Literature DB >> 24064417

BSeQC: quality control of bisulfite sequencing experiments.

Xueqiu Lin1, Deqiang Sun, Benjamin Rodriguez, Qian Zhao, Hanfei Sun, Yong Zhang, Wei Li.   

Abstract

MOTIVATION: Bisulfite sequencing (BS-seq) has emerged as the gold standard to study genome-wide DNA methylation at single-nucleotide resolution. Quality control (QC) is a critical step in the analysis pipeline to ensure that BS-seq data are of high quality and suitable for subsequent analysis. Although several QC tools are available for next-generation sequencing data, most of them were not designed to handle QC issues specific to BS-seq protocols. Therefore, there is a strong need for a dedicated QC tool to evaluate and remove potential technical biases in BS-seq experiments.
RESULTS: We developed a package named BSeQC to comprehensively evaluate the quality of BS-seq experiments and automatically trim nucleotides with potential technical biases that may result in inaccurate methylation estimation. BSeQC takes standard SAM/BAM files as input and generates bias-free SAM/BAM files for downstream analysis. Evaluation based on real BS-seq data indicates that the use of the bias-free SAM/BAM file substantially improves the quantification of methylation level.
AVAILABILITY AND IMPLEMENTATION: BSeQC is freely available at: http://code.google.com/p/bseqc/.

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Year:  2013        PMID: 24064417      PMCID: PMC3842756          DOI: 10.1093/bioinformatics/btt548

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  12 in total

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Journal:  Nature       Date:  2011-12-14       Impact factor: 49.962

2.  htSeqTools: high-throughput sequencing quality control, processing and visualization in R.

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Journal:  Bioinformatics       Date:  2011-12-22       Impact factor: 6.937

3.  RSeQC: quality control of RNA-seq experiments.

Authors:  Liguo Wang; Shengqin Wang; Wei Li
Journal:  Bioinformatics       Date:  2012-06-27       Impact factor: 6.937

Review 4.  DNA methylation and human disease.

Authors:  Keith D Robertson
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Review 5.  Principles and challenges of genomewide DNA methylation analysis.

Authors:  Peter W Laird
Journal:  Nat Rev Genet       Date:  2010-03       Impact factor: 53.242

Review 6.  Analysing and interpreting DNA methylation data.

Authors:  Christoph Bock
Journal:  Nat Rev Genet       Date:  2012-10       Impact factor: 53.242

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Authors:  Benjamin P Berman; Daniel J Weisenberger; Joseph F Aman; Toshinori Hinoue; Zachary Ramjan; Yaping Liu; Houtan Noushmehr; Christopher P E Lange; Cornelis M van Dijk; Rob A E M Tollenaar; David Van Den Berg; Peter W Laird
Journal:  Nat Genet       Date:  2011-11-27       Impact factor: 38.330

8.  Human DNA methylomes at base resolution show widespread epigenomic differences.

Authors:  Ryan Lister; Mattia Pelizzola; Robert H Dowen; R David Hawkins; Gary Hon; Julian Tonti-Filippini; Joseph R Nery; Leonard Lee; Zhen Ye; Que-Minh Ngo; Lee Edsall; Jessica Antosiewicz-Bourget; Ron Stewart; Victor Ruotti; A Harvey Millar; James A Thomson; Bing Ren; Joseph R Ecker
Journal:  Nature       Date:  2009-10-14       Impact factor: 49.962

9.  BSMAP: whole genome bisulfite sequence MAPping program.

Authors:  Yuanxin Xi; Wei Li
Journal:  BMC Bioinformatics       Date:  2009-07-27       Impact factor: 3.169

10.  BSmooth: from whole genome bisulfite sequencing reads to differentially methylated regions.

Authors:  Kasper D Hansen; Benjamin Langmead; Rafael A Irizarry
Journal:  Genome Biol       Date:  2012-10-03       Impact factor: 13.583

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  20 in total

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Journal:  Sci Immunol       Date:  2019-04-26

2.  Statistical challenges in analyzing methylation and long-range chromosomal interaction data.

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Journal:  Stat Biosci       Date:  2016-03-07

3.  Urinary Nucleic Acid in Tumor: Bioinformatics Approaches.

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Journal:  Methods Mol Biol       Date:  2021

Review 4.  DNA methylation analysis in plants: review of computational tools and future perspectives.

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5.  Epigenome data release: a participant-centered approach to privacy protection.

Authors:  Stephanie O M Dyke; Warren A Cheung; Yann Joly; Ole Ammerpohl; Pavlo Lutsik; Mark A Rothstein; Maxime Caron; Stephan Busche; Guillaume Bourque; Lars Rönnblom; Paul Flicek; Stephan Beck; Martin Hirst; Henk Stunnenberg; Reiner Siebert; Jörn Walter; Tomi Pastinen
Journal:  Genome Biol       Date:  2015-07-17       Impact factor: 13.583

6.  MOABS: model based analysis of bisulfite sequencing data.

Authors:  Deqiang Sun; Yuanxin Xi; Benjamin Rodriguez; Hyun Jung Park; Pan Tong; Mira Meong; Margaret A Goodell; Wei Li
Journal:  Genome Biol       Date:  2014-02-24       Impact factor: 13.583

7.  Targeted alignment and end repair elimination increase alignment and methylation measure accuracy for reduced representation bisulfite sequencing data.

Authors:  Saurabh Baheti; Rahul Kanwar; Meike Goelzenleuchter; Jean-Pierre A Kocher; Andreas S Beutler; Zhifu Sun
Journal:  BMC Genomics       Date:  2016-02-27       Impact factor: 3.969

8.  HMPL: A Pipeline for Identifying Hemimethylation Patterns by Comparing Two Samples.

Authors:  Shuying Sun; Peng Li
Journal:  Cancer Inform       Date:  2015-08-09

9.  Large conserved domains of low DNA methylation maintained by Dnmt3a.

Authors:  Mira Jeong; Deqiang Sun; Min Luo; Yun Huang; Grant A Challen; Benjamin Rodriguez; Xiaotian Zhang; Lukas Chavez; Hui Wang; Rebecca Hannah; Sang-Bae Kim; Liubin Yang; Myunggon Ko; Rui Chen; Berthold Göttgens; Ju-Seog Lee; Preethi Gunaratne; Lucy A Godley; Gretchen J Darlington; Anjana Rao; Wei Li; Margaret A Goodell
Journal:  Nat Genet       Date:  2013-11-24       Impact factor: 38.330

Review 10.  Base resolution methylome profiling: considerations in platform selection, data preprocessing and analysis.

Authors:  Zhifu Sun; Julie Cunningham; Susan Slager; Jean-Pierre Kocher
Journal:  Epigenomics       Date:  2015-09-14       Impact factor: 4.778

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