, BISCUIT, and BWA-Meth based on alignment accuracy and methylation calling accuracy. Conclusion BSBolt offers streamlined processing of bisulfite sequencing data through an integrated toolset that offers support for simulation, alignment, methylation calling, and data aggregation. BSBolt is implemented as a Python package and command line utility for flexibility when building informatics pipelines. BSBolt is available at https://github.com/NuttyLogic/BSBolt under an MIT license.

scholarly journals A Bayesian Approach for Analysis of Whole-Genome Bisulfite Sequencing Data Identifies Disease-Associated Changes in DNA Methylation

Genetics ◽  
2017 ◽  
Vol 205 (4) ◽  
pp. 1443-1458 ◽  
Author(s):  
Owen J. L. Rackham ◽  
Sarah R. Langley ◽  
Thomas Oates ◽  
Eleni Vradi ◽  
Nathan Harmston ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bayesian Approach ◽  
Bisulfite Sequencing ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Genome Bisulfite Sequencing ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data

scholarly journals GBSA: a comprehensive software for analysing whole genome bisulfite sequencing data

2012 ◽  
Vol 41 (4) ◽  
pp. e55-e55 ◽  
Author(s):  
Touati Benoukraf ◽  
Sarawut Wongphayak ◽  
Luqman Hakim Abdul Hadi ◽  
Mengchu Wu ◽  
Richie Soong
Keyword(s):  
Bisulfite Sequencing ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Genome Bisulfite Sequencing ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data
Sign in / Sign up

Export Citation Format

Share Document